"Expertise alone is insufficient. What is it that is uniquely me that I bring to that table?"

People leaders know the rollout playbook by heart — executive messaging, training programs, adoption metrics. What it can't address is the quieter, harder work underneath: helping managers move their teams from AI anxiety to genuine agency when those same managers are privately navigating the same shift themselves. That's the real work Jane Shlaes and Susan Finerty brought to the stage at the 2026 WISE conference — a live, interactive keynote exchange that quickly became something more useful than a prepared presentation.

People shaping the work

Jane Shlaes and Susan Finerty, both long-tenured practitioners in talent development, coaching, and leadership change, co-facilitated this keynote exchange. Their starting point: the people manager role is the most trusted and influential lever in any organization for helping teams move from uncertainty to ownership — and that role is under-equipped for what AI adoption is actually asking of it.

They scrapped the script — on purpose

Here's what made this keynote exchange different. Shlaes and Finerty arrived with a prepared outline and AI-assisted slides. Then they looked around the room, recognized they were in a space full of practitioners who'd been wrestling with these same tensions all day, and made a deliberate call: set aside the deck and farm the expertise already in the room.

What came back was immediate and specific. People managers can build trusting relationships. They can tailor conversations to the individual. They can hold space. They can model their own uncertainty transparently. They can make people feel genuinely heard in a way that — as one voice in the room put it plainly —

"AI can't necessarily do that."

The presenters named what was emerging: these are coaching skills. And in the current environment, they're not supplementary. They're the job.

The tension that ran through the whole room

Three leadership tensions shaped the dialogue. None of them were new. All of them are harder right now.

Confidence vs. Learning

"Leaders feel pressured to project confidence while privately figuring it out themselves."

This signal didn't just surface in this keynote — the presenters noted it had threaded through nearly every other presentation at the event. The shared reframe: vulnerability isn't a liability in an AI adoption moment. Modeling uncertainty openly, and being visibly side-by-side with your team in the learning, may be the most credible thing a people leader can do right now. Performing readiness when you don't have it is the move that erodes trust.

Expertise vs. Meaning

This is the tension that carries the most emotional weight. Generative AI has effectively flattened technical expertise — the thing many leaders and individual contributors built their professional identity around. When someone in the audience put it directly, the room recognized it immediately:

"People are being asked to break their own expertise in order to transform it — they're attached to it. It's a huge part of their ego."

The practical implication isn't to minimize that loss. It's to help people answer a harder question: if my expertise isn't enough anymore, what is uniquely me? The answer, surfaced across the live exchange, points consistently toward relational and coaching skills — the things that aren't being flattened.

Stability vs. Agility

Many organizational systems are still designed to reward optimization and consistency. But the actual work — especially in matrixed, cross-functional environments — has become continuously iterative. Roles shift. Priorities reprioritize. Decisions get renegotiated. The gap between what leadership systems reinforce and what the work now requires is a structural mismatch, not a personal failing. Helping managers thrive in that ambiguity, rather than just survive it, is a development gap most organizations haven't fully addressed.

What "change metabolization" actually means for your team

One phrase surfaced in the room that's worth holding onto: change metabolization . The idea — that people absorb and process change at different rates, in different ways, based on who they are and what the change is asking of them — reframes the manager's role from change communicator to change companion. The manager who knows their people well enough to tailor that journey is doing something AI cannot replicate.

What the room heard — and recognized

The 10-second silence near the opening of the keynote exchange wasn't a warm-up gimmick. The presenters asked everyone to bring to mind someone they knew personally who had moved from uncertainty to ownership — and then let the room sit with it quietly. In a full conference day, that pause landed differently. It named something most people hadn't had space to acknowledge: that this transition is personal before it's organizational, and the people closest to their teams are the ones positioned to hold that.

The closing note was equally direct:

"We're asking for higher levels of maturity from leaders — and that doesn't come overnight."

That's not a discouraging signal. It's an honest one. And it points toward what L&D and people leaders can actually do: build the conditions for that maturity to develop, rather than assuming a training program will produce it.

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What to try next

Three moves worth testing quickly — all anchored in what surfaced during the live exchange:

1. Start with emotion, not information. Before moving a team member toward action on AI adoption, find out where they actually are emotionally. The coaching question sequence surfaced in the keynote follows a simple arc: emotion → possibility → action. Skipping to action without the first two steps is why most adoption conversations stall.
2. Make "what's uniquely me?" a real conversation. As expertise gets flattened, people need help identifying what they bring beyond technical knowledge. This isn't a pep talk — it's a structured coaching conversation. What do you do that AI can't replicate? What relationships, judgments, and contextual reads are yours alone? That question is worth making explicit.
3. Model your own uncertainty — visibly. Transparency about where you're still learning isn't a credibility risk in this environment. It's a trust signal. Name what you're figuring out alongside your team. That side-by-side posture is what the live exchange kept returning to as the move that actually accelerates the shift from anxiety to agency.