Why isn’t training closing the AI ROI gap?
Companies have poured money into artificial intelligence, but many leaders still can’t point to a clear return on that investment. A new survey of learning and development professionals suggests the problem isn’t simply a training gap. It’s that organizations haven’t agreed on what success looks like.
The annual AI in Learning & Development Report surveyed more than 800 workplace learning professionals across more than 25 countries. Their answers reveal a familiar pattern. AI is making training content faster to produce, but far fewer teams can show that it changes how people perform at work.
Speed is the win teams can see
Three-quarters of respondents, 75%, named faster content creation as one of the clearest impacts of AI adoption. That means shorter production times for new training and more of it coming out the door. Only 11% pointed to improved on-the-job performance.
That gap matters because most workplace training exists to improve performance. Yet only 35% of L&D teams consistently measure on-the-job performance, compared with 72% who consistently track participation and completions. The report says this suggests that leaders are either not rewarding L&D against performance metrics, or that no one has agreed on what success should be. The survey responses point to the second explanation. More than one in five respondents named a lack of agreed-upon success metrics as their biggest barrier to proving impact.
Permission and data gaps slow teams down
A leadership mandate to use AI doesn’t automatically open the door to new tools. Of L&D teams that started from a mandate, 73% still need departmental or cross-functional permission to pilot a new AI tool. Some are limited to company-approved tools and can’t test anything beyond them.
What do L&D teams need to prove AI’s impact?
Data is another bottleneck. A majority of L&D teams are confident that AI is leading to improvements, yet they struggle to produce evidence of those gains. When asked about the biggest barrier to proving impact, 53% pointed to an organizational constraint, including missing success metrics and limited access to data or measurement tools. In practice, the data needed to measure impact can sit in disconnected systems, such as a learning management system, an HR information system, a survey tool and an AI video platform.
Without that evidence, teams risk becoming what the report calls a content factory. If they use AI to churn out training faster but never check whether it changes behavior, more content is all they have to show for the investment.
There is some encouragement in the data. About a third of L&D teams report performance gains from AI, such as faster time to proficiency or better on-the-job performance. Those teams tend to share certain traits, including the freedom to pilot or build AI solutions and the use of AI to evaluate their own work. Many of those factors, the report notes, depend on decisions outside L&D’s control.
Three structural fixes
What should organizations do to close the AI ROI gap?
Based on its findings, the report recommends three changes. First, leaders should agree on what AI is supposed to accomplish, then decide how its use will be rewarded and measured. For L&D, that means settling on the performance changes the business wants before designing any new training, including training on AI itself.
Second, organizations should invest in data integration before scaling new AI solutions or automating more workflows. Teams across functions need access to the data required to measure AI’s impact.
Third, leaders should bring L&D into the AI strategy conversation. If the goal of AI is to automate manual work, the time it frees up should go toward building more strategic skills, such as how to use AI to change how work gets done. L&D is well positioned to lead that effort, the report says, because it can identify where training can be part of the solution and where it can’t.
Training can help close the gap between AI adoption and return on investment, the report concludes, but only once those conditions are in place.
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