The human resources (HR) function, which is responsible for enabling workforce transformation in the artificial intelligence (AI) era, may not yet be fully positioned to lead that transformation. Unless HR leaders proactively engage at the C-suite decision table, where technology investments, operating-model decisions and workforce-readiness discussions are taking place, organizations risk deploying AI into an operating model that is not designed to absorb it.
This conclusion is based on Protiviti’s survey of nearly 800 executives globally, more than 80% of whom are C-suite leaders. The research found that chief human resources officers (CHROs) are less aligned than their C-suite peers on AI readiness, expected business value and the scale of workforce transformation required to capture that value. The study also found that HR lags leading functions in AI adoption and that CHROs express lower confidence in workforce readiness.
If organizations hope to realize AI’s full potential, four priorities must move to the top of the agenda.
1. Redesign work, don’t just automate tasks.
HR leaders must focus on redesigning work, not simply automating existing processes. According to the survey, only 13% of CHROs strongly agree that job descriptions and role designs are AI-ready, compared with 28% of respondents across the C-suite.
As AI compresses work into fewer, higher-value activities, simply layering technology onto existing jobs will not deliver transformational results. Organizations must rethink how work is structured, how talent is deployed, how performance is measuredmeasured, and how careers evolve in an AI-enabled workforce.
At a practical level, organizations should:
- Identify administrative and operational tasks that can be automated while elevating human responsibilities to higher-value activities
- Align workforce capabilities with future business and AI demands
- Redesign jobs around uniquely human capabilities such as judgment, creativity, problem solving and decision-making
2. Build continuous learning and workforce adaptability.
The second priority is ensuring employees can continuously adapt as skill requirements evolve.
AI transformation requires ongoing workforce development, not one-time training initiatives. Yet only 14% of CHROs strongly agree that their organization’s learning capabilities are AI-ready, compared with 36% overall.
Organizations should invest in learning models that support:
- Continuous reskilling
- AI literacy
- Human-AI collaboration
- Rapid workforce adaptation
- Cross-functional learning
The goal is not simply to teach employees how to use AI tools. It is to build a workforce capable of evolving alongside rapidly changing technologies.
3. Prepare managers to lead human and digital workforces.
The third priority is developing management capabilities suited to hybrid workforces.
Over the next several years, organizations expect AI to evolve from an efficiency tool into a driver of business value. That transition will require managers to oversee work performed by both people and AI-enabled systems.
Managers must increasingly become orchestrators of AI-enabled work rather than supervisors of human labor alone. This requires new capabilities, including:
- AI literacy and fluency
- Governance and oversight skills
- Ability to evaluate AI-generated outputs
- Cross-functional collaboration
- Ethical decision-making
- Accountability for human and digital performance
Managers must also learn how to coach employees working alongside AI while maintaining trust, transparency, and responsible use of technology.
4. Modernize performance management and rewards.
Workforce transformation does not end with jobs and skills. Organizations must also evolve compensation, incentives, and performance-management systems. You cannot redesign roles for AI-enabled work while evaluating employees using metrics designed for a pre-AI environment.
As AI assumes a greater share of routine work, traditional measures such as activity levels, output volume and hours worked become less meaningful indicators of performance. Instead, organizations should place greater emphasis on:
- Business outcomes
- Decision quality
- Innovation
- Customer impact
- Productivity improvements
- Revenue contribution
- Speed to market
If AI can complete a significant portion of a task in minutes, rewarding employees solely for the volume of work completed becomes less valuable than measuring the impact they create.
Organizations should also avoid measuring AI productivity through a single metric. Protiviti’s research suggests a broader approach that combines business performance metrics, workflow analytics, adoption indicators and workforce-readiness measures to assess how AI contributes to business value.
Performance metrics should extend beyond efficiency and cost savings to include productivity improvements, revenue growth, customer satisfaction, time-to-market acceleration, innovation outcomes, and workforce readiness. Executive incentives should align with these priorities and include measures such as AI-adoption milestones, workforce reskilling progress, role redesign completion, talent mobility and AI-enabled productivity gains.
Achieving C-suite Alignment on the Future of Work
None of these changes can succeed without leadership alignment and HR’s active participation in AI strategy.
If leaders disagree on how work will evolve, it becomes difficult to align investments in technology, talent, learning, and workforce design. This challenge is particularly important because the survey found significant differences between CHROs and other members of the C-suite regarding AI readiness, workforce transformation, and future value expectations.
Organizations should establish a cross-functional AI workforce steering committee to bring together the CFO, CIO, COO, CHRO and business leaders to define future workforce requirements; develop workforce-readiness metrics and review them regularly alongside AI investment plans; and align workforce transformation initiatives with enterprise AI strategies and business objectives.
Ultimately, AI transformation is workforce transformation. Organizations that redesign work, build adaptive learning models, prepare managers for hybrid workforces, and align leadership around a shared vision of the future of work will be well positioned to convert AI investments into sustainable business value. And, for HR leaders, one final point: to lead workforce transformation credibly, HR must also accelerate AI adoption within its own function. The future of work cannot be shaped effectively by a function that remains behind in its own transformation.
Fran Maxwell is Managing Director at Protiviti.