This highlight video is from April 10, 2026 session Design Charrette | Stop Talking. Start Building AI Leaders
"One of the forerunners of these models is having the exact same problems as my tiny organization of four." — Iliana Alvarado, HumanSide
The business problem no one wants to say out loud
Michael Grubich works with hundreds of organizations worldwide. What he keeps hearing isn't a technology problem — it's a leadership problem. Organizations have tools. They don't have people who can translate those tools into business value.
Most have 7 or 8 AI tools being paid for independently across teams, no shared language, and no clear definition of what "AI-ready" even means. Mike brought that pressure into the room:
"It's not AI adoption — it's how do we get to AI evangelism? Who can translate AI into business value?" — Mike Grubich, LAK Group
That's the internal client's real ask. Not "use AI more." But who in your organization can connect AI capability to business outcomes — and do you know how to find, develop, and deploy them?
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Who was in the room: Michael Grubich (President & CEO, LAK Group), serving as the Internal Client; Iliana Alvarado (Managing Partner, HumanSide), as the AI Strategist — alongside Matt Sernaker (Executive Producer, Lake Forest Center for Leadership), David Scherer (Producer), and facilitator Dirk Tussing (CEO & President, ELE).
The discussion featured active contributions from Nicole DeFalco (CEO, Upsurge Advisors), Deepa Kartha (CEO, Journyz), Brady Bair (CNA Insurance), and Sandra Garcia (UL Solutions). These leaders were joined by a peer group of senior HR, Talent, and L&D executives representing over 20 global and local organizations across healthcare, financial services, insurance, and professional consulting.
The systems failure hiding in plain sight
Mike's framing set the stakes: three things are breaking simultaneously. Organizations can't identify who has AI potential internally. They don't know how to develop those people once found. And middle managers — 70–80% of most leadership populations — are the bottleneck where AI strategy stalls.
Sandra Garcia (UL Solutions) sharpened it further: middle managers can't explain the why of AI to their teams because no one gave it to them first. The anxiety travels down because the clarity never did.
That's not a training gap. That's a strategy gap wearing a training costume.
From programs to readiness — the shift is already happening
Mike's own firm is living this data: traditional leadership development requests dropped 3–4x year over year. Coaching requests tripled in Q1 alone.
People aren't abandoning learning. They're abandoning learning that isn't immediately applicable. The design question has changed: not "what program do we build?" but "what does this person need to do — and when?"
Agility over durability: Iliana's reframe for L&D
Where Mike named the problem, Iliana Alvarado brought the possibility lens. Her message: the entire design paradigm needs to shift — starting with why organizations are communicating the AI imperative wrong.
"The why is not because we want higher productivity — that doesn't rally employees." — Iliana Alvarado, HumanSide (AI Strategist)
The peer group pushed the design implications further. If the why is broken, so is everything built on top of it — including content that assumes durability when the moment demands agility.
"Sage on the stage has to go away… the human as guide on the side — not only for other humans, but also for AI." — Nicole DeFalco, Upsurge Advisors
The human orchestrates. They don't deliver content. That's the identity shift Iliana's AI Strategist lens kept returning to — and it points directly to where the real leverage is.
The middle manager is the inflection point — develop them first
That identity shift matters most in the middle. The C-suite isn't where AI transformation stalls — it's in the 70–80% of your leadership population sitting in middle and frontline management.
Start middle-out, not top-down. Develop managers first so they can hold space for real dialogue about how work is shifting locally. If they can't articulate the why of AI to their own teams, no enterprise strategy compensates.
The manager is the message.
Integration beats access: what the coaching data actually shows
When AI coaching is left to individuals, about 10% use it. When a human coach integrates it into their process, that jumps to 75%.
The AI Execution Gap: From fragmented adoption to strategic integration.
(Credit: Created with Google Gemini Banana Nano)
AI tools don't drive behavior change independently. They need a human in the loop — not to supervise, but to model and embed. Access isn't the problem. Integration is.
What to try next
1. Name your "AI Evangelists" — deliberately. Map your leadership population against one question: who can translate AI capability into a business outcome in their context? Early signal: can they articulate the why of AI to their team in a way that lands?
2. Build shared AI language before building more programs. If your C-suite, IT, HR, and frontline managers define "AI" four different ways, no strategy holds. Start with 10 cross-functionally agreed terms. Early signal: fewer alignment meetings needed to reach a decision.
3. Run one coaching pilot with AI integrated — not added. Assign a coach who builds AI into existing workflow. Measure engagement at 30 days. The 10%-to-75% gap isn't magic — it's what happens when AI becomes part of a trusted relationship rather than another platform to log into.
The question worth sitting with: What percentage of your current leadership development investment is explicitly designed to build AI capabilities your leaders need to be job-ready in the next 12 months — and do you actually know that number?
If any of these insights resonate — and you've got a top-of-mind talent business problem you'd like the ELE community to work on — send it our way. Members can submit their business challenge here: Submit My Business Challenge Now
