Training · Leadership, Lab, and Crowd

Your team will use AI on Monday, or your AI strategy is theater.

Three tracks for three audiences. Execs need a mental model. ICs need hands-on patterns. The wider org needs the cultural setup. Pick one or stack all three. Anchored on Mollick's Leadership-Lab-Crowd. Built to survive without me.

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TL;DR · 60-second read

What you walk away with

Your team stops being AI-curious and starts shipping AI work.

Who it's for: Leaders stuck at the 20% adoption ceiling. Execs who need the model, ICs who need the patterns, the wider org that needs the cultural setup.
Format: Three tracks (Leadership, Lab, Crowd). Pick one or stack all three.
Investment: Quoted in writing within 48 hours.
Next step: Book the Training intro

Three internal roles every AI-adopting org needs. Most programs train only the Crowd, hit the 20% ceiling, stall. Fix: train all three in sequence.

"Secret cyborg" lives here too. People use AI privately but won't share, because no one signaled it's safe to admit.

Role 1 · Leadership

Leadership

Execs who set strategy and allocate budget. Without them, training hits the ceiling.

Role 2 · Lab

Lab

A small builder team running experiments. Without them, no examples to teach from.

Role 3 · Crowd

Crowd

The 80% using AI daily. Without them, only power users benefit.

Track 1 · 2 sessions, 90 min each, plus async reading

Leadership (executive layer)

For execs setting AI strategy. Three-Horizon portfolio framing. Budget defense language. Eval oversight without becoming a bottleneck.

Track 2 · 4 sessions, 2 hours each, plus hands-on builds

Lab (internal builder team)

For your 5 to 10 builders. Prompt engineering for production. Eval setup (Braintrust or equivalent). Multi-model routing and cost control. Agent literacy: single-shot vs multi-step vs multi-agent.

Track 3 · 2 sessions, 60 min each, plus async references

Crowd (everyone else)

For ops, sales, CS, engineering. Daily-use patterns. Prompting for the use case, not the demo.

Generic AI training flatlines after the trainer leaves. This one lives in the knowledge base your team and your AI both work from.

Without · Most AI training

Generic and disposable

Prompt workshops disconnected from real workflows. Trainer leaves, team forgets. Vendor tutorials that lock you in.

With · What you get here

Tied to your workflows, kept by your team

Built on your actual use cases. References in the shared knowledge base. Adoption tracked at 30/60/90.

Me, an exec sponsor, one Lab lead. Live workshops, recordings, async. Reinforcement at 30/60/90.

Phase 1 · Week 1 · Diagnostic

Map current AI usage

Interview 6 to 10 across all three roles. Surface the secret cyborg. Pick highest-leverage Crowd workflows.

Phase 2 · Weeks 2 to 3 · Leadership track

Lock the strategy

Two exec sessions. Lock strategy, allocation, metrics. Signal it's safe to admit AI use.

Phase 3 · Weeks 3 to 6 · Lab track

Hands-on builds

Four sessions with builders. Real internal use cases. Eval framework stood up.

Phase 4 · Weeks 6 to 8 · Crowd track

Use-case workshops

Two sessions per team. Use-case prompting. Contribution path back to the knowledge base.

Phase 5 · 30/60/90 post-engagement

Reinforcement

Adoption review. Course corrections on what stuck.

End of engagement · What you get

Three tracks delivered

Adoption baseline measured. Lab can run future training. Crowd has references in the knowledge base. Leadership has the diagnostic to flag regressions.

+6 months · Clients report

The ceiling moves

Adoption pushes past the 20% ceiling and keeps climbing. Secret cyborg shrinks. Lab ships internal tools without outside help. New hires train through the OS.

What is AI workforce training based on Leadership-Lab-Crowd?

A 4 to 8 week program that trains three internal roles every AI-adopting org needs: Leadership (execs who signal safety and set strategy), Lab (a small builder team running experiments), and Crowd (the 80% using AI in daily work). Anchored on Ethan Mollick's Leadership-Lab-Crowd framework (Wharton, May 2025). Most programs train only the Crowd, hit the 20% adoption ceiling, and stall. The fix is training all three in sequence.

How much does AI workforce training cost?

4 to 8 weeks, across one to three tracks. Leadership track: 2 sessions, 90 min each, plus async reading. Lab track: 4 sessions, 2 hours each, plus hands-on builds. Crowd track: 2 sessions, 60 min each, plus async references. Scoped against team size and track mix. Quoted in writing within 48 hours of the discovery call.

Why does most AI training fail to break the 20% adoption ceiling?

Most programs train only the Crowd. The Leadership layer never signals that AI use is safe to admit, so the "secret cyborg" pattern dominates (people use AI privately but won't share). The Lab layer never produces internal examples, so the Crowd has nothing to copy. Training all three in sequence, starting with Leadership, breaks the ceiling.

Who is AI workforce training for?

Companies whose AI strategy is set but whose adoption has stalled. Execs who need a mental model. ICs who need hands-on patterns. Wider orgs who need the cultural setup. Mid-market service firms, roughly $5M to $200M+ ARR. Pairs with Fractional Head of AI Transformation engagements where adoption is the bottleneck.

Can we do just the Crowd track?

You can, but it underperforms. Leadership track first sets the safety signal. Without it, Crowd training teaches skills people are still nervous to use openly.

How many people can you train at once?

Crowd track scales. I've run 50-person workshops. Lab track stays small (5 to 10 builders). Leadership track is the exec layer, usually under 12.

Do we get materials we can reuse?

Yes. Everything goes into the shared knowledge base your team and your AI both work from, or your shared drive. You own the curriculum. New hires train on it without me.

Is this train-the-trainer?

Optional. Most clients add it to the Lab track so one or two internal leads can run future Crowd sessions.

What's your guarantee on this engagement?

Two guarantees. SKU guarantee: if the 60-day adoption re-measure shows no movement from baseline on the agreed metric, I re-run the diagnostic (one session) and ship a written course-correction memo at no additional cost. Umbrella guarantee on every engagement: a 14-day mutual exit. Either party can end the engagement inside the first 14 days. Days worked are billed at the agreed day rate. No further commitment.

The three tracks are the deliverable. These come with it.

Bonus 01

Recordings of all sessions, yours to keep

Every session recorded. For new-hire onboarding, refreshers, anyone who couldn't attend live. Training scales without re-engaging me.

Bonus 02

The Leadership-Lab-Crowd playbook

The framework documented for internal reuse. Diagnostics, exercises, talking tracks for the exec sponsor. Lab runs the next training cycle without me.

Bonus 03

4 weeks of office hours after the last session

Weekly drop-in office hours for the first four weeks post-engagement. Live questions, prompt review, workflow troubleshooting. Catches adoption regressions before they go structural.

Adoption gets re-measured at day 60. If the metric hasn't moved, the course correction is on me. That removes the "training disappeared in the org" risk from the buyer's pile.

AI Workforce Training guarantee

Adoption moves or I re-run the diagnostic

If the 60-day adoption re-measure shows no movement from baseline on the agreed metric, I re-run the diagnostic (one session) and ship a written course-correction memo at no additional cost.

Umbrella · Every engagement

14-day mutual exit

Every engagement carries a 14-day mutual exit. Either party can end the engagement inside the first 14 days. Days worked are billed at the agreed day rate. No further commitment.

Move past the ceiling

Move your team past the AI adoption ceiling.

Book the call. 30 minutes to diagnose where your team is on the Leadership-Lab-Crowd grid. 4 to 8 weeks.