If you’re a senior HR leader, you’re probably trying to identify where AI fits into your organization. You may also be underestimating the impact it’s already having.

“People are turning to AI all the time as a coach and to help with work, but they're just not telling management about it,”  Ethan Mollick, professor at The Wharton School and author of Co-Intelligence, said during Valence’s virtual summit, AI & the Workforce: The Adoption Gap. “They're worried about job outcomes because they’re saving time and they don’t want to give that time back to their companies. They also know efficiency gains can translate into headcount reduction.” 

What’s more, as managers and employees use AI to automate lower-level tasks, it’s collapsing the apprenticeship model that underpins talent development. “That training pipeline that was always implicit has broken, and it has to be reconstructed at the CHRO level,” Ethan emphasized. “That means thinking about what skills people need to learn in a deeper and more serious way.” 

While AI has the potential to unlock incredible gains, real transformation doesn’t happen in the shadows. Organizations need their own AI playbook to address these challenges, and it’s up to HR leaders to write it.

“HR is R&D now,” said Ethan. “The leverage point for organizations is the HR function.”  Here’s Ethan’s advice for talent leaders ready to meet this moment with vision.

Leader. Lab. Crowd.

Writing the AI playbook starts with building communities of practice, running challenges, and creating new ways to reward initiative and share best practices. Ethan’s Leader – Lab – Crowd framework is a great starting point to move from hidden experimentation to innovation and start to uncover the skills your employees need in a changing world.

Leader

Leaders must stop outsourcing AI understanding. The difference between leaders who panic in the face of AI and those who embrace the opportunity to lead comes down to one question for Ethan: “Have they used AI a lot? If you have not tried to use it for every business decision that you legally and ethically can, you don't know what it can do.” Ethan’s challenge to leaders: pick a day and use an AI model for everything you need to get done that day.

AI fluency is motivational. If you want employees to come out of the shadows, your leaders must show their own usage while painting a clear vision: What does work look like with AI? What does good usage look like? What will be rewarded—and what won’t?

Lab

Your AI lab can’t just live in IT. It needs to live in the business; it needs to live in HR.

Labs should be lightweight, fast-moving teams experimenting with workflows, roles, and learning journeys. Importantly, labs should include your AI power users—often employees without technical backgrounds who’ve figured out real use cases.

“The best users of AI I know are good managers, are good teachers,” said Ethan. “The skills that make you good at AI are not prompting skills, they're people skills. If you're good at understanding what someone might be confused about, if you're good at breaking down tasks into steps, if you're good at troubleshooting when someone goes wrong, you're going to be good at AI.”

Don’t wait for perfect policies. Start prototyping performance reviews, coaching systems, onboarding journeys, and L&D content that are AI-aware—and pressure-tested by real users.

Crowd

Your crowd—the employees already using AI behind the scenes—are your greatest untapped asset. They’re also the hungriest for guidance and tools.

“Your idea is to destigmatize use,” said Ethan. “The people who are already trying to evangelize AI, they become part of your lab. And then, of the rest of the people, some are just waiting on training, and some just need clear instructions. They need to get ideas, either from well-built products or from things that come out of the lab.” 

Five Experiments to Kickstart Your AI Playbook 

Creating your AI playbook hinges on experimentation. Ethan offered five experiments you can start running today.

1. AI-Annotated Deliverables

Require all internal reports and project submissions to include a short note on how AI was or wasn’t used—and what value it added.

2. Weekly “How Are You Using AI?” Ritual

In every leadership meeting, dedicate 5 minutes to share new uses of AI—live demos encouraged. Normalize experimentation at the top.

3. AI-First Role Design

Before creating a new role, require the hiring team to spend two hours trying to augment that role with AI, automating tasks and rethinking how AI embeds in the work. Then revise the job description accordingly.

4. Internal Hackathons or Contests

Run a low-stakes competition: What’s one workflow you've meaningfully improved using AI? Offer rewards, visibility, or cross-team collaboration time.

5. Performance Review Redesign

Don’t just use AI to write reviews. Redesign the review process to take advantage of AI’s continuous feedback capabilities—shifting from annual to ongoing performance nudges.

You Can’t Wait for the Manual

There’s no vendor, consultant, or AI lab that can tell you how to adapt your workforce better than your own people. “If you're waiting for someone to hand you a fully built out instruction on how to use AI, you're gonna be waiting until everybody else already figured this out, and that's too late,” Ethan said. 

This is HR’s moment to lead. Not just AI procurement and deployment, but the reinvention of work itself.

Watch the full discussion with Ethan Mollick and Valence CEO Parker Mitchell here.

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Alex McMurray is cofounder and VP of Sales at Valence, where she partners with Fortune 500 enterprises, including Experian, Prudential, Delta, General Mills, Coca-Cola, and more to effectively scale AI coaching to their front lines.