"Senior leaders are not crafting the why. So people aren't really being expected to use it to drive performance." — Nicole DeFalco, Upsurge Advisors
The business problem hiding inside your AI rollout
Most organizations have launched AI tools. Fewer have launched leaders who know how to use them.
That's the gap this live interactive discussion set out to close. The business problem, as Anton Maletich (Alter Domus) put it plainly from the Internal Client chair: his organization had hundreds of agents built by a fraction of its workforce, productivity targets declared but unmeasured, and no shared standard for what AI-enabled work actually looks like. The tools were live. The strategy wasn't.
Who was in the room: Senior HR, L&D, and business leaders including Nicole DeFalco (Upsurge Advisors) as facilitator, Anton Maletich (Alter Domus) as Internal Client, Marty Murrillo (Precisely) as AI Strategist, and Christopher Lind (Christopher Lind Co.) as Real-World Skeptic, alongside a cross-section of ELE members spanning healthcare, financial services, manufacturing, and consulting.
It's not an adoption problem. It's a leadership framing problem.
Anton grounded the room in what the Internal Client actually experiences: a tool mandate from the top, fragmented usage below, and no shared definition of success. Agents were being built in silos — some redundant, some ungoverned — and no one was asking whether they addressed productivity that actually mattered.
"The agent marketplace is now the nightmare that the LMS has been. We've just replaced the LMS with an agent marketplace." — Nicole DeFalco
The tools proliferated. The strategy didn't.
AI output isn't neutral — and neither is your judgment
This is where the Real-World Skeptic earned his moment. Christopher Lind named the tension the room needed to hear: AI output that looks polished on the surface is often structurally empty underneath — no performance-tied behaviors, no measurable outcomes, no accountability built in.
"It looks good on the surface to a seasoned expert, it actually is usually slop." — Christopher Lind
He also introduced the "Grandeur Effect" — AI doesn't just affirm ideas, it presents them as grand, unique, and never-before-seen. The risk isn't bad output. It's confident-looking output that leaders ship without reading closely.
"It can make you look better than you are, and you don't really know." — Dirk Tussing, ELE
The CRIT Model: From assistant to thought partner
Marty Murrillo — in the AI Strategist role — offered the reframe: the problem isn't that leaders are bad at prompting. It's that they've never been asked to treat AI as a thought partner rather than an answer machine. The CRIT Model changes that architecture.
We live-tested Marty's demonstration of the CRIT Model (Context, Role, Interview, Task). The breakthrough? The Interview step. By forcing the AI to ask us questions before generating an answer, we surface blind spots and pressure-test assumptions.
The CRIT Model for AI-driven leadership, from Geoff Woods. (Credit: Google Gemini Banana)
The insight wasn't about the tool itself — it was about leadership capability. If a leader can't answer the AI's interview questions, that gap is the actual business problem to solve.
A moment that mattered
When AI pushed back on a vague prompt — asking the group to name a specific business outcome, not just "improve productivity" — the room landed on something honest: most organizations don't actually know what AI-driven performance looks like in their context.
Dirk Tussing put it plainly: "If we just ask for general stuff, we're gonna get general stuff back."
The CRIT interview step didn't just improve the AI output. It exposed the strategic ambiguity that was already there.
What to try next
Start with one decision, not one tool. Have senior leaders identify a single business decision — something that already happens this quarter — where AI will be used to inform or accelerate it. Name the outcome. Define what "better" looks like before anyone touches a prompt.
Run the CRIT interview on yourself. Before building any AI-enabled leadership development, use the CRIT model's Interview step with a real organizational challenge. If the senior leaders in the room can't answer the clarifying questions, that's your curriculum.
Baseline before you build. Christopher Lind's challenge to the group: if you want to improve productivity, what's your baseline today? Without it, any change is just a gut feeling. Ask your internal client to name the data they have — and flag what's missing.
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
