"AI doesn't need you to change who you are, but it's going to show you clearly who you've been." -- Marty Murrillo

At the ELE Spring Conference on May 21st, keynote speaker Marty Murrillo of Precisely opened with a challenge most AI rollout plans never get to: adoption doesn't stall because of the tools. It stalls because the tools force a reckoning with professional identity — who people believe they are at work, where they hold authority, and what they're still worth when AI can do 60% of what used to define them. Until people leaders address that layer directly, no amount of tool training moves the needle.

The identity gap no one is putting on the roadmap

Most organizations are treating AI adoption as a change management problem. Marty Murrillo reframed it as an identity problem — and the distinction matters enormously for how people leaders show up.

Three things are being disrupted simultaneously: the work itself, the tools people use to do it, and the workflows that connect them. Best practices are outdating every 6–12 months. Interfaces are changing weekly. The ground keeps shifting — and employees are privately asking questions their managers haven't been invited into yet.

"What am I here for? What do I still uniquely add? Where do I still make decisions?" -- Marty Murrillo

These aren't engagement survey questions. They're the internal monologue of a workforce negotiating its own value in real time. People leaders who skip this conversation and go straight to tool adoption are solving the wrong problem.

Leaders in the conversation

The May 21st live discussion brought together people leaders and senior talent professionals engaging directly with Murrillo's framework for identity-driven adoption. The room wasn't debating whether AI would change work — it was grappling with the harder question of how to lead people through a shift that touches role, value, and authority all at once.

What's actually changing — and what stays human

Murrillo was direct about where the real capability shift lands. Task-based expertise — the work AI can increasingly replicate — is no longer a stable identity anchor. What remains distinctly human is judgment, ethics, and the ability to ask whether something should be done, not just whether it can be.

"What stays with you? Judgment, ethics — thinking about whether this is the right thing to do." -- Marty Murrillo

This is the reframe people leaders need to be making explicitly with their teams. The goal isn't to convince employees that AI won't change their roles. It will. The goal is to help them anchor their professional identity in the work AI cannot do: reading a room, sensing what the numbers aren't showing, holding the relational and ethical weight of decisions.

That's the capability shift — from output production to strategic stewardship. And it requires leaders to model it, not just message it.

The leader's own identity shift comes first

One of the sharpest signals from Murrillo's keynote: you cannot guide a workforce through this change if you haven't moved through it yourself.

The shift from knowing answers to asking better questions. From task expertise to judgment and ethics. From holding authority to sharing agency with AI. These are internal moves — and leaders who skip them end up communicating a roadmap they haven't personally walked.

As highlighted during the live discussion:

"Leaders can't just talk the talk. They have to walk it too." -- Marty Murrillo

Visible leadership behavior is the adoption signal the workforce is reading most closely. Executives who say "I don't know, let's try it" — and mean it — are doing more for adoption than any enablement program run without that cultural backing.

Psychological safety isn't a culture initiative in this context. It's an operational condition for AI adoption. Teams need permission to experiment, fail publicly, and keep moving. That permission has to come from the top — and it has to be behavioral, not just stated.

Clarity about decision rights is the hardest thing to provide — and the most valuable

One of the most practical signals from the live discussion: ambiguity about where AI stops and humans start is feeding the authority anxiety that stalls adoption faster than any tool friction.

Employees aren't just asking what AI can do. They're asking where they still get to decide. Without explicit answers, they default to anxiety or avoidance — and people leaders read that as resistance when it's actually a reasonable response to unclear boundaries.

Defining decision rights — which calls stay with humans, which route through AI — isn't an IT governance question. It's a leadership clarity question. And it belongs on the people leader's agenda, not just the tech team's.

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What to try next

1. Run the Three Bucket Exercise with your team. Ask each person to sort their top 12 tasks into three buckets: AI does alone, human + AI together, and uniquely human. It moves the conversation from abstract anxiety to concrete analysis — and gives individuals agency over their own role evolution.
2. Use the 50% threshold as a workforce planning signal. If more than half of someone's tasks land in the "AI does alone" bucket, that's a proactive role conversation — not a performance issue. Getting ahead of it builds trust and preserves the talent you'll need for the work that remains distinctly human.
3. Make your own identity shift visible this week. Name publicly — in a team meeting, a one-on-one, or a leadership communication — which of the three shifts you're personally working through. Leaders who model the internal work build more credibility for the change than those who only communicate the strategy.