The learning and development (L&D) landscape is evolving faster than ever, thanks to the proliferation of artificial intelligence (AI) and the tools available to us in the L&D profession. AI is now a permanent part of L&D. The unfortunate truth stated in a recent article is that 60% of L&D employees believe that AI would make them more productive, and 26% lied or exaggerated their knowledge of AI to keep up with superiors or colleagues. Not utilizing AI because of fear or lack of training and education is like having a superpower and not using it.
Before you become a master of AI within your organization, you must realize a few key concepts.
- AI does not change how people learn.
- The rapid AI revolution has created many questions and misconceptions about AI and its role within L&D. Spoiler alert: AI is not always correct.
- AI abilities change and adapt at an incredible rate. Just like people learn, AI learns and adapts. Your ability to change and adjust is now more critical than ever.
If you are ready to grow your superpowers, then keep reading. Here are the basic steps to develop your AI superpowers:
- Educate yourself and your team on the different types of AI and what they do.
- Select and connect the AI tool to solve a specific business problem.
- Measure its effectiveness with a business metric that the organization cares about.
- Train, pilot and iterate.
- Watch for hallucinations and other bugs.
Essential skill No. 1: Educate yourself and your team.
AI offers many applications within L&D, from designing training curricula and creating personalized learning experiences to assessing program effectiveness and assisting in needs analysis. An all-around understanding of AI, its various forms, and their use cases in L&D can significantly increase your L&D superpowers. Keep in mind that AI tools have specific purposes. There is no one-size-fits-all approach. For instance, if you seek human type interaction, rely on tools like the generative pretrained transformer (GPT) or natural language processing (NLP). Machine learning algorithms are the way to go if you need to classify data effectively or make predictions, as in a needs analysis or program assessment. Knowledge is a superpower — especially when it comes to harnessing the power of AI in L&D.
Essential skill No. 2: Select and connect the AI tool to a specific business need or problem.
Selecting the appropriate AI tool for the task at hand and aligning it with a specific business need or problem is essential because focusing on the need helps us focus our efforts and make measurable progress that others in the organization care about. Gain a thorough understanding of your business problem and then use the first essential skill to guide your selection of the right AI tool.
Essential skill No. 3: Measure its effectiveness with a metric that matters.
It’s not enough to deploy AI-driven tools. You must measure their impact. This means we have to go beyond the typical learning-type metrics. We have to connect with business metrics that the organization cares about. Whether through advanced analytics that tracks learning patterns or AI that predicts future training needs based on past performance, the metrics chosen should directly correlate with the organization’s learning objectives and overall business goals.
By focusing on metrics that reflect meaningful improvements in performance and productivity, you can demonstrate the true value of AI within your training programs and justify continued investment in these advanced learning technologies.
Essential skill No. 4: Train, pilot and iterate.
Embrace training, piloting and Iterating. A successful pilot is a critical first step. The initial pilot focuses on gathering data (training) and implementing the tool. Some tools require more data and training than others. It generally depends on the use case. Conduct the initial pilot in a controlled setting. This initial phase is crucial for identifying potential issues, gauging user receptivity, and determining the AI’s impact on business and learning outcomes.
After the initial pilot, the focus shifts to iteration. This is where you refine and enhance based on feedback and AI findings. The tool should make adjustments as well. The agile iterations help fine-tune the AI applications and ensure they meet the business needs. These adjustments could involve tweaking the AI algorithms, altering the user interface for better accessibility or modifying the content for greater relevance.
Essential skill No. 5: Watch out for hallucinations and other bugs.
As you implement your AI tool(s), be on the lookout for “hallucinations” and other bugs. AI can make stuff up or be wrong, and its content is your responsibility. Similar to how kryptonite weakens superman, these issues can significantly undermine the effectiveness of GPTs, NLPs and ML algorithms. It is important to have a quality process to guard against these false outcomes. Implementing a rigorous Q/A process ensures that the AI’s outputs remain reliable and accurate and maintain the integrity and value of your AI-driven initiatives.
