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ELE is a peer-powered community where people leaders don't just reframe challenges — they leave with decisions, next moves, and 30/60/90-day commitments to move real work forward.&nbsp;For 22 years, leaders from Fortune 1000 companies have brought their hardest problems here — and left sharper than they arrived.

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This is where people leaders get sharper — and their teams get smarter.ELE is a peer-powered network of people leaders who accelerate business results through shared intelligence and real-work collaboration. Learn more below about why ELE has been the trusted choice for leaders building high-performing teams for over 20 years.

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Insights on Talent Challenges | Captured Peer Conversations | ELE

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Executive Learning Exchange (ELE)

<div style="font-family: 'Calibri', 'Candara', 'Segoe UI', 'Optima', Arial, sans-serif; color: #333; line-height: 1.6; max-width: 800px; margin: auto; font-size: 1.1rem;">
<blockquote style="border-left: 4px solid #990000; margin: 20px 0; padding: 10px 20px; background-color: #f8f9fa; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"Expertise alone is insufficient. What is it that is uniquely me that I bring to that table?"</blockquote>
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.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 30px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">They scrapped the script — on purpose</h3>
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 —

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"AI can't necessarily do that."</blockquote>
The presenters named what was emerging: these are coaching skills. And in the current environment, they're not supplementary. They're the job.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 25px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">The tension that ran through the whole room</h3>
Three leadership tensions shaped the dialogue. None of them were new. All of them are harder right now.
Confidence vs. Learning

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"Leaders feel pressured to project confidence while privately figuring it out themselves."</blockquote>
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:

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"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."</blockquote>
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.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 25px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">What "change metabolization" actually means for your team</h3>
One phrase surfaced in the room that's worth holding onto: change metabolization [00:05:48]. 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.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 25px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">What the room heard — and recognized</h3>
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:

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"We're asking for higher levels of maturity from leaders — and that doesn't come overnight."</blockquote>
That's not a discouraging signal. It's an honest one. And it points toward what L&amp;D and people leaders can actually do: build the conditions for that maturity to develop, rather than assuming a training program will produce it.


<hr style="border: 0; border-top: 1px solid #eee; margin: 40px 0;" />

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-bottom: 15px;">What to try next</h3>
Three moves worth testing quickly — all anchored in what surfaced during the live exchange:

<ol style="padding-left: 25px; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">
 	<li style="margin-bottom: 15px;">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.</li>
 	<li style="margin-bottom: 15px;">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.</li>
 	<li style="margin-bottom: 15px;">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.</li>
</ol>
<div style="background-color: #f1f4f9; padding: 20px; border-radius: 8px; margin-top: 40px; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">
Bring this work into the ELE community
If this connects to real work you are trying to move forward — whether that's helping managers lead through AI adoption, rebuilding professional identity after expertise gets disrupted, or designing development that actually builds the maturity this moment requires — bring it into the ELE community. Share the challenge, compare signals with trusted peers, and leave with practical next moves you can use.
Submit My Challenge Now: <a style="color: #0056b3; font-weight: bold; text-decoration: underline;" href="https://www.ele.llc/faqs/share-top-of-mind-talent-challenges">https://www.ele.llc/faqs/share-top-of-mind-talent-challenges</a>

</div>
</div>

Mindset Shift | From AI Anxiety to AI Agency

Digital &amp; AI

jane.shlaes

susan.finerty

Coaching

AI Adoption

manager enablement

wise2026

insights-wise-2026

peer intelligence

practical next moves

AI Anxiety to Agency

People Manager Role

Professional Identity Shift

Change Metabolization

Leadership Vulnerability

Human Skills at Work

Coaching Skills for Managers

Expertise and Meaning

Stability vs Agility

Leadership Maturity

Lurie Children's

Precisely

BARYONS

<div style="font-family: 'Calibri', 'Candara', 'Segoe UI', 'Optima', Arial, sans-serif; color: #333; line-height: 1.6; max-width: 800px; margin: auto; font-size: 1.1rem;">
<blockquote style="border-left: 4px solid #990000; margin: 20px 0; padding: 10px 20px; background-color: #f8f9fa; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"Curiosity, creativity and improv. That's it. That is literally all you need."</blockquote>
People leaders navigating AI transformation aren't lacking tools — they're lacking a practice. That was the live, unscripted signal that surfaced when <a href="https://www.ele.llc/people/michael-hruska" target="_blank" rel="noopener">Mike Hruska</a> (BARYONS) and <a href="https://www.ele.llc/people/marty-murrillo" target="_blank" rel="noopener">Marty Murrillo</a> (Precisely) brought a small-circle conversation into a larger room at the ELE Spring Conference 2026: the real work isn't getting teams access to AI, it's shifting from access to active, continuous practice — while keeping human judgment at the center and stopping organizational bias from scaling silently into every automated decision.
Leaders shaping the work
This live interactive discussion grew out of a deliberate collective intelligence experiment — a small facilitated group thought out loud together, captured it, fed it to AI in real time, and then opened the floor to a wider room to add the next layer. What emerged wasn't a polished framework. It was a working exchange between people leaders, coaching practitioners, and L&amp;D professionals thinking through the same friction from different angles: How do I stay in control of this? Where does my real value live now? And what do I do about the biases already baked into my data?

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 30px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">The first question isn't which tool — it's who's driving</h3>
The discussion opened with a model worth keeping.
[Insert Post-Sharing Slide Graphic: The Technology Centaur Model]
The centaur keeps the human in the lead — AI as power-multiplier, not director. The reverse centaur flips it: the algorithm manages the human, tells them where to go, tracks their eyes, controls the pace. The room recognized both patterns immediately.
One participant described having to actively reset their AI tool — telling it to update its memory, stop its accumulated assumptions, and behave differently. It worked. But the moment landed as something more than a tech tip.

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"No one really knows what they're doing — no matter what they say. We're all improvising together."</blockquote>
That's the actual operating condition. Leaders who perform certainty about AI adoption are spending energy they don't have. The ones moving fastest are treating it like improv: curiosity-first, troop mindset, building as they go.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 25px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">Context is the real input — not the prompt</h3>
One of the sharpest practical moves in the room came from a simple story: 28 executives at a global company, most of whom had never used generative AI before. Generic prompts produced generic output. Then two participants tried something different — they told the AI to treat itself like a 20-year-old intern named Sam, gave it real context about the person's tenure and background, and asked it to ask them questions first.
<img class="aligncenter" src="https://wp.ele.llc/wp-content/uploads/2026/06/The-Intern-Sam-Context-Strategy.jpg" alt="" />
Output quality transformed. Not because the tool got smarter — because the human input got richer.
The practical implication for people leaders: the quality of what AI returns is a direct function of the organizational and personal context you give it upfront. Thin context, thin output. This isn't a prompt engineering tip — it's a practice design decision.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 25px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">AI as mirror: the administrative shift and the blind spot problem</h3>
Two connected signals ran through the middle of the discussion.
The first: AI is already compressing the time it takes to do the work that buries managers. One leader described processing 360-degree feedback for 14 direct reports in two hours — and finding things human review had consistently missed.
<img src="https://wp.ele.llc/wp-content/uploads/2026/06/Manager-Span-of-Control.jpg" alt="" />

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"The non-obvious stuff popped up. It works."</blockquote>
That's not an efficiency story. That's a capability story — AI as forensic mirror, surfacing patterns in your own language, your team's feedback, your organization's blind spots. The leaders in the room who were already doing this weren't using AI to replace judgment. They were using it to see what judgment alone had been missing.
The second signal is harder. When one participant described a hiring algorithm that had silently learned a decade of the organization's own gender bias — promoting patterns that favored men, demoting signals associated with women — the room shifted.

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"You have to check for biases because it'll just amplify what you have."</blockquote>
The data you feed AI carries the fingerprint of every assumption your organization has normalized. Scaling that without interrogating it first isn't transformation — it's acceleration of the status quo.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 25px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">The jerk factor — and why your change model is already outdated</h3>
Traditional change management assumes a beginning state, a transition, and a future state you're moving toward. That model is broken.
The discussion introduced a more honest frame: in mathematics, the "jerk" is the rate-of-change of acceleration. Not change itself — the change of how fast change is changing. That's what people leaders are actually living through. And it's why the standard change playbook produces exhaustion instead of traction.

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"The future state doesn't exist because it's the next iteration. The next iteration. So no wonder you're tired."</blockquote>
The replacement isn't a better Gantt chart. It's a different operating posture — curiosity, creativity, improv — and the recognition that collective intelligence across a trusted peer group is how you navigate what no individual or organization can map alone.


<hr style="border: 0; border-top: 1px solid #eee; margin: 40px 0;" />

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-bottom: 15px;">What to try next</h3>
<ol style="padding-left: 25px; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">
 	<li style="margin-bottom: 15px;">Run one forensic session on your own work. Feed a recent coaching conversation, team debrief, or performance review into an AI tool. Ask it to surface language patterns, themes you avoided, or signals that repeated without resolution. Use the output as a mirror, not a verdict. Early evidence signal: you find at least one pattern you hadn't consciously named.</li>
 	<li style="margin-bottom: 15px;">Front-load context before every significant AI task. Before asking for output, give the tool your role, your specific challenge, your constraints, and your audience. Treat it like briefing a capable but uninformed thinking partner — not issuing a command. Early evidence signal: your first-draft output requires meaningfully less reworking than before.</li>
 	<li style="margin-bottom: 15px;">Audit one AI workflow for direction. Pick one place where AI is already part of your work. Ask honestly: am I directing this, or is it directing me? If you can't answer clearly, reset — start a clean context, set explicit parameters, reassert what you want. Early evidence signal: you can describe the decision boundary between your judgment and the tool's output in one sentence.</li>
</ol>
<div style="background-color: #f1f4f9; padding: 20px; border-radius: 8px; margin-top: 40px; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">
Bring your work into the room
If this connects to real work you are trying to move forward, bring it into the ELE community. Share the challenge, compare signals with trusted peers, and leave with practical next moves you can use.
Submit My Challenge Now: <a style="color: #0056b3; font-weight: bold; text-decoration: underline;" href="https://www.ele.llc/faqs/share-top-of-mind-talent-challenges">https://www.ele.llc/faqs/share-top-of-mind-talent-challenges</a>

</div>
</div>

Leadership Development | Driving AI Transformation

leadership development

marty.murrillo

AI transformation

michael.hruska

AI Coaching

human-centered ai

People Leaders

baryons.aimentor

Coaching Practice

Collective Intelligence

Organizational Bias

Data Bias

Change Acceleration

Forensic Self-Analysis

Span of Control

<div style="font-family: 'Calibri', 'Candara', 'Segoe UI', 'Optima', Arial, sans-serif; color: #333; line-height: 1.6; max-width: 800px; margin: auto; font-size: 1.1rem;">
<blockquote style="border-left: 4px solid #990000; margin: 20px 0; padding: 10px 20px; background-color: #f8f9fa; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"AI doesn't need you to change who you are, but it's going to show you clearly who you've been." -- <a href="https://www.ele.llc/people/marty-murrillo" target="_blank" rel="noopener">Marty Murrillo</a></blockquote>
At the ELE Spring Conference on May 21st, keynote speaker <a href="https://www.ele.llc/people/marty-murrillo" target="_blank" rel="noopener">Marty Murrillo</a> 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.

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"What am I here for? What do I still uniquely add? Where do I still make decisions?" -- <a href="https://www.ele.llc/people/marty-murrillo" target="_blank" rel="noopener">Marty Murrillo</a></blockquote>
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.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 30px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">What's actually changing — and what stays human</h3>
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.

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"What stays with you? Judgment, ethics — thinking about whether this is the right thing to do." -- <a href="https://www.ele.llc/people/marty-murrillo" target="_blank" rel="noopener">Marty Murrillo</a></blockquote>
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.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 25px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">The leader's own identity shift comes first</h3>
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:

<blockquote style="border-left: 4px solid #990000; margin: 15px 0; padding: 5px 20px; font-style: italic; color: #555; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">"Leaders can't just talk the talk. They have to walk it too." -- <a href="https://www.ele.llc/people/marty-murrillo" target="_blank" rel="noopener">Marty Murrillo</a></blockquote>
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.

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-top: 25px; margin-bottom: 10px; border-bottom: 1px solid #eee; padding-bottom: 5px;">Clarity about decision rights is the hardest thing to provide — and the most valuable</h3>
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.


<hr style="border: 0; border-top: 1px solid #eee; margin: 40px 0;" />

<h3 style="font-family: 'Montserrat', sans-serif; font-weight: bold; color: #1a1a1a; font-size: 1.3rem; margin-bottom: 15px;">What to try next</h3>
<ol style="padding-left: 25px; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">
 	<li style="margin-bottom: 15px;">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.</li>
 	<li style="margin-bottom: 15px;">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.</li>
 	<li style="margin-bottom: 15px;">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.</li>
</ol>
<div style="background-color: #f1f4f9; padding: 20px; border-radius: 8px; margin-top: 40px; font-family: 'Calibri', sans-serif; font-size: 1.1rem;">
Bring your work into the room
If this connects to real work you are trying to move forward, bring it into the ELE community. Share the challenge, compare signals with trusted peers, and leave with practical next moves you can use.
Submit My Challenge Now: <a style="color: #0056b3; font-weight: bold; text-decoration: underline;" href="https://www.ele.llc/faqs/share-top-of-mind-talent-challenges">https://www.ele.llc/faqs/share-top-of-mind-talent-challenges</a>

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Mindset Shift | From AI Anxiety to AI Agency

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