Most organizations are teaching employees AI basics, but few are preparing them for the real transformation ahead. A new report from The Conference Board finds that while 55.1% of workers use generative AI or AI agents daily or weekly, only 33.3% have received employer-provided AI training in the past six months. Nearly one-third of workers say their organization provides no AI training at all.

Why Is There Such a Big Gap Between AI Use and AI Training?

The disconnect reveals a fundamental misalignment in how organizations approach AI adoption. Workers are already using AI tools in their jobs, but their employers haven't invested in teaching them how to use those tools effectively. The Conference Board surveyed nearly 1,300 workers and interviewed 35 enterprise leaders to understand this gap, and the findings paint a troubling picture of organizations playing catch-up.

The problem goes deeper than just missing training sessions. Many organizations focus narrowly on AI literacy and basic prompting techniques, rather than helping employees develop the advanced capabilities they actually need. Workers report that they lack sufficient time during work hours to develop AI skills, with only 48% saying their organization provides enough time for learning. Even fewer, 47.6%, believe they have adequate tools, access, and resources to build AI capabilities.

"Many organizations have made progress introducing employees to AI, but AI literacy alone will not create business value. The organizations that benefit most from AI will be those that help employees apply AI effectively in their work, continuously develop new capabilities, and adapt as technology and business needs evolve," said Matt Rosenbaum, Principal Researcher, Human Capital at The Conference Board.

Matt Rosenbaum, Principal Researcher, Human Capital, The Conference Board

What Skills Are Organizations Actually Teaching?

The training gap extends to the types of skills being taught. Organizations are heavily emphasizing foundational knowledge, but they're neglecting the advanced capabilities that drive real business value. This creates a widening gap between what AI technologies can actually do and what employees are prepared to do with them.

• Foundational Focus: Most organizations emphasize AI literacy and basic prompting techniques rather than advanced applications.
• Missing Advanced Skills: Far fewer organizations help workers develop capabilities such as managing AI agents, integrating AI into workflows, or applying AI to strategic business challenges.
• Limited Hands-On Experience: Traditional learning approaches like classroom training are insufficient; workers report high value from multiple training formats including social learning and experiential learning.
• No Reskilling Preparation: Training investments remain heavily focused on upskilling current roles, leaving organizations unprepared for the large-scale reskilling that AI disruption will require.

How to Build an Enterprise-Wide AI Learning Ecosystem

The Conference Board recommends that organizations move beyond one-off training programs and build comprehensive learning ecosystems that align with business strategy. This requires coordination across multiple functions and a fundamental shift in how companies think about workforce development.

• Focus on Applied Capabilities: Develop skills that improve business outcomes, not just AI literacy. Connect training directly to real-world business challenges and measurable results.
• Provide Time and Tools: Give employees dedicated time during work hours for AI skills development, along with sufficient tools, access, and resources to practice and experiment.
• Combine Multiple Learning Approaches: Build learning architectures that blend formal training, social learning from peers, and hands-on experimentation with actual AI tools and workflows.
• Align Across the Organization: Ensure AI skilling efforts connect to business strategy and establish clear ownership for outcomes across HR, learning and development, technology, legal, and business units.
• Plan for Future Reskilling: Begin preparing now for large-scale reskilling needs rather than waiting until workforce disruption becomes widespread and organizations struggle to adapt.
• Build Employee Confidence: Strengthen trust that the organization will help workers adapt as AI technologies continue to evolve, which significantly increases employee optimism about AI's impact on their jobs.

The stakes are particularly high for facility managers and operations leaders, whose roles are rapidly transforming as smart buildings, predictive maintenance systems, and AI-enabled workplace operations become standard. These professionals need practical, hands-on training that goes far beyond basic AI literacy.

"Employees are far more optimistic about AI when they believe their organization will help them adapt as technology evolves. Building that confidence requires giving people the time, support, and opportunities to develop new skills as work changes," explained Marion Devine, Principal Researcher, Human Capital, Europe at The Conference Board.

Marion Devine, Principal Researcher, Human Capital, Europe, The Conference Board

What Happens When Organizations Get It Right?

Real-world examples show what's possible when companies treat AI workforce transformation as a strategic priority. Microsoft's fiscal year 2026 review documented organizations that moved from AI experimentation to embedding AI across core business processes, with remarkable results.

EY deployed Microsoft 365 Copilot to 150,000 employees and achieved a 15% productivity gain, then expanded the deployment across its global workforce of more than 400,000 people. The results included 95% faster lead times, a 37% reduction in finance operating costs, and up to a 90% reduction in manual workloads across key business processes.

Atos Group took a different approach, deploying AI tools to 56,000 employees across 54 countries and building an ecosystem of 19,000 AI agents through a unified operating model. The company created a repeatable model to continuously improve thousands of agents at scale while applying the same playbook to help customers accelerate adoption across highly regulated industries.

These successes share a common thread: organizations that treat workforce transformation as a leadership priority, align training with business outcomes, and provide employees with genuine support and resources see measurable returns on their AI investments. The Conference Board's research suggests that organizations still focused on basic AI literacy are missing the opportunity to unlock real competitive advantage.

"The organizations that navigate AI successfully will be the ones that treat workforce transformation as a leadership priority. CHROs have an opportunity to bring together business leaders, technology teams, and learning functions around a shared strategy for developing the capabilities the organization will need next," stated Diana Scott, US Human Capital Center Leader at The Conference Board.

Diana Scott, US Human Capital Center Leader, The Conference Board

The message is clear: the AI adoption gap isn't primarily a technology problem. It's a workforce development problem. Organizations that close the gap between AI use and AI training will be the ones that capture the real value from their AI investments.