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Key takeaways:
- Leading CHROs are moving beyond isolated AI pilots and focusing on integrated, value-driven HR transformation that redesigns work, workflows, and employee experiences.
- Agentic AI is helping HR leaders reimagine hire-to-retire processes, reduce operational friction, and strengthen HR’s role as a strategic advisor to the business.
- Organizations that succeed with AI in HR start with a clear strategy, design agentic-first workflows before selecting technology, and measure outcomes such as experience, cost-to-serve, decision velocity, and capacity redeployment.
This article is co-authored by Wesley Long, AVP – HR Technology at AT&T, and PwC Partner, Astik Ranade about how leading organizations are approaching agentic AI in HR.
Over the past 12 months, headlines increasingly questioned whether AI in HR was delivering the anticipated productivity gains and cost savings, putting CHROs under pressure and prompting many to take a more cautious approach to AI investment.
Yet a turning point emerged, driven by a new approach spearheaded by forward-looking CHROs. First, these leaders moved beyond scattered pilots and began applying AI to specific business challenges - redesigning experiences and workflows around human judgment and rethinking how work gets done. Second, they moved beyond simply relabeling automation as AI and began investing in higher-value, adaptive opportunities that learn from interactions, improve decisions, anticipate needs, and create compounding value over time.
What enabled these leaders to move from skepticism to execution was a sharper focus on, and a more sophisticated understanding of, how agentic AI is beginning to reshape HR and value creation.
Why Disconnected AI Pilots Fall Short
To be clear, AI did not fail. “AI pilot theater” fell short. In late 2025 and early 2026, many organizations reassessed their portfolio of standalone AI pilots. Although these initiatives increased activity and awareness, they often delivered little business results or durable progress. It became clear that realizing AI’s potential would require an integrated strategy tied to specific business priorities. The next step was to shift from experimentation for its own sake to a coordinated strategy centered on business value.
In the second half of 2026, leading CHROs began moving beyond standalone use cases toward integrated experiences supported by a portfolio of value-focused pilots. Anchor projects targeted broader strategic outcomes, with productivity gains emerging as one benefit rather than the primary goal.
How did they get there?
This value-led AI strategy reflects a fundamentally different view of AI, not as a quick fix but as a long-term shift in how people, processes, and technology work together. CHROs taking this approach recognize that meaningful transformation requires human ingenuity supported by AI-enabled solutions.
Productivity creates projects, reimagining value delivers transformation
As these efforts took shape, HR leaders began positioning themselves as enterprise talent advisors. By blending human insight and organization context with AI-powered agents, they can help shape strategy, redesign work, and guide workforce decisions to support business performance. These AI-enabled HR leaders are contributing in several ways:
Don’t reinvent dysfunction
Reimagining HR requires more than applying AI to existing processes. It means redesigning processes to remove system-imposed “coordination tollbooths,” from labor cost spent on extra time, handoffs, follow-ups, and approvals embedded in legacy ways of managing routine transactions.
Consider a redesigned leave-of-absence process. Agents could validate eligibility based on policy and individual circumstances, route and secure approvals, update relevant systems and notify stakeholders. Removing manual handoffs and follow-ups would make the process simpler and more responsive for employees and HR teams alike.
Forward-looking HR leaders are identifying where AI can orchestrate work across the employee lifecycle. They are applying agentic-first workflow principles that reduce operational friction, while establishing a clear definition of what “agentic-first” means for their organizations.
Together, these efforts are shaping an agentic orchestration ecosystem that reduces the need for users to navigate multiple HR systems and lowers cost-to serve across HR workflows. Key elements of this transformation include:
Operationalizing the employee experience through agent-enabled HR service delivery
Finally, forward-thinking HR leaders prioritize organizational value and employee experience supported by agentic-first workflows. When those priorities guide the transformation, greater efficiency and cost savings follow.
Done well, this approach can generate more meaningful gains in efficiency, scalability, and risk reduction. Together, those benefits create a clear and defensible business case grounded in strategic and operational leverage, not headcount reduction.
Where should leaders start?
Prove value then scale: HR’s agentic AI strategy
CEOs are watching to see whether HR can lead the way in agentic AI innovation and workforce productivity. This is an opportunity for HR to modernize its own operations, to seize the moment, prove it can be done, and set the standard for responsible implementation. HR can then apply what it learns to help other functions make better decisions about agentic AI, bringing a critical understanding of talent, skills, work design, and human adoption.
What does it mean to do this well? HR leaders should begin with a clear north star: an agentic AI strategy that improves the employee experience and delivers real organizational value. From there, they can work backward to define the operating model, workflows, and governance and investments required to achieve it. Productivity gains should emerge from a better-designed work naturally from agentic-designed HR work.
Rather than starting with tools or point solutions, leaders should build an HR taxonomy for the agentic era. This practical framework (and shared dictionary of HR activities) should define, at the activity level, how HR will deliver AI-enabled experiences and higher-value services.
Leaders can then compare this future-state taxonomy to today’s delivery model. The contrast makes explicit how activities, roles, and capacity shift as agentic capabilities come online and where the organization can redeploy human effort to higher-value work.
No strategic plan is complete without a clear value case and enterprise buy-in. By building a financial case with investment requirements, risk considerations, and capacity impacts, leaders can prioritize the high-impact opportunities. These opportunities can also unlock productivity and operating leverage to help secure buy-in for outcome-driven funding—not technology for technology’s sake.
Blueprint the employee lifecycle: Avoid fragmented journeys
Leaders should define end-to-end, agentic-first workflows across the employee lifecycle and translate them into reusable agent skills. These skills should incorporate enterprise context, decision logic, orchestration rules, and governance. Structured design session can then test how these skills work, how they connect, and where human judgement or intervention remains essential.
As teams participate in the process, skepticism can give way to practical innovation. The conversation shifts from “Will this work?” to “How far can this go?” These sessions build understanding and encourage adoption while creating a practical blueprint for production-ready agents.
For example, through client workshops, PwC helped one organization identify productivity opportunities within its learning administration workflows. The organization expanded its vision to include AI agents capable of generating personalized learning videos, moving from process efficiency toward a more tailored learning experience.
This is where widespread adoption begins. By co-creating the future workflows that agents can execute, organizations can build confidence, momentum, and ownership while establishing the foundation required to move from conceptual design to deployed agents.
Together, these steps enable organizations to lead with experience and value, translate intent into agentic execution, and enable productivity and financial impact to emerge as measurable, defensible outcomes.
The path forward for AI in HR
The claim that “AI in HR isn’t delivering” is the wrong diagnosis. The technology itself did not fail. The greater challenge was disconnected pilots, inconsistent implementation, and weak linkages to HR’s operating model.
CHROs who broke through are winning by rewiring how HR runs, clarifying decision rights, redesigning workflows end to end, and putting controls and measurements in place so AI can be trusted.
The future of HR isn’t about hype or deploying AI everywhere at once. It’s about redesigning work with intent, building confidence across functions, and scaling responsibly.
What executives should do now is to move with strategic urgency:
- Reframe: Move from episodic standalone pilots to a governed “portfolio of priorities” aligned with a scalable north-star AI for HR strategy.
- Establish a baseline: Know where you are starting. Establish a clear baseline across value, experience, cost, roles to be automated or augments, and human effort.
- Design before building or buying: Translate the north-star strategy into agentic-first workflows before selecting tools or scaling pilots. Define the required agent skills, orchestration logic, governance controls, and exception paths.
- Clarify who does what: Break each AI-enabled workflow into modular capabilities and determine which could be performed by people, agents, or both. Then redefine role purpose, responsibilities, and required skills. Even where agents have not yet been deployed, organizations can begin decomposing and categorizing the work.
- Measure value: Commit to outcome measures that executives can trust, such as cycle time, cost to serve, risk reduction, decision speed, and capacity redeployment, not vague “productivity” claims.
The organizations that lead in 2026 and beyond will not be necessarily those with the most AI experiments. They’ll be the ones that combine human ingenuity with agentic capabilities, build the foundation for responsible deployment, demonstrate value early, and scale with confidence.
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