Embracing AI in L&D
This blog is part three of a three-part series based on a talk titled "Unleash the Power of L&D: Align, Adapt & AI Your Way to Success," delivered at the NZ HR Leadership Summit in November 2024. The session explored three strategies to unlock the potential of Learning and Development (L&D): Alignment, Adaptability, and AI. Each post in this series dives deeper into one of these strategies, offering practical insights to elevate your L&D initiatives.
In their most recent report, Donald H. Taylor and Engle Vinauskaite state:
“AI presents L&D with a once-in-a-lifetime opportunity to have the impact and reach that it has always wanted.”
Donald H. Taylor and Egle Vinauskaite, “AI in L&D: Intention and reality”. October 2024
How do we make the most of this opportunity? In this final post in the series, we’ll explore ways L&D can use AI well, to increase impact.
Of course many people still have concerns about AI, so let’s mention these first. It is these types of concerns that may need to be included in any policy your team or business decides to write, to guide safe AI usage.
Addressing Common Concerns
Here are some of the most common concerns I hear, along with practical insights to address them:
Privacy concerns: It is always important to consider privacy. The good news is that many tools, such as paid versions of ChatGPT or Microsoft Co-Pilot, do not use your data to train their models. This makes them safer for business use, especially when handling sensitive information. Before you use any tool, make sure you know what the privacy status is.
AI can be used for harm: It’s true that AI has been misused, but increasingly, safeguards are in place to prevent this. For example, tools like those found in Adobe’s Creative Cloud suite won’t respond to prompts that involve unethical or harmful requests. Also, one has to trust that one’s team member are going to use these tools for productive efforts, rather than for harm.
Bias, sensitivity, and social equity: Bias is inherent in any AI trained on large data sets. As L&D practitioners, we need to carefully review AI outputs to ensure they are ethical, fair, and aligned with organisational values. I always remind our team that we are the creators of the content, it’s up to us to tell the tool what exactly we’re looking for, and not accept any outputs that contain bias or encourage insensitivity.
Poor quality of outputs: AI-generated content can sometimes be low quality, especially if the task is complex or the input is vague. The trick is to break tasks into smaller parts, use clear prompts, and refine the results with human oversight.
Environmental impact: AI requires significant computational resources. According to the International Energy Agency, by 2026, data centres could consume as much energy as entire countries like Sweden or Germany. (Time magazine, June 12, 2024).
While we may not have direct solutions to this challenge yet, they are tied to clean energy solutions, and we should include software use of all kinds in with the calculations of our own and our business’ carbon footprints. The most productive conversations I’ve read online are about mitigating our impact by using AI judiciously—for high-value tasks rather than trivial ones. This is akin to reducing car usage for short trips: a small but meaningful step.
How can we use AI?
In their report, Taolr and Vinauskaite suggest that L&D departments worldwide are using AI in three main ways:
For internal efficiency (helping L&D departments complete their work)
For point solutions (in learning experiences)
Business Integration (connecting the work of the organisation)
I’ve gone into a bit more detail, and I’ve looked at the ADDIE phases of any L&D project, and have listed the ways that AI can assist at each phase. Many of these ways are for internal efficiencies, some of them are for point solutions, and a few include business integration ideas.
Download this list using the button at the bottle of this article.
Some specific Examples
As well as these ideas, we’ve developed some specific examples of point solutions for you to see, if you’re not yet familiar with what they may look like.
Here’s an example of an eLearning module that allows learners to translate either the whole course, or a section of language into a language they are more familiar with:
Video#1
Here’s an example of an eLearning module in which the learner can type in a free-text answer, and get some feedback by an AI that is trained to respond based on specific criteria.
Video #2
Artificial intelligence offers L&D practitioners the chance to work smarter, not harder, by automating repetitive tasks and uncovering insights that would otherwise take hours to achieve. With that said, it’s important to remember something that we say often at Pukeko Learning Solutions.
“A fool with a tool is still a fool.”
AI is not a solution in itself but a tool that, when integrated thoughtfully and strategically into processes like the ADDIE framework, can elevate both efficiency and outcomes.
Free resource downloads
To receive copies of the documents in this series of posts, as well as links to experiment with the Point solutions shown above, Click the button below.
