New Research: 77% of Executives Say Managers Are Prepared to Guide AI Skills Development, While 91% of Employees Disagree

Why It Matters

The disconnect undermines ROI on AI training spend and hampers organizations’ ability to leverage AI for competitive advantage, signaling an urgent need for measurable capability frameworks.

Key Takeaways

• 77% of execs say managers ready for AI skill guidance
• 91% of employees say managers unprepared for AI conversations
• 34% of managers feel equipped to discuss AI capabilities
• Less than 10% efficiency gain reported from AI tool use
• 88% of firms see gap between reported and actual AI capability

Pulse Analysis

The new Acorn report highlights a systemic blind spot in corporate AI enablement: leaders are confident their managers can steer AI learning, yet frontline workers overwhelmingly disagree. This misalignment stems from a lack of clear, role‑specific AI competency definitions, leaving managers without the metrics needed to coach effectively. As a result, training programs become checkbox exercises, with 77% of organizations treating course completion as proof of capability, even though 58% admit those programs are only somewhat effective.

Without standardized AI skill frameworks, companies struggle to translate AI tool usage into measurable performance gains. The data shows that only a minority of firms have embedded AI competencies into performance reviews (47%) or defined them at the role level (34%). Consequently, employees report minimal efficiency improvements—under 10%—and a growing sense of skepticism, with 58% slightly skeptical and 28% scared or disillusioned. This sentiment contrasts sharply with the 82% of executives who remain excited about AI, creating a cultural chasm that can erode trust and slow adoption.

For businesses aiming to capitalize on AI, the path forward requires shifting from activity‑based metrics to capability‑based assessments. Implementing role‑level AI standards, equipping managers with evidence‑based coaching tools, and linking learning outcomes directly to performance indicators can close the confidence gap. By doing so, firms not only protect their AI training investments but also unlock the productivity gains necessary to stay competitive in an increasingly automated marketplace.