How To Incorporate Artificial Intelligence Into Learning And Development Strategy?

By Mostafa Sayyadi

Only identifying problems for senior managers is not enough today. They need to be able to develop and implement an AI-powered learning and development strategy. Artificial Intelligence (AI) has placed senior managers in what is known as a dual role. In this article, I examine the challenges of the development and implementation of an AI-powered learning and development strategy and provide an alternative way for companies to re-emerge with sustenance.


As organizations enter the new age of artificial intelligence there are a plethora of unique opportunities. One opportunity is to create an AI-powered learning and development strategy. Developing a technological infrastructure is one important component but there is another that will likely make or break the traditional organization. Success in the era of artificial intelligence does not only require money and investment in technology infrastructure, but it also requires a change in the way leaders think about their learning and development strategy. In this article, I call this new approach the AI-powered learning and development strategy and provide corporate leaders with the best practices for the development and implementation of this effective strategy.

The best practices for the development and implementation of an AI-powered learning and development strategy depend on how senior managers can create a rapid technology change program. There needs to be a strong emphasis on maximizing the performance of the artificial intelligence development and implementing a human resources development project to begin developing and implementing a new form of learning and development strategy, what I call an AI-powered learning and development strategy.

AI-Powered Learning and Development Strategy 

With the introduction of AI to a company, the learning and development strategy will change, and a new learning and development strategy cultivation and implementation process will be redefined based on data analysis and digital applications. [1] [2] [3] [4] The first step is to assess human and technological infrastructure capabilities for AI, avoiding pitfalls in data analysis and further elaboration. Secondly, implementing an effective knowledge management system is one of the most significant technological and human infrastructures companies need before developing AI. [5] [6] Insights related to data analysis are usually available at operational levels, but the lack of an effective knowledge management system causes these insights to not pass through the bottlenecks of communication channels and are not available to upper levels. Here, developing chatbots and using other AI tools can lead to developing a data-oriented approach in companies and eventually strengthen the data analysis side in AI-powered learning and development strategy.

Another critical pillar of AI-powered learning and development strategy is the digital core knowledge, which refers to the software on which algorithms derived from data analysis are applied. [7] [8] This step creates a more scientific baseline for decision-making, and algorithms for hybrid automated processes are presented. It is advisable to avoid software and technology choices that can act on the current CEO’s perception and research of rapid transformations and adoptions. The accelerated decision about technologies could create errors in the data to be utilized in learning and development strategy and delays in effective AI implementation. AI requires processes redesigned to get advantages of automation along critical processes using chatbots. [9] [10] This part of AI implementation is the opportunity to make the participation of internal resources effective, especially those at the bottom line, to work on RPA coding and algorithmics. This can happen if a hybrid change process is allowed, which, under an effective and active sponsorship from the top, can remove the fear of technology from internal resources. The CEO’s role is to communicate technology’s scope and benefits with employees. As said earlier, a bottom-up approach with employees’ participation and decision-making power can lead to minor resistance and create a culture that, in addition to considering experimentation, can better align people and technology, leading to the successful implementation of a learning and development strategy.

Unlearning and Learning

The unlearning and training activities are a great way to learn through experience, and we experienced that “action learning” is the best way. Removing or, better, identifying what is not working anymore, with an effective reality check, allows new learning with experimentation.

Action Learning “learning by doing” involves actively engaging with real-world challenges and reflecting upon them to gain new knowledge and insights. [11] [12] When combined, people can effectively draw from experience to address complex problems and reflect if they are applicable. [13] [14] [15] They benefit from supportive peers who offer new perspectives to explore emerging issues through novel inquiries and probes. 

I present a view of the approaches with and without AI and Chatbots:

AI and Chatbots:

AI-powered Decision Support System (DSS) effectively supports unlearning outside real-life decision-making scenarios. We can design specifically to learn how to provide a safe space for employees to unlearn old habits and learn new ones. 

Unlearning Process (With AI and Chatbots). The same approach is used with DSS, only different in the use of technology.

Without AI and Chatbots:

Scenario Planning and Future-back Thinking. It involves envisioning possible futures and working backwards to let trainees use their skills to identify the skills, knowledge, and behaviors needed in those scenarios. 

Negative Learning. It is a powerful tool to challenge pre-existing beliefs and assumptions, facilitating unlearning and opening the door to new learning. This is particularly effective in extreme cases where existing behaviors or mindsets may harm existing or future leaders, particularly in negative situations.

In Conclusion

AI will transform and enhance decision-making and organizational processes. These transformations will bring extensive benefits to companies. Companies that use this AI have a higher competitive advantage when compared to companies that only focus on one of the two aspects of machines and humans. The change in the approach of CEOs as well as structural and cultural changes will become a basis for developing an effective implementation learning and development strategy to better respond to new learning needs. This AI-powered learning and development strategy, relying on data analysis and AI and digital technology, has a high potential to respond effectively to the emerging learning needs of today’s evolving business environment.

About the Author

Mostafa SayydiMostafa Sayyadi works with senior business leaders to effectively develop innovation in companies and helps companies—from start-ups to the Fortune 100—succeed by improving the effectiveness of their leaders. 


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