About the Exercise
Project Threshold puts you in the seat of an industry leader navigating rapid AI adoption from 2026 to 2030. Over four rounds of escalating scenarios, you make real strategic decisions for your industry — with real trade-offs, immediate scoring, and cross-industry dynamics that reveal how interconnected the US economy actually is.
Not a Workshop
You make binding decisions with real consequences — not brainstorm ideas on sticky notes.
Not a Simulation
The goal is better questions, not computed answers. Reasoning quality matters more than numerical precision.
Not a Test
No scores are "good" or "bad." The value is in how your thinking changes across four rounds.
What Happens in the Room
Each round follows the same structure. The scenario changes, the stakes escalate, but the rhythm stays constant — so participants spend their energy on decisions, not figuring out the format.
Scenario Update
The facilitator reads what's changed in the economy — new AI capabilities entering the market, regulatory shifts, labor dynamics, competitive moves. The landscape you planned for last round may not exist anymore.
Private Intelligence
You receive a confidential card with information only your industry knows. A competitor's move. A regulatory signal. An internal constraint. This is yours alone — and it will shape your decision.
Individual Decision
You analyze your industry's position, weigh the trade-offs, and fill out a decision worksheet committing to one strategic move. There are no safe choices. Every option means giving something up.
Submission
Decision worksheets are collected. No revisions, no take-backs. This mirrors real strategic commitment — once resources are allocated, you live with the consequences.
Scoring
The facilitator evaluates each decision on three dimensions — Strategic Fit, Execution Risk, and Tail Risk — using a transparent banded system. You see exactly how your reasoning was assessed and can challenge the logic.
Cross-Industry Discussion
The centerpiece of the exercise. The full group compares strategies, and the spillovers emerge. The retail participant discovers that the logistics provider just automated the supply chain they depend on. This is where assumptions break.
This cycle repeats four times. Each round covers a different phase of the 2026–2030 AI adoption arc, with accumulating consequences from prior decisions.
The Four Rounds
Foundation
Everyone's optimistic. Copilot tools are arriving across the enterprise. How much do you bet on early adoption — and what do you risk if you're wrong?
Acceleration
Early adopters are pulling ahead. Regulators are waking up. Talent wars are heating up. Do you double down or hedge?
Reckoning
Productivity gains plateau. Labor displacement is front-page news. The bets you placed in Rounds 1 and 2 are now constraints you have to live with.
Normalization
AI is infrastructure now. Markets are repricing. The question isn't whether to adopt — it's whether your position is defensible for the next decade.
How Decisions Are Scored
Every decision is evaluated immediately on three dimensions. Scores are transparent — you see the reasoning, not just the number.
Strategic Fit
Does this decision align with your industry's fundamentals and the macro environment? Is the logic sound given what you know — and what you don't?
Execution Risk
Can your organization realistically pull this off in the timeframe? Do you have the talent, capital, and operational capability — or are you overcommitting?
Tail Risk
What's the catastrophic downside? Does this decision create asymmetric long-term liability — reputational, regulatory, or financial — that you can't walk back?
Each dimension is scored in bands — not on a precise numerical scale. The exercise deliberately avoids false precision. What matters is the quality of your reasoning, not the exact score.
What You Walk Away With
Cross-industry intuition
See how decisions in one industry cascade into others in ways that are invisible from inside a single company.
Stress-tested assumptions
Confront what you actually believe about AI timelines, competitive response, and regulation — then watch those beliefs get pressure-tested in real time.
Second-order clarity
Move past the obvious impacts — automation, cost cuts — to the downstream consequences that separate winners from losers over a 4-year horizon.
Peer perspectives
Eight hours of structured discussion with leaders who face analogous but distinct challenges across different parts of the economy.
No-regrets actions
Leave with a concrete list of strategic moves that are robust regardless of which AI adoption scenario actually plays out.
Who It's For
C-Suite Executives
CEOs, COOs, CTOs, and CFOs making AI investment decisions under genuine uncertainty.
Senior Strategy Leaders
Heads of strategy, corporate development, and strategic planning at large organizations.
Investment Professionals
Portfolio managers and managing directors evaluating AI-related risk and opportunity across industries.
Enterprise AI Decision-Makers
Anyone responsible for deciding where, when, and how to deploy AI at scale.
No AI technical expertise required. You bring industry knowledge and strategic judgment — the exercise provides the AI context.
The Day at a Glance
| Time | Activity | Duration |
|---|---|---|
| 8:30 AM | Arrival & Setup | 15 min |
| 8:45 AM | Welcome & Rules | 15 min |
| 9:00 AM | Practice Micro-Round | 10 min |
| 9:10 AM | Round 1: Foundation | 65 min |
| 10:15 AM | Break | 15 min |
| 10:30 AM | Round 2: Acceleration | 65 min |
| 11:35 AM | Lunch | 40 min |
| 12:15 PM | Round 3: Reckoning | 65 min |
| 1:20 PM | Break | 15 min |
| 1:35 PM | Round 4: Normalization | 65 min |
| 2:40 PM | Break | 10 min |
| 2:50 PM | Structured Debrief | 60 min |
| 3:50 PM | Wrap-Up & Close | 40 min |
The 60-minute debrief is protected time — it's where individual insights become collective intelligence and no-regrets actions take shape.
Why a Tabletop Exercise?
The format originated in military and government planning: gather decision-makers around a scenario, force real decisions under genuine uncertainty, and expose the gaps in your assumptions before they become failures in the field. Over the past two decades, the approach has migrated into corporate strategy — where the stakes are different but the underlying problem is the same. Project Threshold applies this methodology to the most consequential strategic question facing enterprises today: how AI adoption will reshape competitive dynamics across an interconnected economy.
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