If learning and development (L&D) had a top phrase of the year for 2023, artificial intelligence (AI) would be a logical candidate. Looking at the sheer volume of articles on application, opinions and prognostications, it’s a safe bet that AI will continue to make waves in the L&D space this year.

And it’s not just L&D that’s curious about the subject. In a nine-month period spanning June 2022 to March 2023, monthly organic searches for the term artificial intelligence tripled from 7.9M searches to over 30M during the last month of the measured period. And you can bet that curve continued to rise through the remainder of the year.

That being said, AI is a candidate for being one of the worst-named innovations — in part because it is not a single tool as much as it an expanding set of applications. Also, the term “artificial” has connotations that drive apprehension and misunderstanding.

Let’s talk about this for a bit. It’s no secret that AI is ubiquitous and ever-present in our daily lives. Checking the weather? AI. Planning a route to get from here to there? AI. Looking for a gift suggestion? AI. And so on. And yet very few of us have concerns that AI is nefariously plotting to ruin our plans, our commutes and our relationships by engaging with it in this manner. But put it into play in our information and learning systems?

How much easier would it be to talk about AI if it were defined as “accelerated intelligence” or “applied intelligence”? Language matters. Words and labels matter. To paraphrase Raymond Chandler, we need to be very clear in what we talk about when we talk about AI. This is an important area of focus in 2024, not only as pertains to our projects, our constituents and our stakeholders, but also to our credibility as L&D leaders.

For decades, L&D leaders have worked hard to attain and maintain our seat at the organizational leadership and decision-making table. We got here, and remain here, in part, through clearly linking the work that we perform and manage to the objectives of the business. Specifically, empirically connecting L&D efforts to measurable outcomes as a part of the business, not apart from it.

With this in mind, let’s consider some AI New Year’s resolutions to put your organization on the right track in 2024:

Be clear in both definition/aspect and use case: We’re too far down the integration path with too many good examples to continue to formulate generic use cases. This is not to say we shouldn’t experiment — we absolutely need to — but we need to be explicit in what aspects of AI we are using and what we are seeking to achieve.

For example, VPS recently competed in a national challenge sponsored by the U.S. Navy to utilize AI to improve their P-ADDIE-M process.

The challenge was worded as “Using artificial intelligence (AI) large language models (LLMs), automate the process of conducting instructional systems development analysis and requirements development. Specifically, develop quality task analysis, learning analysis, and media selection data in reduced time and at reduced cost.” And even within these constraints, and an added level of evaluation criteria, there were over a dozen different approaches received and considered.

Be intentional in how and when AI is used: There are few things that hamper our ability to integrate innovations and advancements in learning technology more than applying them to the wrong use cases. Or more specifically, applying it in areas where more efficient and equally effective solutions are available.

Using the Navy challenge again as an example, we quickly realized that, at least at the current state of maturity of the tools and systems available for LLMs, we achieved better outcomes (as defined above) by using AI to solve very specific elements of the problem. We continued to use the process, algorithms and robotic process automation we had previously built into the solution as the basis for the solution to which we integrated LLMs. And equally important, we utilized a “humans-in-the-loop” approach, where subjective and expert analysis was beneficial to the outcomes.

Or, more succinctly, just because you got a new hammer doesn’t mean everything should be considered a nail.

Don’t wait! Pick a topic in Q1 and give it a spin: AI is here. L&D is experimenting and implementing, and it is already having an impact. Particularly in complex processes and resource-constrained departments. Identify a specific use case with a clear set of objectives, know your constraints, identify the resources needed (both internally and externally) and then get on with it.

The resource element here is not a trivial point. Just as very few of us would try to build our own virtual reality (VR) headsets or learning management systems (LMSs), we’d do well to consult with folks who already have a few cycles under their belts to better inform our efforts.