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

Acorn, the AI-powered performance enablement learning management platform, released The 2026 State of Learning for AI Fluency Report, revealing a significant disconnect in organizational AI readiness across a survey of more than 1,200 professionals. While 77% of executives believe their managers are prepared to guide AI skills development, 91% of employees say their managers lack that preparation. This structural disconnect explains why organizations are not seeing meaningful gains in skills despite heavy investment in AI training. The study shows that this manager preparedness failure sits at the intersection of three interconnected challenges: organizations lack role-level capability standards, managers lack the frameworks and confidence to guide development conversations, and employees are losing faith that either will change.

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“What this research makes clear is that there are two workforces experiencing the same AI deployment from fundamentally different positions,” said Blake Proberts, CEO and Founder of Acorn. “The deficiency in manager preparedness highlights a measurement infrastructure problem. Managers can’t guide development conversations they have no evidence to anchor on, and without that evidence, employees default to skepticism.”

Organizations Are Investing in AI Without Building the Infrastructure to Support It

Development plans are commonplace, but remain largely ineffective. Nearly six in ten organizations are currently running development programs they consider insufficient: 58% report their development plans are somewhat, not very or not at all effective at improving performance and building capability. Capability in this report is defined as the combination of personal and technical skills, knowledge, processes, tools and behaviors essential to an organization’s success and future needs.

The core issue is that organizations are tracking activity, not capability. Before AI, organizations already struggled to connect learning investment to measurable outcomes:

• 77% of organizations treat training completion as evidence of capability
• 64% of respondents can’t confidently say whether their company’s approach to measuring learning can answer if employees are getting better at their jobs
• 83% of respondents say there is a disparity between what employees in their organization report about their job capabilities and what they observe them demonstrating in practice

The same problem is now playing out with AI. Organizations are deploying AI tools into a workforce with no agreed definition of what AI capability looks like at the role level:

• 47% of companies have not included AI capability in formal performance reviews
• 34% of companies have not defined AI competencies at the role level
• 30% of companies have no formal mechanism to assess and track AI capability at the individual employee level
• 88% of companies may be experiencing a disparity in reported and demonstrated AI capabilities among their employees

“It is clear AI adoption has outpaced enablement,” said Keith Metcalfe, President of Acorn. “We see companies throwing budget at AI without giving their employees the guidance and support required to effectively use it in their roles. The result is an overly confident C-suite and a directionless employee base that is struggling to make sense of AI directives.”

Managers Are Unprepared and Executives Don’t Realize It

Managers play a key role in AI strategy and individual skill development, but the data shows they are under-equipped for the task, and leadership isn’t aware it’s a problem.

Seventy-five percent of individual contributors report their managers are only somewhat prepared or not prepared to have meaningful conversations about traditional skills and 54% of managers agree. Eighty percent of C-suite respondents say their managers are very prepared to have meaningful conversations with employees about their capabilities, including where an employee needs to develop and what ‘good’ looks like.

AI has made this manager preparedness failure and disconnect more acute:

• 91% of individual contributors say their managers are not fully prepared to have meaningful conversations with employees about their AI capabilities
• 77% of executives think their managers are very prepared for AI conversations but only 34% of managers feel prepared, and just 9% of individual contributors agree

“Without consistent check-ins, clear role-level standards and managers equipped to have meaningful development conversations, these plans have no impact,” said Proberts. “What’s missing is a capability layer that connects learning to performance.”

Employees Are Losing Confidence While Organizations Claim Readiness

The disconnect between executive confidence and employee reality is creating workplace anxiety and eroding the credibility of organizational AI readiness efforts: 58% of individual contributors are slightly skeptical and 28% are scared or disillusioned, which contrasts sharply with 82% of executives who report being excited about AI.

Nearly 60% of employees lack confidence applying AI in their role. Among those who have used AI tools, many remain ineffective:

• 58% of companies report employees who are proficient with AI in general but struggle to apply it meaningfully to their specific job
• 59% of individual contributors say AI has made them only slightly more efficient, with less than 10% improvement

Looking ahead, the outlook is bleak. Overall, 61% of respondents are not confident or only somewhat confident their organization’s current approach will prepare the workforce for AI-driven role changes over the next three years.

The C-suite, however, tells a different story. Almost 80% of executives are very confident their AI competency approach will prepare the workforce. However, 41% of individual contributors express zero confidence, a 65-point chasm that reflects something deeper than skepticism. Employees, the people these programs are designed for, do not believe they will work.

“The bottom line is organizations are instituting AI strategies without defining what AI competency looks like and subsequently building AI training programs without role-level targets,” shared Metcalfe. “The primary mechanism organizations are using to measure AI adoption is tracking usage. This gives a wholly incomplete picture of the state of AI readiness in the organization. Without the proper direction and training infrastructure, employees don’t know what ‘good’ looks like for AI in their role, managers can’t assess it and organizations are flying blind on one of the most consequential and unprecedented workforce transitions they’ll face.”

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