Assignment Prompt & Instructions
– ## Module6DBOGL554.docx
– ## LEARNINGMATERIALSModule6.docx
**## Module6DBOGL554.docx**
Module 6: Discussion: AI and Training Development
Welcome OGL 554: Training and Development Crew to our Module 6 Discussion!
As you dive into the content for this week and consider the discussion prompts, please reflect on your experiences with trainings, as well as the materials. Each Module's Discussion Board will provide an opportunity to engage more deeply with something that interests you from the text and learning materials, listen, engage with the perspectives of your peers on these topics and share aspects of the project development process.
We are here to help each other learn, grow and strengthen our insights, evaluative capacities and skills. This is a cooperative process. Generative critiques between peers can prompt us to ask questions about our work and the contributions of fellow colleagues regarding how a specific training could be improved or whether another avenue of address could be engaged to make a substantive difference in the effectiveness of a training. Thank you all for your collegial engagement!
**Step One:** After engaging with the learning materials for this week, please respond to each of the following prompts with an Initial Post.
**1- Find two sources related to AI and Training**
Summarize two sources
about how AI can help facilitate
the development of effective training.
Please provide the bibliographic citation and links.
**2- Social Responsibility, Ethics and Culture**
After engaging the learning materials for this week, please share your reflections on where ethics and AI intersect when t in successful professional development programs. What are three ways that socially responsible companies could invest in cultivating equitable environments, with thriving partnerships, support for career development at all stages, and successful L&D? (Please note: I am not asking about diversity training or "managing diversity"). Requirements: scope at least 200 words and
**must** include
**at least one** references from Module 6, cited and referenced using APA formatting.
**LEARNING MATERIALS AND RESOURCES ARE ATTACHED IN A SEPARATE PAGE**
**## LEARNINGMATERIALSModule6.docx**
LEARNING MATERIALS
[https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/](https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/)
[https://www.ted.com/talks/leah_georges_how_generational_stereotypes_hold_us_back_at_work](https://www.ted.com/talks/leah_georges_how_generational_stereotypes_hold_us_back_at_work)
[https://www.ted.com/talks/adam_grant_are_you_a_giver_or_a_taker?language=en](https://www.ted.com/talks/adam_grant_are_you_a_giver_or_a_taker?language=en)
[https://www.ted.com/talks/regina_hartley_why_the_best_hire_might_not_have_the_perfect_resume](https://www.ted.com/talks/regina_hartley_why_the_best_hire_might_not_have_the_perfect_resume)
Read the following:
· Chapter 10 in Noe "Social Responsibility"
· Chapter 11 Noe "The Future of Training"
Example of what other students wrote
**1- Find two sources related to AI and Training**
**Source #1**
In their 2021 article, Luo et al. explore how artificial intelligence (AI) can enhance the development of effective training for sales agents. They explain that AI coaching tools can analyze large volumes of sales interactions to identify patterns of successful behaviors and deliver personalized, real-time feedback. This allows employees to develop their skills continuously and at their own pace, making training more dynamic and scalable across large teams. AI supports individualized learning by helping agents improve communication and customer engagement strategies based on data-driven insights. However, the authors also caution against overreliance on AI, noting risks such as dehumanization, deskilling, and privacy concerns. To maximize effectiveness and maintain employee trust, they recommend integrating AI within hybrid coaching models that combine the consistency and scale of AI with the emotional intelligence and mentorship provided by human managers.
Luo, X., Qin, M. S., Fang, Z., & Qu, Z. (2021). Artificial Intelligence Coaches for Sales Agents: Caveats and Solutions. Journal of Marketing, 85(2), 14–32.
[https://doi.org/10.1177/0022242920956676Links to an external site.](https://doi.org/10.1177/0022242920956676)
**Source #2**
In their 2021 article, Ronquillo et al. highlight the role of artificial intelligence (AI) in advancing effective training and professional development in nursing. The authors emphasize that AI has the potential to transform nursing education by supporting personalized learning, enhancing clinical decision-making, and enabling high-quality simulation experiences. AI systems can analyze data on individual learners to tailor educational content, identify skill gaps, and adapt instruction in real time. Additionally, AI-powered simulations allow nurses to engage in realistic, scenario-based training that builds critical thinking and clinical competencies in a safe environment. The article also stresses the importance of involving nurses in the development and implementation of AI tools to ensure they are ethically designed and aligned with the realities of clinical practice. Overall, AI is positioned as a powerful tool to improve the effectiveness, efficiency, and accessibility of training in the nursing profession.
Ronquillo, C. E., Peltonen, L., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., Cato, K., Hardiker, N., Junger, A., Michalowski, M., Nyrup, R., Rahimi, S., Reed, D. N., Salakoski, T., Salanterä, S., Walton, N., Weber, P., Wiegand, T., & Topaz, M. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative.
_Journal of Advanced Nursing_,
_77_(9), 3707–3717.
[https://doi.org/10.1111/jan.14855Links to an external site.](https://doi.org/10.1111/jan.14855)
**2- Social Responsibility, Ethics and Culture**
The intersection of ethics and AI in professional development programs presents both exciting potential and critical responsibility. As organizations adopt AI tools for learning and development, ethical considerations must guide their design and implementation. For example, AI can unintentionally reinforce biases if it draws from unbalanced data, which could hinder rather than support equitable career development. Noe (2023) highlights the importance of ensuring that technology-enhanced training methods are accessible and inclusive, promoting ethical use by prioritizing fairness, privacy, and transparency.
Socially responsible companies can invest in cultivating equitable environments in three key ways. First, they can create personalized development pathways supported by ethical AI that adapts to learners’ goals and learning styles. Second, they should establish long-term mentoring programs that bridge positional gaps across all career stages. Third, companies can form community and educational partnerships that expand access to skill-building opportunities for underserved populations, ensuring the organization’s talent pipeline reflects broader societal equity.
**Reference**
Noe, R. A. (2023). Employee training and development (9th ed.). McGraw Hill.
**1- Find two sources related to AI and Training**
Mohammed, A. H., Othman, Z. J., & Abdullah, A. I. (2024). The Role of Artificial Intelligence in Enhancing Sports Analytics and Training.
_Cihan University-Erbil Scientific Journal (Onine)_,
_8_(1), 58–62.
[https://doi.org/10.24086/cuesj.v8n1y2024.pp58-62Links to an external site.](https://doi.org/10.24086/cuesj.v8n1y2024.pp58-62)
This article by Mohammed, Othman, and Abdullah (2024) investigates how modern technology is changing the way athletes train and how sports are analyzed. It explains how tools like computer vision and data tracking are being used to monitor athletic performance, spot patterns, and create more personalized training routines. Coaches can now make better decisions and even reduce the risk of injuries by catching issues early. The authors also mention a few obstacles, like the excessive cost of these systems and the need for people who understand how to use them. Overall, the article shows how this kind of technology is becoming a valuable part of modern sports.
This article shows how AI helps athletes train smarter, not just harder. By using tools that track how someone moves or performs over time, coaches and trainers can figure out exactly what an athlete needs to work on. Instead of giving everyone the same plan, the training becomes more personal and focused. It also helps catch things like bad form or signs of overtraining before they turn into injuries. This kind of approach makes the whole training process more effective because it is based on real data, not just guesswork or one-size-fits-all routines.
Kaldarova, B., Toktarova, A., & Abdrakhmanov, R. (2024). Enhancing deadlift training through an artificial intelligence-driven personal coaching system using skeletal analysis.
_Retos (Madrid)_,
_60_(60), 439–448.
[https://doi.org/10.47197/retos.v60.109183Links to an external site.](https://doi.org/10.47197/retos.v60.109183)
This article looks at how technology can help people get better at doing deadlifts. The authors talk about a coaching system that uses AI to watch how someone moves while lifting. It focuses on things like posture and technique and gives feedback to help improve form. What is useful is that it can point out small mistakes before they turn into injuries. By using this kind of system, people can train safely and get better results. It is a good example of how tech and fitness can work together to make workouts more effective.
The article also shows how AI can make training more effective by giving people real-time feedback on their form and technique. Instead of waiting for a coach to correct mistakes, the system uses motion tracking to spot issues right away, which helps people fix them before they lead to injuries or unhealthy habits. It also makes training more personalized since the feedback is based on each person’s unique movement patterns. This kind of detailed guidance helps people train more efficiently and safely, which is exactly what effective training should do.
**2- Social Responsibility, Ethics and Culture**
When I think about ethics and AI, especially in the context of socially responsible companies or military organizations, three key actions stand out. First, there must be a commitment to building ethical AI systems that are transparent, accountable, and free from bias—particularly in processes like hiring, performance evaluation, and training assignments. This helps ensure fairness and trust. Second, organizations should use AI to personalize career development, offering tailored learning paths that support individuals at every stage of their careers, from onboarding to leadership roles. This kind of support increases access and opportunity for all employees or service members. Third, investing in strong partnerships with educational institutions, community groups, and veteran-focused programs can broaden access to training, digital literacy, and long-term career growth. In the military, applying these principles strengthens not only the development of the individual but also overall mission readiness, ethical leadership, and trust within the ranks and the communities they serve.
I have always found the concept of AI fascinating for business, especially in today’s digital world where, if applied correctly, it can lead to significant positive results. That said, it’s clear that developing stronger digital skills is essential for workforce readiness and employability. According to Noe, “The current education-to-employment system is not adequately preparing students and adults for the 21st century economy. As the future workplace becomes increasingly digitized, employees will need digital literacy skills” (p 1185).
**Reference**
Noe, R. A. (2023).
_Employee training & development_ (9th ed.). McGraw-Hill Education
**1- Find two sources related to AI and Training**
**Source #1**
In their 2021 article, Luo et al. explore how artificial intelligence (AI) can enhance the development of effective training for sales agents. They explain that AI coaching tools can analyze large volumes of sales interactions to identify patterns of successful behaviors and deliver personalized, real-time feedback. This allows employees to develop their skills continuously and at their own pace, making training more dynamic and scalable across large teams. AI supports individualized learning by helping agents improve communication and customer engagement strategies based on data-driven insights. However, the authors also caution against overreliance on AI, noting risks such as dehumanization, deskilling, and privacy concerns. To maximize effectiveness and maintain employee trust, they recommend integrating AI within hybrid coaching models that combine the consistency and scale of AI with the emotional intelligence and mentorship provided by human managers.
Luo, X., Qin, M. S., Fang, Z., & Qu, Z. (2021). Artificial Intelligence Coaches for Sales Agents: Caveats and Solutions. Journal of Marketing, 85(2), 14–32.
[https://doi.org/10.1177/0022242920956676Links to an external site.](https://doi.org/10.1177/0022242920956676)
**Source #2**
In their 2021 article, Ronquillo et al. highlight the role of artificial intelligence (AI) in advancing effective training and professional development in nursing. The authors emphasize that AI has the potential to transform nursing education by supporting personalized learning, enhancing clinical decision-making, and enabling high-quality simulation experiences. AI systems can analyze data on individual learners to tailor educational content, identify skill gaps, and adapt instruction in real time. Additionally, AI-powered simulations allow nurses to engage in realistic, scenario-based training that builds critical thinking and clinical competencies in a safe environment. The article also stresses the importance of involving nurses in the development and implementation of AI tools to ensure they are ethically designed and aligned with the realities of clinical practice. Overall, AI is positioned as a powerful tool to improve the effectiveness, efficiency, and accessibility of training in the nursing profession.
Ronquillo, C. E., Peltonen, L., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., Cato, K., Hardiker, N., Junger, A., Michalowski, M., Nyrup, R., Rahimi, S., Reed, D. N., Salakoski, T., Salanterä, S., Walton, N., Weber, P., Wiegand, T., & Topaz, M. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative.
_Journal of Advanced Nursing_,
_77_(9), 3707–3717.
[https://doi.org/10.1111/jan.14855Links to an external site.](https://doi.org/10.1111/jan.14855)
**2- Social Responsibility, Ethics and Culture**
The intersection of ethics and AI in professional development programs presents both exciting potential and critical responsibility. As organizations adopt AI tools for learning and development, ethical considerations must guide their design and implementation. For example, AI can unintentionally reinforce biases if it draws from unbalanced data, which could hinder rather than support equitable career development. Noe (2023) highlights the importance of ensuring that technology-enhanced training methods are accessible and inclusive, promoting ethical use by prioritizing fairness, privacy, and transparency.
Socially responsible companies can invest in cultivating equitable environments in three key ways. First, they can create personalized development pathways supported by ethical AI that adapts to learners’ goals and learning styles. Second, they should establish long-term mentoring programs that bridge positional gaps across all career stages. Third, companies can form community and educational partnerships that expand access to skill-building opportunities for underserved populations, ensuring the organization’s talent pipeline reflects broader societal equity.
**Reference**
Noe, R. A. (2023). Employee training and development (9th ed.). McGraw Hill.
**Summarize two sources about how AI can help facilitate the development of effective training.**
Bayly-Castaneda, K., Ramirez-Montoya, M.-S., & Morita-Alexander, A. (2024). Crafting personalized learning paths with AI for lifelong learning: a systematic literature review.
_Frontiers in Education (Lausanne)_,
_9_.
[https://doi.org/10.3389/feduc.2024.1424386Links to an external site.](https://doi.org/10.3389/feduc.2024.1424386)
· This article conducts a systematic literature review on existing research relating to artificial intelligence and lifelong learning. It posits that artificial intelligence has the capability to create personalized strategies for lifelong learning, which is a benefit for different learners. It also addresses the ethical issues created by the research divide globally. Due to the fact that research in some countries is more developed than in others, biases are created within algorithms that have the potential to impact lifelong learning. Overall, this article views artificial intelligence as a tool to enhance lifelong learning.
Chen, Z. (2024). [Rev. of
_Responsible AI in Organizational Training: Applications, Implications, and Recommendations for Future Development_].
_Human Resource Development Review_,
_23_(4), 498–521.
[https://doi.org/10.1177/15344843241273316Links to an external site.](https://doi.org/10.1177/15344843241273316)
· This article examines the potential interaction between artificial intelligence and Human Resource Development practices. It notes that the sensitivity of human data and information in this field creates ethical concerns about the use of AI. However, the article emphasizes that when responsibly governed, artificial intelligence can transform training processes, provided there is alignment with ethical standards, stakeholder needs, and strategic HRD principles. By creating a roadmap on how organizations can integrate AI effectively, ethically, and responsibly, this article forecasts future trends.
**2- Social Responsibility, Ethics and Culture**
After engaging with this week’s learning materials, the rapid development of AI technology creates interesting ethical dilemmas relating to professional development and training. Artificial intelligence has the capability to push the boundaries of what is possible when it comes to education and training. AI models can create customized learning environments that overcome traditional barriers. Due to the autonomous nature of AI recommendations, it is imperative that employees understand the ethical and moral implications of relying on these decisions. As such, the first way companies can support successful L&D with AI would be to articulate standards for use. Landrum (2018) asserts that ethical breaches result from miseducation about company mission and a lack of access to resources. Ensuring that employees have clear expectations about AI use through training and aligning said expectations to organizational missions will support success. Additionally, companies can foster ethical environments by addressing generational gaps that may inhibit AI usage. As Georges (2019) posits in her TedTalk, the current generational divide in the workplace creates age-based stereotypes that can inhibit growth. Using training as an opportunity to “debunk” these stereotypes by creating a space for all to learn equitable strategies for AI usage will benefit socially responsible organizations. Finally, organizations should implement organizational learning to generate feedback loops about AI usage. This technology is so new and rapidly evolving. Continuing to evaluate and strengthen its relationship with training and ensuring that ethical standards are applied is absolutely necessary.
Landrum, S. (2018, August 8).
_Addressing Ethics in Training – Training Industry_. Training Industry.
[https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/Links to an external site.](https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/)
Georges, L. (2019). How generational stereotypes hold us back at work | Leah Georges [YouTube Video]. In
_YouTube_. https://www.youtube.com/watch?v=dKNu5ZnWhb4
Module 6 Discussion
**Two Sources on AI and Training**
**Source 1:** _AI Implementation Impact on Workforce Productivity: The Role of AI Training and Organizational Adaptation_
This study investigated the impact of AI implementation on workforce productivity by focusing on the mediating roles of organizational adaptation and AI Training. The findings indicated that the implementation of AI significantly impacts both AI Training and Organizational Adaptation, which in turn influence workplace productivity. This relationship highlights significant comprehensive strategies that encompass technological adoption, employee training, and organizational flexibility. The recommendation from these findings for the company was to continue to prioritize AI training initiatives to ensure that its employees have the necessary skills to harness AI's potential.
**Nurlia, N., Daud, I., & Rosadi, M. E. (2023). AI Implementation Impact on Workforce Productivity: The Role of AI Training and Organizational Adaptation. Escalate Economics and Business Journal, 1(01), 01-13.** [**https://doi.org/10.61536/escalate.v1i01.6** Links to an external site.](https://doi.org/10.61536/escalate.v1i01.6) ****
**Source 2:** _Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice, and policy_.
This article brings collective insight from collaborators within the industry, academia, and the public sector to highlight the opportunities, challenges, and potential research into the AI technological potential application. One of those potential ideas was using AI-powered platforms to assess performance metrics and provide personalized learning paths through training. This would allow for more strategic and data-informed training that could be widely popular within he organizational sectors. The article finished that the cultural perspective on AI decision marketing and transparency as to how this technology works is key for building support for advancement and technological acceptance.
**Dwivedi, Y. K., et al. (2021).**
**_Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy_. International Journal of Information Management, 57, 101994.** [**https://doi.org/10.1016/j.ijinfomgt.2019.08.002** Links to an external site.](https://doi.org/10.1016/j.ijinfomgt.2019.08.002)
**Social Responsibility, Ethics, and Culture**
As society moves forward with AI use in professional spaces, as with any advancement in technology, the ethical considerations must remain central with that advancement. Changes in automation, such as those in decision-making, learner evaluations, and content delivery, can be unintentionally used in harmful ways. On the backside of AI, we must ensure we are using inclusive data sets to train AT not to replicate biases in its use. At the front of it we need to be creating spaces of equal opportunity to learn that technology to level the playing field for professional development within our organizations.
1.
**Inclusive AI Design** – Not knowing a ton about the backside of AI could be detrimental for a company hoping to use it within their departments and institutions. Having someone working with that technology company to ensure that any AI used in learning and development platforms is developed using diverse data sets and audited regularly for consistency in those areas would be a huge help to those wanting to stay in alignment with their mission, vision, and values.
2.
**Career Development Accessibility** – Using AI to create more accessible and customizable learning experiences for its employees is another key way a company or institution could invest in AI. In chapter 10, we learned about the Americans with Disabilities Act (ADA) and the requirements that go along with it (Noe, 466, 2023). With that being said, this is typically not enough, and gaps are still apparent. There is not always an equitable opportunity; however, AI could change that. Offering reskilling opportunities for older workers, entry-level support, and an adaptable curriculum to accommodate employees with disabilities, this could be a game-changer to continue to push for a more equitable experience.
3.
**Human-AI Collaboration Culture** – The last way companies could use AI in a sociality responsible way is through ethical and robust training on AI usage. AI is not going anywhere, just as the calculator made math harder, allowing us to achieve more, AI will do the same for automatic processing and decision making. Training to teach us to understand, interpret, and audit AI data rather than rely on it blindly will allow us to grow with the technology and push it to its capabilities. This will also ensure we are encouraging human dialogue and feedback that matches the values of the individuals in a way that promotes trust, transparency, and advancement.
In this way, AI becomes a tool not just for efficiency, but for equity and organizational empathy that will move us into the future.
**Reference** Noe, R. A. (2023).
_Employee Training and Development_. McGraw Hill, Cop.
**## LEARNINGMATERIALSModule6.docx**
LEARNING MATERIALS
[https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/](https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/)
[https://www.ted.com/talks/leah_georges_how_generational_stereotypes_hold_us_back_at_work](https://www.ted.com/talks/leah_georges_how_generational_stereotypes_hold_us_back_at_work)
[https://www.ted.com/talks/adam_grant_are_you_a_giver_or_a_taker?language=en](https://www.ted.com/talks/adam_grant_are_you_a_giver_or_a_taker?language=en)
[https://www.ted.com/talks/regina_hartley_why_the_best_hire_might_not_have_the_perfect_resume](https://www.ted.com/talks/regina_hartley_why_the_best_hire_might_not_have_the_perfect_resume)
Read the following:
· Chapter 10 in Noe "Social Responsibility"
· Chapter 11 Noe "The Future of Training"
Example of what other students wrote
**1- Find two sources related to AI and Training**
**Source #1**
In their 2021 article, Luo et al. explore how artificial intelligence (AI) can enhance the development of effective training for sales agents. They explain that AI coaching tools can analyze large volumes of sales interactions to identify patterns of successful behaviors and deliver personalized, real-time feedback. This allows employees to develop their skills continuously and at their own pace, making training more dynamic and scalable across large teams. AI supports individualized learning by helping agents improve communication and customer engagement strategies based on data-driven insights. However, the authors also caution against overreliance on AI, noting risks such as dehumanization, deskilling, and privacy concerns. To maximize effectiveness and maintain employee trust, they recommend integrating AI within hybrid coaching models that combine the consistency and scale of AI with the emotional intelligence and mentorship provided by human managers.
Luo, X., Qin, M. S., Fang, Z., & Qu, Z. (2021). Artificial Intelligence Coaches for Sales Agents: Caveats and Solutions. Journal of Marketing, 85(2), 14–32.
[https://doi.org/10.1177/0022242920956676Links to an external site.](https://doi.org/10.1177/0022242920956676)
**Source #2**
In their 2021 article, Ronquillo et al. highlight the role of artificial intelligence (AI) in advancing effective training and professional development in nursing. The authors emphasize that AI has the potential to transform nursing education by supporting personalized learning, enhancing clinical decision-making, and enabling high-quality simulation experiences. AI systems can analyze data on individual learners to tailor educational content, identify skill gaps, and adapt instruction in real time. Additionally, AI-powered simulations allow nurses to engage in realistic, scenario-based training that builds critical thinking and clinical competencies in a safe environment. The article also stresses the importance of involving nurses in the development and implementation of AI tools to ensure they are ethically designed and aligned with the realities of clinical practice. Overall, AI is positioned as a powerful tool to improve the effectiveness, efficiency, and accessibility of training in the nursing profession.
Ronquillo, C. E., Peltonen, L., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., Cato, K., Hardiker, N., Junger, A., Michalowski, M., Nyrup, R., Rahimi, S., Reed, D. N., Salakoski, T., Salanterä, S., Walton, N., Weber, P., Wiegand, T., & Topaz, M. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative.
_Journal of Advanced Nursing_,
_77_(9), 3707–3717.
[https://doi.org/10.1111/jan.14855Links to an external site.](https://doi.org/10.1111/jan.14855)
**2- Social Responsibility, Ethics and Culture**
The intersection of ethics and AI in professional development programs presents both exciting potential and critical responsibility. As organizations adopt AI tools for learning and development, ethical considerations must guide their design and implementation. For example, AI can unintentionally reinforce biases if it draws from unbalanced data, which could hinder rather than support equitable career development. Noe (2023) highlights the importance of ensuring that technology-enhanced training methods are accessible and inclusive, promoting ethical use by prioritizing fairness, privacy, and transparency.
Socially responsible companies can invest in cultivating equitable environments in three key ways. First, they can create personalized development pathways supported by ethical AI that adapts to learners’ goals and learning styles. Second, they should establish long-term mentoring programs that bridge positional gaps across all career stages. Third, companies can form community and educational partnerships that expand access to skill-building opportunities for underserved populations, ensuring the organization’s talent pipeline reflects broader societal equity.
**Reference**
Noe, R. A. (2023). Employee training and development (9th ed.). McGraw Hill.
**1- Find two sources related to AI and Training**
Mohammed, A. H., Othman, Z. J., & Abdullah, A. I. (2024). The Role of Artificial Intelligence in Enhancing Sports Analytics and Training.
_Cihan University-Erbil Scientific Journal (Onine)_,
_8_(1), 58–62.
[https://doi.org/10.24086/cuesj.v8n1y2024.pp58-62Links to an external site.](https://doi.org/10.24086/cuesj.v8n1y2024.pp58-62)
This article by Mohammed, Othman, and Abdullah (2024) investigates how modern technology is changing the way athletes train and how sports are analyzed. It explains how tools like computer vision and data tracking are being used to monitor athletic performance, spot patterns, and create more personalized training routines. Coaches can now make better decisions and even reduce the risk of injuries by catching issues early. The authors also mention a few obstacles, like the excessive cost of these systems and the need for people who understand how to use them. Overall, the article shows how this kind of technology is becoming a valuable part of modern sports.
This article shows how AI helps athletes train smarter, not just harder. By using tools that track how someone moves or performs over time, coaches and trainers can figure out exactly what an athlete needs to work on. Instead of giving everyone the same plan, the training becomes more personal and focused. It also helps catch things like bad form or signs of overtraining before they turn into injuries. This kind of approach makes the whole training process more effective because it is based on real data, not just guesswork or one-size-fits-all routines.
Kaldarova, B., Toktarova, A., & Abdrakhmanov, R. (2024). Enhancing deadlift training through an artificial intelligence-driven personal coaching system using skeletal analysis.
_Retos (Madrid)_,
_60_(60), 439–448.
[https://doi.org/10.47197/retos.v60.109183Links to an external site.](https://doi.org/10.47197/retos.v60.109183)
This article looks at how technology can help people get better at doing deadlifts. The authors talk about a coaching system that uses AI to watch how someone moves while lifting. It focuses on things like posture and technique and gives feedback to help improve form. What is useful is that it can point out small mistakes before they turn into injuries. By using this kind of system, people can train safely and get better results. It is a good example of how tech and fitness can work together to make workouts more effective.
The article also shows how AI can make training more effective by giving people real-time feedback on their form and technique. Instead of waiting for a coach to correct mistakes, the system uses motion tracking to spot issues right away, which helps people fix them before they lead to injuries or unhealthy habits. It also makes training more personalized since the feedback is based on each person’s unique movement patterns. This kind of detailed guidance helps people train more efficiently and safely, which is exactly what effective training should do.
**2- Social Responsibility, Ethics and Culture**
When I think about ethics and AI, especially in the context of socially responsible companies or military organizations, three key actions stand out. First, there must be a commitment to building ethical AI systems that are transparent, accountable, and free from bias—particularly in processes like hiring, performance evaluation, and training assignments. This helps ensure fairness and trust. Second, organizations should use AI to personalize career development, offering tailored learning paths that support individuals at every stage of their careers, from onboarding to leadership roles. This kind of support increases access and opportunity for all employees or service members. Third, investing in strong partnerships with educational institutions, community groups, and veteran-focused programs can broaden access to training, digital literacy, and long-term career growth. In the military, applying these principles strengthens not only the development of the individual but also overall mission readiness, ethical leadership, and trust within the ranks and the communities they serve.
I have always found the concept of AI fascinating for business, especially in today’s digital world where, if applied correctly, it can lead to significant positive results. That said, it’s clear that developing stronger digital skills is essential for workforce readiness and employability. According to Noe, “The current education-to-employment system is not adequately preparing students and adults for the 21st century economy. As the future workplace becomes increasingly digitized, employees will need digital literacy skills” (p 1185).
**Reference**
Noe, R. A. (2023).
_Employee training & development_ (9th ed.). McGraw-Hill Education
**1- Find two sources related to AI and Training**
**Source #1**
In their 2021 article, Luo et al. explore how artificial intelligence (AI) can enhance the development of effective training for sales agents. They explain that AI coaching tools can analyze large volumes of sales interactions to identify patterns of successful behaviors and deliver personalized, real-time feedback. This allows employees to develop their skills continuously and at their own pace, making training more dynamic and scalable across large teams. AI supports individualized learning by helping agents improve communication and customer engagement strategies based on data-driven insights. However, the authors also caution against overreliance on AI, noting risks such as dehumanization, deskilling, and privacy concerns. To maximize effectiveness and maintain employee trust, they recommend integrating AI within hybrid coaching models that combine the consistency and scale of AI with the emotional intelligence and mentorship provided by human managers.
Luo, X., Qin, M. S., Fang, Z., & Qu, Z. (2021). Artificial Intelligence Coaches for Sales Agents: Caveats and Solutions. Journal of Marketing, 85(2), 14–32.
[https://doi.org/10.1177/0022242920956676Links to an external site.](https://doi.org/10.1177/0022242920956676)
**Source #2**
In their 2021 article, Ronquillo et al. highlight the role of artificial intelligence (AI) in advancing effective training and professional development in nursing. The authors emphasize that AI has the potential to transform nursing education by supporting personalized learning, enhancing clinical decision-making, and enabling high-quality simulation experiences. AI systems can analyze data on individual learners to tailor educational content, identify skill gaps, and adapt instruction in real time. Additionally, AI-powered simulations allow nurses to engage in realistic, scenario-based training that builds critical thinking and clinical competencies in a safe environment. The article also stresses the importance of involving nurses in the development and implementation of AI tools to ensure they are ethically designed and aligned with the realities of clinical practice. Overall, AI is positioned as a powerful tool to improve the effectiveness, efficiency, and accessibility of training in the nursing profession.
Ronquillo, C. E., Peltonen, L., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., Cato, K., Hardiker, N., Junger, A., Michalowski, M., Nyrup, R., Rahimi, S., Reed, D. N., Salakoski, T., Salanterä, S., Walton, N., Weber, P., Wiegand, T., & Topaz, M. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative.
_Journal of Advanced Nursing_,
_77_(9), 3707–3717.
[https://doi.org/10.1111/jan.14855Links to an external site.](https://doi.org/10.1111/jan.14855)
**2- Social Responsibility, Ethics and Culture**
The intersection of ethics and AI in professional development programs presents both exciting potential and critical responsibility. As organizations adopt AI tools for learning and development, ethical considerations must guide their design and implementation. For example, AI can unintentionally reinforce biases if it draws from unbalanced data, which could hinder rather than support equitable career development. Noe (2023) highlights the importance of ensuring that technology-enhanced training methods are accessible and inclusive, promoting ethical use by prioritizing fairness, privacy, and transparency.
Socially responsible companies can invest in cultivating equitable environments in three key ways. First, they can create personalized development pathways supported by ethical AI that adapts to learners’ goals and learning styles. Second, they should establish long-term mentoring programs that bridge positional gaps across all career stages. Third, companies can form community and educational partnerships that expand access to skill-building opportunities for underserved populations, ensuring the organization’s talent pipeline reflects broader societal equity.
**Reference**
Noe, R. A. (2023). Employee training and development (9th ed.). McGraw Hill.
**Summarize two sources about how AI can help facilitate the development of effective training.**
Bayly-Castaneda, K., Ramirez-Montoya, M.-S., & Morita-Alexander, A. (2024). Crafting personalized learning paths with AI for lifelong learning: a systematic literature review.
_Frontiers in Education (Lausanne)_,
_9_.
[https://doi.org/10.3389/feduc.2024.1424386Links to an external site.](https://doi.org/10.3389/feduc.2024.1424386)
· This article conducts a systematic literature review on existing research relating to artificial intelligence and lifelong learning. It posits that artificial intelligence has the capability to create personalized strategies for lifelong learning, which is a benefit for different learners. It also addresses the ethical issues created by the research divide globally. Due to the fact that research in some countries is more developed than in others, biases are created within algorithms that have the potential to impact lifelong learning. Overall, this article views artificial intelligence as a tool to enhance lifelong learning.
Chen, Z. (2024). [Rev. of
_Responsible AI in Organizational Training: Applications, Implications, and Recommendations for Future Development_].
_Human Resource Development Review_,
_23_(4), 498–521.
[https://doi.org/10.1177/15344843241273316Links to an external site.](https://doi.org/10.1177/15344843241273316)
· This article examines the potential interaction between artificial intelligence and Human Resource Development practices. It notes that the sensitivity of human data and information in this field creates ethical concerns about the use of AI. However, the article emphasizes that when responsibly governed, artificial intelligence can transform training processes, provided there is alignment with ethical standards, stakeholder needs, and strategic HRD principles. By creating a roadmap on how organizations can integrate AI effectively, ethically, and responsibly, this article forecasts future trends.
**2- Social Responsibility, Ethics and Culture**
After engaging with this week’s learning materials, the rapid development of AI technology creates interesting ethical dilemmas relating to professional development and training. Artificial intelligence has the capability to push the boundaries of what is possible when it comes to education and training. AI models can create customized learning environments that overcome traditional barriers. Due to the autonomous nature of AI recommendations, it is imperative that employees understand the ethical and moral implications of relying on these decisions. As such, the first way companies can support successful L&D with AI would be to articulate standards for use. Landrum (2018) asserts that ethical breaches result from miseducation about company mission and a lack of access to resources. Ensuring that employees have clear expectations about AI use through training and aligning said expectations to organizational missions will support success. Additionally, companies can foster ethical environments by addressing generational gaps that may inhibit AI usage. As Georges (2019) posits in her TedTalk, the current generational divide in the workplace creates age-based stereotypes that can inhibit growth. Using training as an opportunity to “debunk” these stereotypes by creating a space for all to learn equitable strategies for AI usage will benefit socially responsible organizations. Finally, organizations should implement organizational learning to generate feedback loops about AI usage. This technology is so new and rapidly evolving. Continuing to evaluate and strengthen its relationship with training and ensuring that ethical standards are applied is absolutely necessary.
Landrum, S. (2018, August 8).
_Addressing Ethics in Training – Training Industry_. Training Industry.
[https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/Links to an external site.](https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/)
Georges, L. (2019). How generational stereotypes hold us back at work | Leah Georges [YouTube Video]. In
_YouTube_. https://www.youtube.com/watch?v=dKNu5ZnWhb4
Module 6 Discussion
**Two Sources on AI and Training**
**Source 1:** _AI Implementation Impact on Workforce Productivity: The Role of AI Training and Organizational Adaptation_
This study investigated the impact of AI implementation on workforce productivity by focusing on the mediating roles of organizational adaptation and AI Training. The findings indicated that the implementation of AI significantly impacts both AI Training and Organizational Adaptation, which in turn influence workplace productivity. This relationship highlights significant comprehensive strategies that encompass technological adoption, employee training, and organizational flexibility. The recommendation from these findings for the company was to continue to prioritize AI training initiatives to ensure that its employees have the necessary skills to harness AI's potential.
**Nurlia, N., Daud, I., & Rosadi, M. E. (2023). AI Implementation Impact on Workforce Productivity: The Role of AI Training and Organizational Adaptation. Escalate Economics and Business Journal, 1(01), 01-13.** [**https://doi.org/10.61536/escalate.v1i01.6** Links to an external site.](https://doi.org/10.61536/escalate.v1i01.6) ****
**Source 2:** _Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice, and policy_.
This article brings collective insight from collaborators within the industry, academia, and the public sector to highlight the opportunities, challenges, and potential research into the AI technological potential application. One of those potential ideas was using AI-powered platforms to assess performance metrics and provide personalized learning paths through training. This would allow for more strategic and data-informed training that could be widely popular within he organizational sectors. The article finished that the cultural perspective on AI decision marketing and transparency as to how this technology works is key for building support for advancement and technological acceptance.
**Dwivedi, Y. K., et al. (2021).**
**_Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy_. International Journal of Information Management, 57, 101994.** [**https://doi.org/10.1016/j.ijinfomgt.2019.08.002** Links to an external site.](https://doi.org/10.1016/j.ijinfomgt.2019.08.002)
**Social Responsibility, Ethics, and Culture**
As society moves forward with AI use in professional spaces, as with any advancement in technology, the ethical considerations must remain central with that advancement. Changes in automation, such as those in decision-making, learner evaluations, and content delivery, can be unintentionally used in harmful ways. On the backside of AI, we must ensure we are using inclusive data sets to train AT not to replicate biases in its use. At the front of it we need to be creating spaces of equal opportunity to learn that technology to level the playing field for professional development within our organizations.
1.
**Inclusive AI Design** – Not knowing a ton about the backside of AI could be detrimental for a company hoping to use it within their departments and institutions. Having someone working with that technology company to ensure that any AI used in learning and development platforms is developed using diverse data sets and audited regularly for consistency in those areas would be a huge help to those wanting to stay in alignment with their mission, vision, and values.
2.
**Career Development Accessibility** – Using AI to create more accessible and customizable learning experiences for its employees is another key way a company or institution could invest in AI. In chapter 10, we learned about the Americans with Disabilities Act (ADA) and the requirements that go along with it (Noe, 466, 2023). With that being said, this is typically not enough, and gaps are still apparent. There is not always an equitable opportunity; however, AI could change that. Offering reskilling opportunities for older workers, entry-level support, and an adaptable curriculum to accommodate employees with disabilities, this could be a game-changer to continue to push for a more equitable experience.
3.
**Human-AI Collaboration Culture** – The last way companies could use AI in a sociality responsible way is through ethical and robust training on AI usage. AI is not going anywhere, just as the calculator made math harder, allowing us to achieve more, AI will do the same for automatic processing and decision making. Training to teach us to understand, interpret, and audit AI data rather than rely on it blindly will allow us to grow with the technology and push it to its capabilities. This will also ensure we are encouraging human dialogue and feedback that matches the values of the individuals in a way that promotes trust, transparency, and advancement.
In this way, AI becomes a tool not just for efficiency, but for equity and organizational empathy that will move us into the future.
**Reference** Noe, R. A. (2023).
_Employee Training and Development_. McGraw Hill, Cop.
**## Module6DBOGL554.docx**
Module 6: Discussion: AI and Training Development
Welcome OGL 554: Training and Development Crew to our Module 6 Discussion!
As you dive into the content for this week and consider the discussion prompts, please reflect on your experiences with trainings, as well as the materials. Each Module's Discussion Board will provide an opportunity to engage more deeply with something that interests you from the text and learning materials, listen, engage with the perspectives of your peers on these topics and share aspects of the project development process.
We are here to help each other learn, grow and strengthen our insights, evaluative capacities and skills. This is a cooperative process. Generative critiques between peers can prompt us to ask questions about our work and the contributions of fellow colleagues regarding how a specific training could be improved or whether another avenue of address could be engaged to make a substantive difference in the effectiveness of a training. Thank you all for your collegial engagement!
**Step One:** After engaging with the learning materials for this week, please respond to each of the following prompts with an Initial Post.
**1- Find two sources related to AI and Training**
Summarize two sources
about how AI can help facilitate
the development of effective training.
Please provide the bibliographic citation and links.
**2- Social Responsibility, Ethics and Culture**
After engaging the learning materials for this week, please share your reflections on where ethics and AI intersect when t in successful professional development programs. What are three ways that socially responsible companies could invest in cultivating equitable environments, with thriving partnerships, support for career development at all stages, and successful L&D? (Please note: I am not asking about diversity training or "managing diversity"). Requirements: scope at least 200 words and
**must** include
**at least one** references from Module 6, cited and referenced using APA formatting.
**LEARNING MATERIALS AND RESOURCES ARE ATTACHED IN A SEPARATE PAGE**
**## LEARNINGMATERIALSModule6.docx**
LEARNING MATERIALS
[https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/](https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/)
[https://www.ted.com/talks/leah_georges_how_generational_stereotypes_hold_us_back_at_work](https://www.ted.com/talks/leah_georges_how_generational_stereotypes_hold_us_back_at_work)
[https://www.ted.com/talks/adam_grant_are_you_a_giver_or_a_taker?language=en](https://www.ted.com/talks/adam_grant_are_you_a_giver_or_a_taker?language=en)
[https://www.ted.com/talks/regina_hartley_why_the_best_hire_might_not_have_the_perfect_resume](https://www.ted.com/talks/regina_hartley_why_the_best_hire_might_not_have_the_perfect_resume)
Read the following:
· Chapter 10 in Noe "Social Responsibility"
· Chapter 11 Noe "The Future of Training"
Example of what other students wrote
**1- Find two sources related to AI and Training**
**Source #1**
In their 2021 article, Luo et al. explore how artificial intelligence (AI) can enhance the development of effective training for sales agents. They explain that AI coaching tools can analyze large volumes of sales interactions to identify patterns of successful behaviors and deliver personalized, real-time feedback. This allows employees to develop their skills continuously and at their own pace, making training more dynamic and scalable across large teams. AI supports individualized learning by helping agents improve communication and customer engagement strategies based on data-driven insights. However, the authors also caution against overreliance on AI, noting risks such as dehumanization, deskilling, and privacy concerns. To maximize effectiveness and maintain employee trust, they recommend integrating AI within hybrid coaching models that combine the consistency and scale of AI with the emotional intelligence and mentorship provided by human managers.
Luo, X., Qin, M. S., Fang, Z., & Qu, Z. (2021). Artificial Intelligence Coaches for Sales Agents: Caveats and Solutions. Journal of Marketing, 85(2), 14–32.
[https://doi.org/10.1177/0022242920956676Links to an external site.](https://doi.org/10.1177/0022242920956676)
**Source #2**
In their 2021 article, Ronquillo et al. highlight the role of artificial intelligence (AI) in advancing effective training and professional development in nursing. The authors emphasize that AI has the potential to transform nursing education by supporting personalized learning, enhancing clinical decision-making, and enabling high-quality simulation experiences. AI systems can analyze data on individual learners to tailor educational content, identify skill gaps, and adapt instruction in real time. Additionally, AI-powered simulations allow nurses to engage in realistic, scenario-based training that builds critical thinking and clinical competencies in a safe environment. The article also stresses the importance of involving nurses in the development and implementation of AI tools to ensure they are ethically designed and aligned with the realities of clinical practice. Overall, AI is positioned as a powerful tool to improve the effectiveness, efficiency, and accessibility of training in the nursing profession.
Ronquillo, C. E., Peltonen, L., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., Cato, K., Hardiker, N., Junger, A., Michalowski, M., Nyrup, R., Rahimi, S., Reed, D. N., Salakoski, T., Salanterä, S., Walton, N., Weber, P., Wiegand, T., & Topaz, M. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative.
_Journal of Advanced Nursing_,
_77_(9), 3707–3717.
[https://doi.org/10.1111/jan.14855Links to an external site.](https://doi.org/10.1111/jan.14855)
**2- Social Responsibility, Ethics and Culture**
The intersection of ethics and AI in professional development programs presents both exciting potential and critical responsibility. As organizations adopt AI tools for learning and development, ethical considerations must guide their design and implementation. For example, AI can unintentionally reinforce biases if it draws from unbalanced data, which could hinder rather than support equitable career development. Noe (2023) highlights the importance of ensuring that technology-enhanced training methods are accessible and inclusive, promoting ethical use by prioritizing fairness, privacy, and transparency.
Socially responsible companies can invest in cultivating equitable environments in three key ways. First, they can create personalized development pathways supported by ethical AI that adapts to learners’ goals and learning styles. Second, they should establish long-term mentoring programs that bridge positional gaps across all career stages. Third, companies can form community and educational partnerships that expand access to skill-building opportunities for underserved populations, ensuring the organization’s talent pipeline reflects broader societal equity.
**Reference**
Noe, R. A. (2023). Employee training and development (9th ed.). McGraw Hill.
**1- Find two sources related to AI and Training**
Mohammed, A. H., Othman, Z. J., & Abdullah, A. I. (2024). The Role of Artificial Intelligence in Enhancing Sports Analytics and Training.
_Cihan University-Erbil Scientific Journal (Onine)_,
_8_(1), 58–62.
[https://doi.org/10.24086/cuesj.v8n1y2024.pp58-62Links to an external site.](https://doi.org/10.24086/cuesj.v8n1y2024.pp58-62)
This article by Mohammed, Othman, and Abdullah (2024) investigates how modern technology is changing the way athletes train and how sports are analyzed. It explains how tools like computer vision and data tracking are being used to monitor athletic performance, spot patterns, and create more personalized training routines. Coaches can now make better decisions and even reduce the risk of injuries by catching issues early. The authors also mention a few obstacles, like the excessive cost of these systems and the need for people who understand how to use them. Overall, the article shows how this kind of technology is becoming a valuable part of modern sports.
This article shows how AI helps athletes train smarter, not just harder. By using tools that track how someone moves or performs over time, coaches and trainers can figure out exactly what an athlete needs to work on. Instead of giving everyone the same plan, the training becomes more personal and focused. It also helps catch things like bad form or signs of overtraining before they turn into injuries. This kind of approach makes the whole training process more effective because it is based on real data, not just guesswork or one-size-fits-all routines.
Kaldarova, B., Toktarova, A., & Abdrakhmanov, R. (2024). Enhancing deadlift training through an artificial intelligence-driven personal coaching system using skeletal analysis.
_Retos (Madrid)_,
_60_(60), 439–448.
[https://doi.org/10.47197/retos.v60.109183Links to an external site.](https://doi.org/10.47197/retos.v60.109183)
This article looks at how technology can help people get better at doing deadlifts. The authors talk about a coaching system that uses AI to watch how someone moves while lifting. It focuses on things like posture and technique and gives feedback to help improve form. What is useful is that it can point out small mistakes before they turn into injuries. By using this kind of system, people can train safely and get better results. It is a good example of how tech and fitness can work together to make workouts more effective.
The article also shows how AI can make training more effective by giving people real-time feedback on their form and technique. Instead of waiting for a coach to correct mistakes, the system uses motion tracking to spot issues right away, which helps people fix them before they lead to injuries or unhealthy habits. It also makes training more personalized since the feedback is based on each person’s unique movement patterns. This kind of detailed guidance helps people train more efficiently and safely, which is exactly what effective training should do.
**2- Social Responsibility, Ethics and Culture**
When I think about ethics and AI, especially in the context of socially responsible companies or military organizations, three key actions stand out. First, there must be a commitment to building ethical AI systems that are transparent, accountable, and free from bias—particularly in processes like hiring, performance evaluation, and training assignments. This helps ensure fairness and trust. Second, organizations should use AI to personalize career development, offering tailored learning paths that support individuals at every stage of their careers, from onboarding to leadership roles. This kind of support increases access and opportunity for all employees or service members. Third, investing in strong partnerships with educational institutions, community groups, and veteran-focused programs can broaden access to training, digital literacy, and long-term career growth. In the military, applying these principles strengthens not only the development of the individual but also overall mission readiness, ethical leadership, and trust within the ranks and the communities they serve.
I have always found the concept of AI fascinating for business, especially in today’s digital world where, if applied correctly, it can lead to significant positive results. That said, it’s clear that developing stronger digital skills is essential for workforce readiness and employability. According to Noe, “The current education-to-employment system is not adequately preparing students and adults for the 21st century economy. As the future workplace becomes increasingly digitized, employees will need digital literacy skills” (p 1185).
**Reference**
Noe, R. A. (2023).
_Employee training & development_ (9th ed.). McGraw-Hill Education
**1- Find two sources related to AI and Training**
**Source #1**
In their 2021 article, Luo et al. explore how artificial intelligence (AI) can enhance the development of effective training for sales agents. They explain that AI coaching tools can analyze large volumes of sales interactions to identify patterns of successful behaviors and deliver personalized, real-time feedback. This allows employees to develop their skills continuously and at their own pace, making training more dynamic and scalable across large teams. AI supports individualized learning by helping agents improve communication and customer engagement strategies based on data-driven insights. However, the authors also caution against overreliance on AI, noting risks such as dehumanization, deskilling, and privacy concerns. To maximize effectiveness and maintain employee trust, they recommend integrating AI within hybrid coaching models that combine the consistency and scale of AI with the emotional intelligence and mentorship provided by human managers.
Luo, X., Qin, M. S., Fang, Z., & Qu, Z. (2021). Artificial Intelligence Coaches for Sales Agents: Caveats and Solutions. Journal of Marketing, 85(2), 14–32.
[https://doi.org/10.1177/0022242920956676Links to an external site.](https://doi.org/10.1177/0022242920956676)
**Source #2**
In their 2021 article, Ronquillo et al. highlight the role of artificial intelligence (AI) in advancing effective training and professional development in nursing. The authors emphasize that AI has the potential to transform nursing education by supporting personalized learning, enhancing clinical decision-making, and enabling high-quality simulation experiences. AI systems can analyze data on individual learners to tailor educational content, identify skill gaps, and adapt instruction in real time. Additionally, AI-powered simulations allow nurses to engage in realistic, scenario-based training that builds critical thinking and clinical competencies in a safe environment. The article also stresses the importance of involving nurses in the development and implementation of AI tools to ensure they are ethically designed and aligned with the realities of clinical practice. Overall, AI is positioned as a powerful tool to improve the effectiveness, efficiency, and accessibility of training in the nursing profession.
Ronquillo, C. E., Peltonen, L., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., Cato, K., Hardiker, N., Junger, A., Michalowski, M., Nyrup, R., Rahimi, S., Reed, D. N., Salakoski, T., Salanterä, S., Walton, N., Weber, P., Wiegand, T., & Topaz, M. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative.
_Journal of Advanced Nursing_,
_77_(9), 3707–3717.
[https://doi.org/10.1111/jan.14855Links to an external site.](https://doi.org/10.1111/jan.14855)
**2- Social Responsibility, Ethics and Culture**
The intersection of ethics and AI in professional development programs presents both exciting potential and critical responsibility. As organizations adopt AI tools for learning and development, ethical considerations must guide their design and implementation. For example, AI can unintentionally reinforce biases if it draws from unbalanced data, which could hinder rather than support equitable career development. Noe (2023) highlights the importance of ensuring that technology-enhanced training methods are accessible and inclusive, promoting ethical use by prioritizing fairness, privacy, and transparency.
Socially responsible companies can invest in cultivating equitable environments in three key ways. First, they can create personalized development pathways supported by ethical AI that adapts to learners’ goals and learning styles. Second, they should establish long-term mentoring programs that bridge positional gaps across all career stages. Third, companies can form community and educational partnerships that expand access to skill-building opportunities for underserved populations, ensuring the organization’s talent pipeline reflects broader societal equity.
**Reference**
Noe, R. A. (2023). Employee training and development (9th ed.). McGraw Hill.
**Summarize two sources about how AI can help facilitate the development of effective training.**
Bayly-Castaneda, K., Ramirez-Montoya, M.-S., & Morita-Alexander, A. (2024). Crafting personalized learning paths with AI for lifelong learning: a systematic literature review.
_Frontiers in Education (Lausanne)_,
_9_.
[https://doi.org/10.3389/feduc.2024.1424386Links to an external site.](https://doi.org/10.3389/feduc.2024.1424386)
· This article conducts a systematic literature review on existing research relating to artificial intelligence and lifelong learning. It posits that artificial intelligence has the capability to create personalized strategies for lifelong learning, which is a benefit for different learners. It also addresses the ethical issues created by the research divide globally. Due to the fact that research in some countries is more developed than in others, biases are created within algorithms that have the potential to impact lifelong learning. Overall, this article views artificial intelligence as a tool to enhance lifelong learning.
Chen, Z. (2024). [Rev. of
_Responsible AI in Organizational Training: Applications, Implications, and Recommendations for Future Development_].
_Human Resource Development Review_,
_23_(4), 498–521.
[https://doi.org/10.1177/15344843241273316Links to an external site.](https://doi.org/10.1177/15344843241273316)
· This article examines the potential interaction between artificial intelligence and Human Resource Development practices. It notes that the sensitivity of human data and information in this field creates ethical concerns about the use of AI. However, the article emphasizes that when responsibly governed, artificial intelligence can transform training processes, provided there is alignment with ethical standards, stakeholder needs, and strategic HRD principles. By creating a roadmap on how organizations can integrate AI effectively, ethically, and responsibly, this article forecasts future trends.
**2- Social Responsibility, Ethics and Culture**
After engaging with this week’s learning materials, the rapid development of AI technology creates interesting ethical dilemmas relating to professional development and training. Artificial intelligence has the capability to push the boundaries of what is possible when it comes to education and training. AI models can create customized learning environments that overcome traditional barriers. Due to the autonomous nature of AI recommendations, it is imperative that employees understand the ethical and moral implications of relying on these decisions. As such, the first way companies can support successful L&D with AI would be to articulate standards for use. Landrum (2018) asserts that ethical breaches result from miseducation about company mission and a lack of access to resources. Ensuring that employees have clear expectations about AI use through training and aligning said expectations to organizational missions will support success. Additionally, companies can foster ethical environments by addressing generational gaps that may inhibit AI usage. As Georges (2019) posits in her TedTalk, the current generational divide in the workplace creates age-based stereotypes that can inhibit growth. Using training as an opportunity to “debunk” these stereotypes by creating a space for all to learn equitable strategies for AI usage will benefit socially responsible organizations. Finally, organizations should implement organizational learning to generate feedback loops about AI usage. This technology is so new and rapidly evolving. Continuing to evaluate and strengthen its relationship with training and ensuring that ethical standards are applied is absolutely necessary.
Landrum, S. (2018, August 8).
_Addressing Ethics in Training – Training Industry_. Training Industry.
[https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/Links to an external site.](https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/)
Georges, L. (2019). How generational stereotypes hold us back at work | Leah Georges [YouTube Video]. In
_YouTube_. https://www.youtube.com/watch?v=dKNu5ZnWhb4
Module 6 Discussion
**Two Sources on AI and Training**
**Source 1:** _AI Implementation Impact on Workforce Productivity: The Role of AI Training and Organizational Adaptation_
This study investigated the impact of AI implementation on workforce productivity by focusing on the mediating roles of organizational adaptation and AI Training. The findings indicated that the implementation of AI significantly impacts both AI Training and Organizational Adaptation, which in turn influence workplace productivity. This relationship highlights significant comprehensive strategies that encompass technological adoption, employee training, and organizational flexibility. The recommendation from these findings for the company was to continue to prioritize AI training initiatives to ensure that its employees have the necessary skills to harness AI's potential.
**Nurlia, N., Daud, I., & Rosadi, M. E. (2023). AI Implementation Impact on Workforce Productivity: The Role of AI Training and Organizational Adaptation. Escalate Economics and Business Journal, 1(01), 01-13.** [**https://doi.org/10.61536/escalate.v1i01.6** Links to an external site.](https://doi.org/10.61536/escalate.v1i01.6) ****
**Source 2:** _Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice, and policy_.
This article brings collective insight from collaborators within the industry, academia, and the public sector to highlight the opportunities, challenges, and potential research into the AI technological potential application. One of those potential ideas was using AI-powered platforms to assess performance metrics and provide personalized learning paths through training. This would allow for more strategic and data-informed training that could be widely popular within he organizational sectors. The article finished that the cultural perspective on AI decision marketing and transparency as to how this technology works is key for building support for advancement and technological acceptance.
**Dwivedi, Y. K., et al. (2021).**
**_Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy_. International Journal of Information Management, 57, 101994.** [**https://doi.org/10.1016/j.ijinfomgt.2019.08.002** Links to an external site.](https://doi.org/10.1016/j.ijinfomgt.2019.08.002)
**Social Responsibility, Ethics, and Culture**
As society moves forward with AI use in professional spaces, as with any advancement in technology, the ethical considerations must remain central with that advancement. Changes in automation, such as those in decision-making, learner evaluations, and content delivery, can be unintentionally used in harmful ways. On the backside of AI, we must ensure we are using inclusive data sets to train AT not to replicate biases in its use. At the front of it we need to be creating spaces of equal opportunity to learn that technology to level the playing field for professional development within our organizations.
1.
**Inclusive AI Design** – Not knowing a ton about the backside of AI could be detrimental for a company hoping to use it within their departments and institutions. Having someone working with that technology company to ensure that any AI used in learning and development platforms is developed using diverse data sets and audited regularly for consistency in those areas would be a huge help to those wanting to stay in alignment with their mission, vision, and values.
2.
**Career Development Accessibility** – Using AI to create more accessible and customizable learning experiences for its employees is another key way a company or institution could invest in AI. In chapter 10, we learned about the Americans with Disabilities Act (ADA) and the requirements that go along with it (Noe, 466, 2023). With that being said, this is typically not enough, and gaps are still apparent. There is not always an equitable opportunity; however, AI could change that. Offering reskilling opportunities for older workers, entry-level support, and an adaptable curriculum to accommodate employees with disabilities, this could be a game-changer to continue to push for a more equitable experience.
3.
**Human-AI Collaboration Culture** – The last way companies could use AI in a sociality responsible way is through ethical and robust training on AI usage. AI is not going anywhere, just as the calculator made math harder, allowing us to achieve more, AI will do the same for automatic processing and decision making. Training to teach us to understand, interpret, and audit AI data rather than rely on it blindly will allow us to grow with the technology and push it to its capabilities. This will also ensure we are encouraging human dialogue and feedback that matches the values of the individuals in a way that promotes trust, transparency, and advancement.
In this way, AI becomes a tool not just for efficiency, but for equity and organizational empathy that will move us into the future.
**Reference** Noe, R. A. (2023).
_Employee Training and Development_. McGraw Hill, Cop.
**## Module6DBOGL554.docx**
Module 6: Discussion: AI and Training Development
Welcome OGL 554: Training and Development Crew to our Module 6 Discussion!
As you dive into the content for this week and consider the discussion prompts, please reflect on your experiences with trainings, as well as the materials. Each Module's Discussion Board will provide an opportunity to engage more deeply with something that interests you from the text and learning materials, listen, engage with the perspectives of your peers on these topics and share aspects of the project development process.
We are here to help each other learn, grow and strengthen our insights, evaluative capacities and skills. This is a cooperative process. Generative critiques between peers can prompt us to ask questions about our work and the contributions of fellow colleagues regarding how a specific training could be improved or whether another avenue of address could be engaged to make a substantive difference in the effectiveness of a training. Thank you all for your collegial engagement!
**Step One:** After engaging with the learning materials for this week, please respond to each of the following prompts with an Initial Post.
**1- Find two sources related to AI and Training**
Summarize two sources
about how AI can help facilitate
the development of effective training.
Please provide the bibliographic citation and links.
**2- Social Responsibility, Ethics and Culture**
After engaging the learning materials for this week, please share your reflections on where ethics and AI intersect when t in successful professional development programs. What are three ways that socially responsible companies could invest in cultivating equitable environments, with thriving partnerships, support for career development at all stages, and successful L&D? (Please note: I am not asking about diversity training or "managing diversity"). Requirements: scope at least 200 words and
**must** include
**at least one** references from Module 6, cited and referenced using APA formatting.
**LEARNING MATERIALS AND RESOURCES ARE ATTACHED IN A SEPARATE PAGE**
**## LEARNINGMATERIALSModule6.docx**
LEARNING MATERIALS
[https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/](https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/)
[https://www.ted.com/talks/leah_georges_how_generational_stereotypes_hold_us_back_at_work](https://www.ted.com/talks/leah_georges_how_generational_stereotypes_hold_us_back_at_work)
[https://www.ted.com/talks/adam_grant_are_you_a_giver_or_a_taker?language=en](https://www.ted.com/talks/adam_grant_are_you_a_giver_or_a_taker?language=en)
[https://www.ted.com/talks/regina_hartley_why_the_best_hire_might_not_have_the_perfect_resume](https://www.ted.com/talks/regina_hartley_why_the_best_hire_might_not_have_the_perfect_resume)
Read the following:
· Chapter 10 in Noe "Social Responsibility"
· Chapter 11 Noe "The Future of Training"
Example of what other students wrote
**1- Find two sources related to AI and Training**
**Source #1**
In their 2021 article, Luo et al. explore how artificial intelligence (AI) can enhance the development of effective training for sales agents. They explain that AI coaching tools can analyze large volumes of sales interactions to identify patterns of successful behaviors and deliver personalized, real-time feedback. This allows employees to develop their skills continuously and at their own pace, making training more dynamic and scalable across large teams. AI supports individualized learning by helping agents improve communication and customer engagement strategies based on data-driven insights. However, the authors also caution against overreliance on AI, noting risks such as dehumanization, deskilling, and privacy concerns. To maximize effectiveness and maintain employee trust, they recommend integrating AI within hybrid coaching models that combine the consistency and scale of AI with the emotional intelligence and mentorship provided by human managers.
Luo, X., Qin, M. S., Fang, Z., & Qu, Z. (2021). Artificial Intelligence Coaches for Sales Agents: Caveats and Solutions. Journal of Marketing, 85(2), 14–32.
[https://doi.org/10.1177/0022242920956676Links to an external site.](https://doi.org/10.1177/0022242920956676)
**Source #2**
In their 2021 article, Ronquillo et al. highlight the role of artificial intelligence (AI) in advancing effective training and professional development in nursing. The authors emphasize that AI has the potential to transform nursing education by supporting personalized learning, enhancing clinical decision-making, and enabling high-quality simulation experiences. AI systems can analyze data on individual learners to tailor educational content, identify skill gaps, and adapt instruction in real time. Additionally, AI-powered simulations allow nurses to engage in realistic, scenario-based training that builds critical thinking and clinical competencies in a safe environment. The article also stresses the importance of involving nurses in the development and implementation of AI tools to ensure they are ethically designed and aligned with the realities of clinical practice. Overall, AI is positioned as a powerful tool to improve the effectiveness, efficiency, and accessibility of training in the nursing profession.
Ronquillo, C. E., Peltonen, L., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., Cato, K., Hardiker, N., Junger, A., Michalowski, M., Nyrup, R., Rahimi, S., Reed, D. N., Salakoski, T., Salanterä, S., Walton, N., Weber, P., Wiegand, T., & Topaz, M. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative.
_Journal of Advanced Nursing_,
_77_(9), 3707–3717.
[https://doi.org/10.1111/jan.14855Links to an external site.](https://doi.org/10.1111/jan.14855)
**2- Social Responsibility, Ethics and Culture**
The intersection of ethics and AI in professional development programs presents both exciting potential and critical responsibility. As organizations adopt AI tools for learning and development, ethical considerations must guide their design and implementation. For example, AI can unintentionally reinforce biases if it draws from unbalanced data, which could hinder rather than support equitable career development. Noe (2023) highlights the importance of ensuring that technology-enhanced training methods are accessible and inclusive, promoting ethical use by prioritizing fairness, privacy, and transparency.
Socially responsible companies can invest in cultivating equitable environments in three key ways. First, they can create personalized development pathways supported by ethical AI that adapts to learners’ goals and learning styles. Second, they should establish long-term mentoring programs that bridge positional gaps across all career stages. Third, companies can form community and educational partnerships that expand access to skill-building opportunities for underserved populations, ensuring the organization’s talent pipeline reflects broader societal equity.
**Reference**
Noe, R. A. (2023). Employee training and development (9th ed.). McGraw Hill.
**1- Find two sources related to AI and Training**
Mohammed, A. H., Othman, Z. J., & Abdullah, A. I. (2024). The Role of Artificial Intelligence in Enhancing Sports Analytics and Training.
_Cihan University-Erbil Scientific Journal (Onine)_,
_8_(1), 58–62.
[https://doi.org/10.24086/cuesj.v8n1y2024.pp58-62Links to an external site.](https://doi.org/10.24086/cuesj.v8n1y2024.pp58-62)
This article by Mohammed, Othman, and Abdullah (2024) investigates how modern technology is changing the way athletes train and how sports are analyzed. It explains how tools like computer vision and data tracking are being used to monitor athletic performance, spot patterns, and create more personalized training routines. Coaches can now make better decisions and even reduce the risk of injuries by catching issues early. The authors also mention a few obstacles, like the excessive cost of these systems and the need for people who understand how to use them. Overall, the article shows how this kind of technology is becoming a valuable part of modern sports.
This article shows how AI helps athletes train smarter, not just harder. By using tools that track how someone moves or performs over time, coaches and trainers can figure out exactly what an athlete needs to work on. Instead of giving everyone the same plan, the training becomes more personal and focused. It also helps catch things like bad form or signs of overtraining before they turn into injuries. This kind of approach makes the whole training process more effective because it is based on real data, not just guesswork or one-size-fits-all routines.
Kaldarova, B., Toktarova, A., & Abdrakhmanov, R. (2024). Enhancing deadlift training through an artificial intelligence-driven personal coaching system using skeletal analysis.
_Retos (Madrid)_,
_60_(60), 439–448.
[https://doi.org/10.47197/retos.v60.109183Links to an external site.](https://doi.org/10.47197/retos.v60.109183)
This article looks at how technology can help people get better at doing deadlifts. The authors talk about a coaching system that uses AI to watch how someone moves while lifting. It focuses on things like posture and technique and gives feedback to help improve form. What is useful is that it can point out small mistakes before they turn into injuries. By using this kind of system, people can train safely and get better results. It is a good example of how tech and fitness can work together to make workouts more effective.
The article also shows how AI can make training more effective by giving people real-time feedback on their form and technique. Instead of waiting for a coach to correct mistakes, the system uses motion tracking to spot issues right away, which helps people fix them before they lead to injuries or unhealthy habits. It also makes training more personalized since the feedback is based on each person’s unique movement patterns. This kind of detailed guidance helps people train more efficiently and safely, which is exactly what effective training should do.
**2- Social Responsibility, Ethics and Culture**
When I think about ethics and AI, especially in the context of socially responsible companies or military organizations, three key actions stand out. First, there must be a commitment to building ethical AI systems that are transparent, accountable, and free from bias—particularly in processes like hiring, performance evaluation, and training assignments. This helps ensure fairness and trust. Second, organizations should use AI to personalize career development, offering tailored learning paths that support individuals at every stage of their careers, from onboarding to leadership roles. This kind of support increases access and opportunity for all employees or service members. Third, investing in strong partnerships with educational institutions, community groups, and veteran-focused programs can broaden access to training, digital literacy, and long-term career growth. In the military, applying these principles strengthens not only the development of the individual but also overall mission readiness, ethical leadership, and trust within the ranks and the communities they serve.
I have always found the concept of AI fascinating for business, especially in today’s digital world where, if applied correctly, it can lead to significant positive results. That said, it’s clear that developing stronger digital skills is essential for workforce readiness and employability. According to Noe, “The current education-to-employment system is not adequately preparing students and adults for the 21st century economy. As the future workplace becomes increasingly digitized, employees will need digital literacy skills” (p 1185).
**Reference**
Noe, R. A. (2023).
_Employee training & development_ (9th ed.). McGraw-Hill Education
**1- Find two sources related to AI and Training**
**Source #1**
In their 2021 article, Luo et al. explore how artificial intelligence (AI) can enhance the development of effective training for sales agents. They explain that AI coaching tools can analyze large volumes of sales interactions to identify patterns of successful behaviors and deliver personalized, real-time feedback. This allows employees to develop their skills continuously and at their own pace, making training more dynamic and scalable across large teams. AI supports individualized learning by helping agents improve communication and customer engagement strategies based on data-driven insights. However, the authors also caution against overreliance on AI, noting risks such as dehumanization, deskilling, and privacy concerns. To maximize effectiveness and maintain employee trust, they recommend integrating AI within hybrid coaching models that combine the consistency and scale of AI with the emotional intelligence and mentorship provided by human managers.
Luo, X., Qin, M. S., Fang, Z., & Qu, Z. (2021). Artificial Intelligence Coaches for Sales Agents: Caveats and Solutions. Journal of Marketing, 85(2), 14–32.
[https://doi.org/10.1177/0022242920956676Links to an external site.](https://doi.org/10.1177/0022242920956676)
**Source #2**
In their 2021 article, Ronquillo et al. highlight the role of artificial intelligence (AI) in advancing effective training and professional development in nursing. The authors emphasize that AI has the potential to transform nursing education by supporting personalized learning, enhancing clinical decision-making, and enabling high-quality simulation experiences. AI systems can analyze data on individual learners to tailor educational content, identify skill gaps, and adapt instruction in real time. Additionally, AI-powered simulations allow nurses to engage in realistic, scenario-based training that builds critical thinking and clinical competencies in a safe environment. The article also stresses the importance of involving nurses in the development and implementation of AI tools to ensure they are ethically designed and aligned with the realities of clinical practice. Overall, AI is positioned as a powerful tool to improve the effectiveness, efficiency, and accessibility of training in the nursing profession.
Ronquillo, C. E., Peltonen, L., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., Cato, K., Hardiker, N., Junger, A., Michalowski, M., Nyrup, R., Rahimi, S., Reed, D. N., Salakoski, T., Salanterä, S., Walton, N., Weber, P., Wiegand, T., & Topaz, M. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative.
_Journal of Advanced Nursing_,
_77_(9), 3707–3717.
[https://doi.org/10.1111/jan.14855Links to an external site.](https://doi.org/10.1111/jan.14855)
**2- Social Responsibility, Ethics and Culture**
The intersection of ethics and AI in professional development programs presents both exciting potential and critical responsibility. As organizations adopt AI tools for learning and development, ethical considerations must guide their design and implementation. For example, AI can unintentionally reinforce biases if it draws from unbalanced data, which could hinder rather than support equitable career development. Noe (2023) highlights the importance of ensuring that technology-enhanced training methods are accessible and inclusive, promoting ethical use by prioritizing fairness, privacy, and transparency.
Socially responsible companies can invest in cultivating equitable environments in three key ways. First, they can create personalized development pathways supported by ethical AI that adapts to learners’ goals and learning styles. Second, they should establish long-term mentoring programs that bridge positional gaps across all career stages. Third, companies can form community and educational partnerships that expand access to skill-building opportunities for underserved populations, ensuring the organization’s talent pipeline reflects broader societal equity.
**Reference**
Noe, R. A. (2023). Employee training and development (9th ed.). McGraw Hill.
**Summarize two sources about how AI can help facilitate the development of effective training.**
Bayly-Castaneda, K., Ramirez-Montoya, M.-S., & Morita-Alexander, A. (2024). Crafting personalized learning paths with AI for lifelong learning: a systematic literature review.
_Frontiers in Education (Lausanne)_,
_9_.
[https://doi.org/10.3389/feduc.2024.1424386Links to an external site.](https://doi.org/10.3389/feduc.2024.1424386)
· This article conducts a systematic literature review on existing research relating to artificial intelligence and lifelong learning. It posits that artificial intelligence has the capability to create personalized strategies for lifelong learning, which is a benefit for different learners. It also addresses the ethical issues created by the research divide globally. Due to the fact that research in some countries is more developed than in others, biases are created within algorithms that have the potential to impact lifelong learning. Overall, this article views artificial intelligence as a tool to enhance lifelong learning.
Chen, Z. (2024). [Rev. of
_Responsible AI in Organizational Training: Applications, Implications, and Recommendations for Future Development_].
_Human Resource Development Review_,
_23_(4), 498–521.
[https://doi.org/10.1177/15344843241273316Links to an external site.](https://doi.org/10.1177/15344843241273316)
· This article examines the potential interaction between artificial intelligence and Human Resource Development practices. It notes that the sensitivity of human data and information in this field creates ethical concerns about the use of AI. However, the article emphasizes that when responsibly governed, artificial intelligence can transform training processes, provided there is alignment with ethical standards, stakeholder needs, and strategic HRD principles. By creating a roadmap on how organizations can integrate AI effectively, ethically, and responsibly, this article forecasts future trends.
**2- Social Responsibility, Ethics and Culture**
After engaging with this week’s learning materials, the rapid development of AI technology creates interesting ethical dilemmas relating to professional development and training. Artificial intelligence has the capability to push the boundaries of what is possible when it comes to education and training. AI models can create customized learning environments that overcome traditional barriers. Due to the autonomous nature of AI recommendations, it is imperative that employees understand the ethical and moral implications of relying on these decisions. As such, the first way companies can support successful L&D with AI would be to articulate standards for use. Landrum (2018) asserts that ethical breaches result from miseducation about company mission and a lack of access to resources. Ensuring that employees have clear expectations about AI use through training and aligning said expectations to organizational missions will support success. Additionally, companies can foster ethical environments by addressing generational gaps that may inhibit AI usage. As Georges (2019) posits in her TedTalk, the current generational divide in the workplace creates age-based stereotypes that can inhibit growth. Using training as an opportunity to “debunk” these stereotypes by creating a space for all to learn equitable strategies for AI usage will benefit socially responsible organizations. Finally, organizations should implement organizational learning to generate feedback loops about AI usage. This technology is so new and rapidly evolving. Continuing to evaluate and strengthen its relationship with training and ensuring that ethical standards are applied is absolutely necessary.
Landrum, S. (2018, August 8).
_Addressing Ethics in Training – Training Industry_. Training Industry.
[https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/Links to an external site.](https://trainingindustry.com/articles/compliance/addressing-ethics-in-training/)
Georges, L. (2019). How generational stereotypes hold us back at work | Leah Georges [YouTube Video]. In
_YouTube_. https://www.youtube.com/watch?v=dKNu5ZnWhb4
Module 6 Discussion
**Two Sources on AI and Training**
**Source 1:** _AI Implementation Impact on Workforce Productivity: The Role of AI Training and Organizational Adaptation_
This study investigated the impact of AI implementation on workforce productivity by focusing on the mediating roles of organizational adaptation and AI Training. The findings indicated that the implementation of AI significantly impacts both AI Training and Organizational Adaptation, which in turn influence workplace productivity. This relationship highlights significant comprehensive strategies that encompass technological adoption, employee training, and organizational flexibility. The recommendation from these findings for the company was to continue to prioritize AI training initiatives to ensure that its employees have the necessary skills to harness AI's potential.
**Nurlia, N., Daud, I., & Rosadi, M. E. (2023). AI Implementation Impact on Workforce Productivity: The Role of AI Training and Organizational Adaptation. Escalate Economics and Business Journal, 1(01), 01-13.** [**https://doi.org/10.61536/escalate.v1i01.6** Links to an external site.](https://doi.org/10.61536/escalate.v1i01.6) ****
**Source 2:** _Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice, and policy_.
This article brings collective insight from collaborators within the industry, academia, and the public sector to highlight the opportunities, challenges, and potential research into the AI technological potential application. One of those potential ideas was using AI-powered platforms to assess performance metrics and provide personalized learning paths through training. This would allow for more strategic and data-informed training that could be widely popular within he organizational sectors. The article finished that the cultural perspective on AI decision marketing and transparency as to how this technology works is key for building support for advancement and technological acceptance.
**Dwivedi, Y. K., et al. (2021).**
**_Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy_. International Journal of Information Management, 57, 101994.** [**https://doi.org/10.1016/j.ijinfomgt.2019.08.002** Links to an external site.](https://doi.org/10.1016/j.ijinfomgt.2019.08.002)
**Social Responsibility, Ethics, and Culture**
As society moves forward with AI use in professional spaces, as with any advancement in technology, the ethical considerations must remain central with that advancement. Changes in automation, such as those in decision-making, learner evaluations, and content delivery, can be unintentionally used in harmful ways. On the backside of AI, we must ensure we are using inclusive data sets to train AT not to replicate biases in its use. At the front of it we need to be creating spaces of equal opportunity to learn that technology to level the playing field for professional development within our organizations.
1.
**Inclusive AI Design** – Not knowing a ton about the backside of AI could be detrimental for a company hoping to use it within their departments and institutions. Having someone working with that technology company to ensure that any AI used in learning and development platforms is developed using diverse data sets and audited regularly for consistency in those areas would be a huge help to those wanting to stay in alignment with their mission, vision, and values.
2.
**Career Development Accessibility** – Using AI to create more accessible and customizable learning experiences for its employees is another key way a company or institution could invest in AI. In chapter 10, we learned about the Americans with Disabilities Act (ADA) and the requirements that go along with it (Noe, 466, 2023). With that being said, this is typically not enough, and gaps are still apparent. There is not always an equitable opportunity; however, AI could change that. Offering reskilling opportunities for older workers, entry-level support, and an adaptable curriculum to accommodate employees with disabilities, this could be a game-changer to continue to push for a more equitable experience.
3.
**Human-AI Collaboration Culture** – The last way companies could use AI in a sociality responsible way is through ethical and robust training on AI usage. AI is not going anywhere, just as the calculator made math harder, allowing us to achieve more, AI will do the same for automatic processing and decision making. Training to teach us to understand, interpret, and audit AI data rather than rely on it blindly will allow us to grow with the technology and push it to its capabilities. This will also ensure we are encouraging human dialogue and feedback that matches the values of the individuals in a way that promotes trust, transparency, and advancement.
In this way, AI becomes a tool not just for efficiency, but for equity and organizational empathy that will move us into the future.
**Reference** Noe, R. A. (2023).
_Employee Training and Development_. McGraw Hill, Cop.
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