Dashboard

Forms

Listening Meetup

Page banners

Plan landings

Main navigation

Gallery

Upload

Media library

Memberships

All tickets

Create ticket

Prepaid tickets

Users

For 22 years, senior leaders from Fortune 1000 companies have brought their hardest problems here — and left sharper than they arrived.

UPCOMING CALENDAR

LATEST IDEA EXCHANGE

RECENT INSIGHTS

WHO WE ARE

Schedule a Meetup

About ELE

Schedule a Local Meetup

Bring a real bottleneck. Name what's stuck, what's at stake, and why it matters now.

Community-Powered Calendar

Signal what matters most. Your vote shapes what this community tackles next.

Companies In Our Network

Contact ELE

Find the peer conversation that moves your work forward.The right exchange builds better leaders, closes capability gaps, and cuts through what internal meetings can't.

Figure out if ELE is for you. Straight answers on what ELE is, who it’s built for, and how contributing members actually work together. Still have a question? Contact us.

Get answers about how Executive Learning Exchange (ELE) works — peer-powered leadership development that fixes real work issues, reverses burnout, and accelerates business value. No programs. No vendors. In the flow of work.

Real challenges. Real peers. Clear next moves.

This is where people-leaders get sharper.

Want ELE to come to you? Propose a local gathering — the community decides what gets scheduled.

LAK Group

CNA Insurance

Allstate Insurance

Waukesha County Technical College

Marquette University

HumanSide

<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;">"For leaders, what we need to be is responsibly curious. Ask questions, be interested, not interesting." — <a style="color: #333; text-decoration: none;" href="https://www.ele.llc/people/michael-grubich" target="_blank" rel="noopener">Michael Grubich</a>, LAK Group</blockquote>
The real work in the room
Senior talent leaders, executives, and academic advisors came together to move past the hype and get honest about what AI adoption actually requires — not just tool access, but structural redesign. The work was getting stuck where organizations were overlaying AI onto unchanged roles, skipping the governance architecture that builds real trust, and treating adoption as a communications problem rather than an organizational design problem. It matters now because the window for deliberate design is narrowing: the organizations pulling ahead aren't moving faster — they're moving more intentionally.
Leaders in the conversation
Michael Grubich, President of LAK Group and adjunct faculty at Marquette's College of Business Administration, brought a practitioner's lens on talent strategy and organizational decisions across industries. Peter Hogaboam, Director of Technical Learning and Communications at CNA Insurance, shared live pilot architecture and the nuts-and-bolts of progressive risk assessment. Jim Orheim, Program Director for Executive Education and Professional Development at Marquette University, offered the academic institution's perspective on what enterprises expect from incoming talent. Dr. Phyllis King, Chief Innovation Strategist at Waukesha County Technical College, reframed the literacy-versus-skills distinction that anchored much of the exchange. Lorna Malloy, Strategic L&amp;D Leader at Allstate, brought a Fortune 100 view of AI integration at scale — and the felt reality of how fast organizational mindset can shift. Interactive prompts from practitioners across the room surfaced the environmental friction, the silence masking resistance, and the governance gaps most organizations haven't named yet.

<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;">AI skills vs. AI literacy — and why the difference will cost you</h3>
<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;">"There's a difference between AI skills and AI literacy." — <a style="color: #555; text-decoration: none;" href="https://www.ele.llc/people/phyllis-king" target="_blank" rel="noopener">Phyllis King</a>, Waukesha County Technical College</blockquote>
AI skills mean a person can operate a tool. AI literacy means they understand the effect, the ethics, and the responsible intent behind using it. One produces tool competency. The other produces organizational judgment.
Most enterprise training programs are building the former while assuming the latter follows automatically. It doesn't. Organizations that conflate the two are producing workforces that can run AI but can't govern it — and that gap shows up in compliance failures, inconsistent use, and adoption that stalls the moment someone asks a hard question about risk.
The practical implication is structural: foundational training needs to target literacy first, tool fluency second. Jim Orheim described Marquette's College of Business already requiring all faculty and staff to complete ethics, safety, and responsible-use training this summer — not because they're behind, but because they want to set the standard before the pressure arrives from outside.

<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;">Taking the seat — redefining the job, not just the toolset</h3>
<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;">"They took an organizational approach to it versus a tactical approach." — <a style="color: #555; text-decoration: none;" href="https://www.ele.llc/people/michael-grubich" target="_blank" rel="noopener">Michael Grubich</a>, LAK Group</blockquote>
He described a client who stopped all incoming AI tools, stepped back to re-examine every role against business strategy, assessed whether the right people were in position, and then deployed. That sequence — organizational design before tool deployment — is what makes adoption stick.
The panel was direct: top-down AI messaging registers at roughly 4% on the behavior-change iceberg. The real work happens at the middle-manager and frontline-leader layer — and that's exactly where L&amp;D and HR have the deepest reach. Waiting for C-suite clarity to cascade is not a strategy.
When an organization doesn't know how to rewrite roles, update operating norms, or establish communication agreements around AI use, those are not technology problems. They are people-leader problems. The moment to act on that is now.

<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 unspoken realities — resistance, the grid, and what's coming</h3>
The sharpest exchange in the room didn't come from the panel. It came from the floor.
A practitioner asked directly: is the environmental impact of enterprise AI data centers part of anyone's governance conversation? The panel's honest answer was largely no — and one leader named it plainly, stating that right now their organization does nothing and doesn't even have a plan yet.
What followed surfaced two signals that most organizations are not yet tracking.
The first is a psychological safety gap hiding in plain sight. Change management practitioners in the room described a dynamic that's easy to miss: people are reading the organizational climate and choosing not to surface real concerns — including environmental and ethical reservations — because they anticipate those concerns being framed as resistance to adoption. The silence looks like buy-in. It isn't. It's suppressed friction that will surface later, at a much higher cost.
The second signal is generational and incoming. Several practitioners noted that a wave of talent is arriving with environmental values baked in as non-negotiables — and that when those employees encounter mandatory AI adoption with no sustainability framework attached, the disconnect will be immediate and visible.
These aren't fringe concerns. They're governance gaps that organizations with mature people-and-culture infrastructure will be better positioned to absorb — and that organizations without it will be caught flat-footed by.


<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;">Audit your training for the literacy gap. Pull your current AI training content and ask one question: does this teach people how to think about AI use, or only how to perform it? If the ethics, intent, and governance dimensions aren't explicitly present, close that gap before the next cohort goes through.</li>
 	<li style="margin-bottom: 15px;">Design a listening mechanism specifically for suppressed resistance. Pulse surveys and skip-level conversations with a direct question about AI concerns — anonymous, low-stakes, framed as input rather than performance assessment — will surface what people aren't saying in public. That signal is more operationally useful than any adoption metric you're currently tracking.</li>
 	<li style="margin-bottom: 15px;">Run one role-redefinition conversation before the next tool deployment. Before any new AI capability goes live on your team, gather the relevant people leaders and ask: if this tool does what it promises, what changes about this role? What stays? What needs to be renegotiated — including expectations, norms, and potentially compensation? That conversation, done once with intention, builds the muscle for doing it at scale.</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 real work into the community
If this connects to work you're trying to move forward — a stalled AI rollout, a governance structure that isn't holding, roles that need redesigning, or a room that's gone quiet when it shouldn't — 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>

Executive Cohort Panel | Framing the Why

Future of Work

Digital &amp; AI

michael.grubich

lorna.malloy

peter.hogaboam

Middle Management

jim.orheim

AI Adoption

phyllis.king

L&amp;D strategy

AI literacy

dustin.brewer

manager enablement

responsible AI use

wise2026

People Leaders

executive-cohort

insights-wise-2026

peer intelligence

role redefinition

Organizational Redesign

Governance and Trust

Change Resistance

Systemic Change

Environmental Impact of AI

Precisely

<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>

</div>
</div>

Executive Cohort Panel | Framing the Why

Identity Drives AI Adoption — or Stalls It

Login