Most Organizations Train for Today’s AI, Not Tomorrow’s Jobs
As AI reshapes the nature of work, most companies are still focused on helping employees grow in their current roles rather than preparing them for the jobs that are coming next. That’s the central finding of new research from The Conference Board, which warns that while investment in AI literacy is rising, few organizations are laying the groundwork for the large-scale reskilling that AI-driven transformation will demand.
The disconnect is already visible in the numbers. Drawing on interviews with 35 enterprise leaders and a global survey of nearly 1,300 workers, the report shows that formal training is failing to keep pace with adoption: 55% of workers use AI regularly, but only 33% have received employer-provided AI training in the past six months. Nearly one-third say their employer offers no AI training at all.
“Many organizations have made progress introducing employees to AI, but AI literacy alone will not create business value.”
— Matt Rosenbaum, Principal Researcher, Human Capital, The Conference BoardAdoption Is Outrunning Training
Where training does exist, it tends to stop at the basics. Many organizations emphasize AI literacy and simple prompting, while far fewer help workers build advanced capabilities such as managing AI agents, integrating AI into workflows, or applying it to strategic business challenges. The result is a widening gap between what the technology can do and what employees are actually prepared to do with it.
Access is only part of the problem. Roughly half of workers say they have enough time during work hours (48%) or sufficient tools and resources (48%) to build AI skills — meaning the other half do not. Leaders in the study stress that meaningful skill-building takes more than a course catalog: it requires dedicated time, hands-on experimentation, and active managerial support.
“Employees are far more optimistic about AI when they believe their organization will help them adapt as technology evolves.”
— Marion Devine, Principal Researcher, Human Capital, Europe, The Conference BoardFrom Training Programs to Learning Ecosystems
The report argues that traditional, standalone learning is no longer enough. Effective AI workforce development requires an enterprise-wide ecosystem — one that aligns strategy, governance, learning, workflow redesign, culture, and skills measurement, and reinforces AI capabilities across the entire employee life cycle from hiring through performance management. Crucially, skilling efforts pay off most when they are tied directly to business goals rather than treated as a training initiative on the side.
For CHROs and business leaders, the researchers recommend developing applied, outcome-focused capabilities; giving people real time and tools to learn through practice; blending formal, social, and experiential learning; and, above all, beginning to prepare for reskilling now — rather than waiting until workforce disruption becomes widespread and much harder to manage.
Training lags adoption. 55% of workers use AI regularly, but only 33% have had employer-provided AI training in the past six months — and 28% get none at all.
Skills stall at the basics. Most programs cover AI literacy and prompting; few build advanced skills like managing AI agents or embedding AI into workflows.
Time and support are missing. Only about half of workers say they have enough time (48%) or tools and resources (48%) to actually develop AI capabilities.
Reskilling is being neglected. Investment stays focused on upskilling current roles, leaving organizations underprepared for the redeployment AI will require.
Ecosystems beat programs. Success comes from enterprise-wide learning tied to business strategy — and from starting to plan for reskilling before disruption hits.
