As enterprises accelerate investments in artificial intelligence, a new study from Protiviti suggests that the biggest obstacle to realizing AI’s business value may not be technology—it may be workforce readiness. While most C-suite executives expect AI to boost revenue and profitability over the next three years, chief human resources officers (CHROs) are significantly less confident that organizations are prepared for the organizational redesign, skills development and cultural changes required to make AI transformation successful.

Artificial intelligence has become a boardroom priority, with organizations investing heavily in automation, generative AI and intelligent business processes to improve productivity and create competitive advantage. Yet as executive teams focus on technology adoption, HR leaders appear to be asking a different question: Is the workforce ready?

That tension is at the center of Protiviti’s fifth AI Pulse Survey, The AI-People Conundrum: Learning to Lead, Not Lag, which finds a widening perception gap between HR leaders and the rest of the executive suite. While nearly 80% of executives believe AI will improve both profitability and revenue growth within the next three years, CHROs are the least optimistic about whether their organizations can successfully manage the workforce transformation needed to unlock those gains.

The research, based on responses from nearly 800 global executives, more than 80% of whom hold C-suite roles, highlights an increasingly important reality for enterprise AI strategies: technology investments alone are unlikely to deliver sustainable business value without parallel investments in people, skills and organizational change.

Unlike their executive peers, CHROs are prioritizing workforce readiness over AI-driven financial returns. The survey found they are the only C-suite leaders who do not identify business value capture as AI’s primary objective by 2029, reflecting a broader concern that organizations may be underestimating the complexity of redesigning work for an AI-enabled future.

That cautious outlook is particularly evident in HR operations. Just 5% of CHROs expect at least half of HR work to be AI-enabled within the next three years, despite widespread recognition that many administrative HR tasks are suitable for automation.

The findings contrast sharply with expectations across other business functions. According to the survey, 88% of executives expect more than one-quarter of IT work to be AI-enabled within three years, compared with 72% in finance, 66% in supply chain, 56% in audit, and 50% in human resources.

While HR is expected to increase AI adoption substantially from current levels, executives responsible for workforce strategy remain considerably more cautious than their peers about the pace of that transformation.

The survey also points to significant differences in how executives assess organizational readiness.

Only 13% of CHROs strongly agree that their organizations have AI-ready job designs, compared with 28% across the broader C-suite. Confidence in learning and development capabilities is similarly low, with only 14% of CHROs expressing strong confidence that employees are prepared for AI-driven work, versus 36% overall.

By contrast, technology leaders express much higher confidence. Nearly 96% of IT executives report positive views of their organizations’ AI learning readiness, while 88% believe existing role designs can effectively support AI adoption.

The divergence suggests that HR leaders are evaluating AI transformation through a broader organizational lens. Rather than focusing primarily on deploying AI tools, they are considering the downstream implications for workforce planning, role redesign, compensation models, career pathways and employee development.

The survey reinforces a growing consensus among workplace analysts that AI transformation is increasingly synonymous with workforce transformation.

According to McKinsey & Company, organizations capturing the greatest value from generative AI are combining technology investments with operating model redesign, workforce reskilling and leadership development. Similarly, Gartner has emphasized that successful enterprise AI initiatives require organizations to redesign work—not simply automate existing processes.

Protiviti’s findings align with that perspective.

While many executives anticipate rapid AI adoption across enterprise functions, CHROs appear more focused on the organizational infrastructure required to sustain those changes over time. Around 82% of CHROs expect organizations to operate with a blended human-and-digital workforce by 2030, compared with 93% across the broader executive population.

That difference does not necessarily indicate resistance to AI. Instead, it reflects concerns that workforce transformation—including change management, learning strategies and organizational redesign—may not be progressing at the same pace as technology deployment.

The report also challenges assumptions about AI adoption within HR itself.

Although analysts estimate that a significant proportion of HR activities—including recruiting administration, employee support, document management and workforce analytics—can be enhanced through automation, many HR leaders remain cautious about deploying AI across functions that involve sensitive employee data, compliance requirements and complex decision-making.

Major enterprise software providers including Microsoft, Google, Salesforce, Workday, Oracle, and SAP continue expanding AI capabilities across HR platforms, embedding generative AI into talent acquisition, employee experience and workforce planning. However, enterprise adoption increasingly depends on governance, data quality and responsible AI practices rather than technology availability alone.

For HR leaders, the findings reinforce an evolving role within enterprise AI strategies. Rather than acting solely as users of AI-powered HR systems, HR departments are becoming architects of organizational transformation—responsible for redesigning jobs, developing AI literacy, supporting workforce reskilling and ensuring employees can effectively collaborate with intelligent technologies.

As organizations move from AI experimentation toward enterprise-wide deployment, workforce readiness may become one of the strongest predictors of AI success. Protiviti’s latest research suggests that while executive enthusiasm for AI remains high, sustainable business value will depend on whether organizations invest as heavily in people and organizational change as they do in technology.

Market Landscape

Enterprise AI adoption is rapidly expanding beyond pilot projects into core business operations. Vendors including Microsoft, Google, Salesforce, Workday, SAP, Oracle, and Adobe are embedding generative AI into HR, finance and productivity platforms, enabling organizations to automate workflows and enhance decision-making.

Research from Gartner and McKinsey & Company consistently indicates that AI delivers the greatest return when paired with workforce transformation, organizational redesign and continuous employee upskilling. As enterprises shift toward human-AI collaboration, HR leaders are expected to play a central role in aligning talent strategies with technology investments.

Top Insights

• Protiviti’s survey reveals that CHROs are significantly less confident than other executives about organizational readiness for AI, emphasizing workforce transformation over short-term business value.
• Only 5% of CHROs expect at least half of HR work to be AI-enabled within three years, reflecting concerns about governance, role redesign and scaling AI responsibly.
• Confidence in AI-ready job design and employee learning capabilities remains substantially lower among HR leaders than IT executives, highlighting a growing C-suite perception gap.
• Organizations expect AI adoption to accelerate across finance, IT, supply chain, audit and HR, but workforce readiness is emerging as a critical determinant of enterprise success.
• The findings reinforce that AI transformation increasingly depends on organizational redesign, employee reskilling and change management rather than technology deployment alone.

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