I recently joined David Wachtel—General Manager of HCM Products at Workday and a longtime friend—on Workday's Future of Work podcast. We covered a lot of ground: AI literacy, trust, operating culture, what it actually takes to lead through this moment. If you haven't listened, I'd encourage you to. But there's a point I kept circling in that conversation without fully landing it — and I want to say it clearly here.
HR is not losing ground to AI. HR is ceding it. And that's a choice, not an inevitability.
Workday's Future of Work Pod: What We Got Into
Dave opened with something that's been sitting with me. Workday's research shows that 83% of employees are being asked to work faster because of AI—but 40% don't believe speed alone generates better outcomes. He asked me why that friction exists.
My answer was direct: They're right.
"Speed doesn't mean better outcomes. In most of the early deployments, we really have just scaled existing ways of doing things. More is not better, and faster is not better."
What we've done in most early AI deployments is exactly what we did during cloud transformation—lifted and shifted. Same processes, just running on different infrastructure. We got to go-live, called it done, and planned to optimize later. Very few actually did.
Dave also asked what's at stake if HR doesn't keep up, and (again) I said it plainly: "We become stakeholders and not stewards."
We get consulted. We weigh in. We occasionally pump the brakes. But we don't lead. And the business isn't going to make space for us to catch up.
As I said on the podcast: "The business is not going to wait for us to be AI ready before they go forward with their AI agendas." They're not waiting. The question is whether HR shows up to lead or gets handed the outcome.
Beyond BCRs: HR's AI Stewardship Problem
After listening to the full episode (surely I'm not the only one that analyzes every word they say in a recording?) I felt compelled to double-down on this point. It's just too important to gloss over: When HR is the stakeholder of a technology initiative, minimum viable is often the starting point for the solutions we get. All of that nuanced complexity that often relegates us to fun police
And when it comes to AI, which has introduced an unprecedented urgency to innovate and evolve, the definition of minimum viable is… highly subjective depending on who's in charge.
Here's what the minimum viable gap actually looks like in practice:
Say your organization deploys an AI HR agent to triage employ requests and queries. Great use case, something many are leading with… but also a salient case in point for why MVP matters so much for HR.
As defined by IT, a minimally viable solution could respond to questions about leave by simply providing a link to relevant policy documents. You asked about leave, here's the leave policy. Requirements met, right? I mean… kind of.
When HR leads that same implementation, the solution looks different. It answers specific questions to the best of its ability–and escalates certain conversations to an HR business partner. It applies guardrails so the AI isn't inferring or advising beyond its lane. The governance is more robust because the people building it understand what's at stake when an employee is asking about leave at 11pm on a Sunday.
That's not a technology gap. That's a domain knowledge gap. And it only closes when HR is at the helm, when it's both ready and able to lead AI solution design–and workforce transformation more broadly.
But posture alone--the insistence that HR should lead workforce strategy design, delivery and management for the AI-enabled enterprise--the posture is the easy part. The hard truth is that many teams aren't ready to lead. Org-wide AI literacy closely tied to business acumen, solution-oriented governance and risk management–these are the critical capabilities for HR's next chapter.
Closing the Gaps: Our Not-So-Shiny Path Forward
The honest reason HR ends up in the stakeholder seat isn't malice or incompetence. It's real, closeable gaps that we haven't historically had the tools or community to address. Understanding these gaps was the primary reason we developed the AI Momentum Model. Closing those gaps is why I founded the Human-Centric AI Council—and why, last month, we launched the Cohort Zero Transformation Toolkit.
If you missed last week's Town Hall, we built four frameworks (all free to use thanks to our underwriters). Not aspirational best practice documents--real guides built by practitioners who have actually moved AI work forward inside real organizations.
- An AI literacy course with applied learning and real HR scenarios
- A Responsible AI Framework as an interactive workbook
- An AI Change Management guide to help you wrap your head around the full scale of AI's catalytic changes
- A Solution Decision Framework—build, buy, borrow, or bot—that accounts for what you already own before you go shopping.
These weren't built by vendors. They were built by HR leaders at Cisco, Appian, The Estee Lauder Companies, Calendly, Blue Origin, Coinbase, Miro—people who hit the same walls you're hitting and built the tools they wished they'd had.
As I said on the podcast:
"We need to lead the way in being human. Being human-centric."
That's not a platitude. It's the whole point. HR's domain knowledge—about people, about work, about what good outcomes actually look like—is exactly what's missing from enterprise-led AI initiatives right now.
The toolkit is the foundation, and the work continues with a refresh of the AIMM this fall--and a new Council Cohort. What is AI's real impact on HR operating models? How do you govern responsibly without stalling? What stays human—and who decides?
Those are stewardship questions. And the window to claim them is open—but it won't be forever.
Listen to my full conversation with Dave on Workday's Future of Work podcast. And explore the toolkit at kyleandco.com/aicouncil—Cohort Two applications are open.
