The CHRO Action Plan: From Learning Programs to Living Performance

For years, HR leaders have talked about productivity, transformation, and growth as parallel tracks. Today, those tracks are converging. AI is accelerating how work gets done, but the real shift is not just technological. It is organizational. The most forward-looking CHROs are redesigning how teams operate, how trust is built, and how learning shows up in daily performance.

This action plan outlines three priorities shaping that shift. The first two are already gaining traction. The third is where the work becomes truly strategic.

1. Deploy AI at the team level, not just the individual one

Early AI adoption focused on personal efficiency. Faster writing, quicker analysis, cleaner summaries. Useful, yes. Transformational, no.

The biggest productivity gains appear when AI improves how teams coordinate, make decisions, and learn together. Shared visibility into workflows, patterns, and outcomes reduces friction and guesswork. It also creates a common language for improvement that feels less personal and less political.

As Allison Pinkham, former CHRO of Galderma, put it:

“When you have AI observing how team dynamics work, it automatically takes away the defensiveness. It’s observing observable behavior. There’s no ‘maybe they’re biased.’ That’s an opportunity to bring teams closer together.”

This is a subtle but critical point. Team-level AI shifts feedback from judgment to data. It allows performance conversations to center on patterns and outcomes rather than personalities.

2. HR owns the design principles that make AI usable and trusted

Most executives now agree that AI will reshape work. Where alignment breaks down is on how that change is introduced.

If employees experience AI primarily as monitoring, scoring, or headcount reduction, adoption slows and resistance hardens. Trust is not a communications issue. It is a design issue.

HR is uniquely positioned to set the rules of engagement:

• What data is collected and why
• How insights are used in decisions
• What protections exist for employees
• How human judgment remains part of the loop
• How feedback improves with use

Organizations that codify these principles early create momentum. Those that delay end up managing fear instead of performance, especially when it comes to feedback. This turns performance management into a partnership. And with Gallup showing that teams with regular feedback have 14.9% lower turnover, that’s more than feel-good HR — it’s business impact.

3. Learning will become performance, and adaptability becomes the advantage

This is where the real reset begins.

For decades, learning lived outside of work. Courses, programs, certifications, and development plans were designed as inputs. Performance was the output measured later.

That separation no longer holds.

The shift from learning events to learning signals

AI-enabled work environments generate constant feedback. Decisions, interactions, and outcomes leave data trails. Learning no longer needs to be scheduled. It can be embedded directly into the flow of work.

What changes is the unit of value.

Instead of asking:

• Who completed the program?
• Who earned the credential?

Leading organizations ask:

• Who adapted fastest when priorities shifted?
• Which teams improved outcomes after feedback?
• Where did capability gaps close in real time?

Research from the World Economic Forum shows that skills instability is accelerating, with nearly half of core skills expected to change within a few years. This makes static role definitions increasingly fragile.

Performance, then, becomes the visible expression of learning. If learning is not changing behavior and results, it is not learning. It is content.

Workforce planning moves from prediction to capacity

Traditional workforce planning tries to forecast roles years in advance. That approach struggles in environments defined by rapid technological and market shifts.

A more resilient model focuses on adaptive capacity:

• How quickly can teams reconfigure?
• How easily can skills travel across roles?
• How prepared are managers to coach through change?

This is where T-shaped roles matter. Deep expertise still anchors value, but horizontal skills make that expertise usable across contexts.

Common horizontal capabilities include:

• Cross-functional collaboration
• Data-informed decision-making
• Coaching and feedback literacy
• Change navigation

McKinsey research on reskilling emphasizes that organizations outperform peers when they invest in these transferable capabilities alongside technical depth. The payoff shows up in speed, not just skill.

Learning becomes continuous, visible, and accountable

When learning is integrated into performance systems, it becomes harder to hide and easier to improve.

High-performing organizations are beginning to:

• Surface learning moments inside weekly workflows
• Use AI to identify where support is needed, not just who is struggling
• Equip managers to reinforce learning through real work, not post-course checklists

This aligns with findings from the Gartner, which notes that employees are more likely to apply new skills when learning is contextual, timely, and manager-supported.

Adaptability becomes measurable. Growth becomes observable. Development stops being aspirational and starts being operational.

What this means for CHROs right now

The future of work is not waiting for the next framework or technology. It is already forming inside teams that learn while performing and perform while learning.

The CHRO action plan is clear:

• Scale AI where work actually happens, at the team level
• Design trust into systems before expecting adoption
• Redefine learning as a performance capability, not a support function

Organizations that make this shift will not just keep pace with change. They will compound capability while others chase it.

That is not a learning strategy. It is a performance strategy, and if you need help rethinking your strategy, let’s start here.