New research from University of Phoenix found that while most organisations have adopted artificial intelligence, many are still struggling to transform workflows and generate measurable business outcomes.
University of Phoenix has released the C-Suite AI Impact Report: Getting Value from AI, new research examining how organisations are working to turn artificial intelligence investments into measurable business outcomes.
Based on a survey of 150 C-Suite leaders across North America conducted in collaboration with Jeanne Meister, a future of work strategist and HR consultant, the report found a growing gap between AI adoption and enterprise-wide transformation.
Key findings revealed that 63% of C-Suite leaders have deployed at least one AI use case, but fewer than one-third are using AI to transform work processes and workflows. Meanwhile, 56% predicted AI will become a proactive human capital tool by the end of 2026.
The research also found that 90% of C-Suite leaders identified learning and development as the leading use case for AI in HR. Nearly 60% reported adopting a skills-based workforce model, although ownership of these initiatives remained fragmented across organisations.
In addition, 75% of respondents said HR and IT were unlikely to merge but would work more closely together in the future.
More than six in ten leaders cited productivity and competitive advantage as the main benefits of AI adoption, while employee fear and distrust remained the biggest barriers to broader implementation.
The report also highlighted the importance of leadership capabilities, with respondents identifying critical thinking and role-modelling AI literacy as essential skills for scaling AI successfully.
“The next phase of AI adoption is not about experimentation; it is about execution,” said Meister.
“Our research shows that leaders are increasingly focused on translating AI investments into measurable value by embedding AI into workflow design, skills development and day-to-day decision making. Organizations that align AI with a clear skills strategy and model its use at the leadership level will be better positioned to scale impact across the enterprise.”
According to the report, many organisations continue to pilot AI technologies without fully integrating them into core business processes. Leaders are increasingly focusing on how AI can support workflow design and measurable outcomes as they move from isolated projects to enterprise-wide deployment.
The findings also pointed to the growing importance of skills-based workforce strategies. While many organisations are embracing this approach, responsibility for skills initiatives is often spread across HR, IT and business leadership teams.
The report suggested that stronger collaboration between HR and IT will be critical to aligning workforce planning with AI investments and broader Digital Transformation objectives.
“C-Suite leaders are recognizing that implementing new technology in a vacuum does not create value,” said Jay Titus, Vice President of the Workforce Solutions Group, University of Phoenix.
“To best leverage and scale AI successfully, organizations must focus on how work gets done, including how teams build skills, collaborate across functions and address employee concerns. Trust, leadership behavior and pointing to clear use cases are just as important as the technology itself.”
The research also underscored the importance of addressing the human side of AI adoption. While productivity gains and competitive advantage remain key objectives, employee concerns continue to slow broader deployment efforts.
The report identified an ‘AI hopefulness gap’, with younger leaders expressing lower levels of optimism about AI’s impact compared with older generations.
To address these challenges, organisations are placing greater emphasis on AI literacy as a core workforce capability. Leaders stressed the importance of defining AI literacy expectations by role and demonstrating AI use at the leadership level to encourage adoption across the organisation.
The report concluded with recommendations for organisations seeking to move beyond isolated AI pilots and develop integrated strategies that connect skills development, workflow redesign and measurable business outcomes.
