AI Adoption Gap Puts Leadership in the HR Spotlight

Enterprise AI investment is accelerating, but organizations are finding that deploying tools does not automatically translate into better business performance. New research from the FranklinCovey Institute suggests that one obstacle may be less about technology access and more about how leaders guide employees through change. In a June 2026 global worker survey, employees ranked honesty about AI’s impact on their work as their most desired leadership behavior. Yet only 36% said they received that transparency from their manager, highlighting a people-management challenge for organizations seeking measurable returns from AI.

AI Adoption Is Becoming a Leadership Challenge

For many organizations, the first phase of enterprise AI adoption involved giving employees access to generative AI tools, encouraging experimentation, and identifying tasks that could be automated. The next phase is proving more complicated: embedding AI into everyday workflows and ensuring that increased usage produces meaningful improvements in performance.

New research from the FranklinCovey Institute puts leadership behavior at the center of that challenge. A June 2026 global survey of workers across industries and regions asked employees which leadership behaviors they most wanted during AI transformation. The findings suggest that employees are looking for more than software access or technical instruction. They want clarity, learning opportunities, support for experimentation, and a practical explanation of how AI relates to their jobs.

The survey’s five highest-ranked behaviors were honesty about how AI will change work, access to AI learning opportunities, a safe environment for experimentation, help connecting AI to specific workflows, and a clear organizational vision.

However, the percentages published alongside those rankings measure how many employees say they currently receive each behavior from their leaders—not how many employees want it. Only 36% reported receiving honesty about AI’s impact, while 41% said their leaders helped connect AI to their team’s specific workflows. The full research report is still forthcoming, and the announcement does not provide the survey’s sample size or detailed methodology.

Transparency Is the First Test for AI Leaders

The highest-ranked employee expectation was straightforward: leaders should be honest about how AI will change work. Only 36% of respondents said they received this from their manager.

That finding points to a central workforce issue. AI adoption can create uncertainty about job responsibilities, performance expectations, required skills, and the future shape of particular roles. If leaders communicate only the benefits of new tools without addressing those concerns, employees may be left to interpret the implications themselves.

For HR teams, transparency needs to extend beyond broad statements that AI will improve productivity. Employees need to understand which tasks may change, where human judgment remains essential, what new capabilities will be expected, and how the organization intends to support people through the transition.

This is not simply a communications exercise. It connects directly to workforce planning, job design, employee engagement, and change management.

Training Needs to Connect With Real Work

Access to learning opportunities for building AI skills ranked second in the FranklinCovey survey. Yet only 46% of employees said their leaders provided those opportunities.

The result reinforces the importance of moving beyond generic AI awareness sessions. Employees need role-relevant guidance that shows how AI can support the work they actually perform.

A finance team, for example, may need training in AI-assisted analysis and reporting. Customer service employees may need to understand how AI-generated responses should be reviewed. HR professionals may require guidance on responsible use in recruitment, employee communications, and workforce analytics.

The challenge is to connect training with practical application. Employees should be able to identify appropriate use cases, understand the limitations of AI-generated outputs, and know when human review is necessary.

The findings also give HR leaders a reason to work more closely with business-unit managers. Learning teams can provide the framework, but managers are often best positioned to identify where AI can improve specific processes and where employees need additional support.

Psychological Safety and Experimentation Matter

Creating a safe space for experimentation and learning ranked third among employee expectations. FranklinCovey reported that 59% of respondents said they received this behavior from their leaders—the highest current-receipt figure among the five behaviors listed.

That result is encouraging, but it also shows why experimentation needs to be paired with structure. Employees should be able to test approved tools, share lessons, and identify useful applications without fearing that every unsuccessful attempt will be treated as a performance failure.

At the same time, experimentation cannot mean unrestricted use. Organizations need clear policies covering confidential information, data protection, accuracy, intellectual property, and human oversight.

HR, IT, legal, and business leaders therefore have complementary responsibilities. HR can help establish learning cultures and behavioral expectations, while technical and risk teams define the controls that make experimentation responsible.

From AI Access to Workflow Redesign

The FranklinCovey findings align with a wider industry concern: AI use is spreading faster than enterprise-wide transformation.

McKinsey’s November 2025 global survey found that 88% of respondents said their organizations regularly used AI in at least one business function. Yet nearly two-thirds said their organizations had not begun scaling AI across the enterprise. Only 39% reported an enterprise-level EBIT impact from AI.

The research also identified workflow redesign as an important differentiator for organizations capturing greater value from AI. In other words, adding AI to an existing process may not be enough. Companies may need to rethink how work is allocated, how decisions are made, and where people and AI systems collaborate. <a href=”https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-2025″>McKinsey’s State of AI 2025 research</a> provides a broader view of this adoption-to-value challenge.

That shift has implications for HR technology and workforce strategy. As AI moves from individual productivity tools toward agents and more complex workflow applications, organizations will need to reconsider job responsibilities, skills frameworks, performance measures, and employee development.

FranklinCovey Positions Leadership Development as Part of AI Readiness

FranklinCovey is positioning its AI readiness offering, AI Realized: From Disruption to Advantage, as a response to the leadership and behavior gap identified in its research.

The solution includes Gain AI Traction, a leader and team experience designed to develop four behaviors: confidence, consistency, capability, and adaptability. The company’s approach focuses on helping employees become more comfortable using AI, establishing shared practices, developing practical skills, and adapting as tools and workflows change.

The program is intended for both leaders and individual contributors. FranklinCovey says its approach is designed to help organizations move from scattered experimentation toward broader adoption and more effective human-AI collaboration.

The company also cites work with large technology organizations and other clients, including a logistics organization whose workforce development executive described improved clarity, reduced anxiety, and increased usage. That is a customer testimonial rather than independently measured evidence of financial returns.

The distinction matters. Leadership development can support adoption, but organizations still need to establish clear business objectives, measure workflow improvements, and assess whether AI investments deliver sustained value.

The CHRO’s Role in Making AI Transformation Work

The survey adds to a growing case for CHRO involvement in enterprise AI strategy. HR leaders are positioned to connect technology deployment with workforce planning, skills development, organizational culture, and employee experience.

That role is likely to expand as businesses move toward agentic AI and automated workflows. Employees may need to supervise AI-generated work, manage exceptions, validate outputs, and collaborate with systems that perform multi-step tasks.

Leaders will need to explain not only which tools are available but also how work is changing and what employees need to do differently. Managers will require practical guidance, while HR teams will need ways to monitor skills readiness, employee confidence, adoption patterns, and the impact of redesigned roles.

FranklinCovey’s central argument is that leadership determines whether AI increases activity or improves performance. Its survey does not independently establish that leadership behavior causes stronger AI returns, but it highlights a workforce dimension that organizations cannot afford to overlook.

For HRTech leaders, the next stage of AI transformation is therefore not just about selecting platforms. It is about preparing people, redesigning work, and building the management practices that allow technology to create lasting organizational value.

Market Landscape

The AI adoption challenge is increasingly shifting from tool availability to organizational readiness. Research from McKinsey and PwC points to workflow redesign, workforce skills, trust, and leadership alignment as important factors in moving beyond experimentation.