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Pre-Exercise Diagnostic Survey

Pre-Exercise Diagnostic Survey#

Administer 1-2 Weeks Before Exercise

Purpose: Capture baseline assumptions from participants. Use results to (a) identify outliers and prepare for debate, (b) inform debrief by contrasting initial assumptions with post-exercise thinking, (c) calibrate individual participants during exercise based on aggregate results.

Format: 8-question survey, 15-20 min completion time Scoring: Multiple choice; each question has a rubric Participant Model: Individual industry representatives respond individually (not as teams)

Question 1: Speed of Enterprise AI Adoption#

Question Text: "By 2028 (2 years from now), what percentage of large enterprises (>$1B revenue) will have deployed at least one AI copilot tool into their primary business processes?"

Answer Options:

  • A) Less than 25% (slow adoption)
  • B) 25-50% (moderate adoption)
  • C) 50-75% (rapid adoption)
  • D) More than 75% (ubiquitous adoption)

Scoring Rubric:

  • A = Pessimistic on speed: Participant expects significant adoption friction, regulatory constraints, or organizational resistance.
  • B = Moderate: Steady but not explosive adoption curve.
  • C = Rapid: Majority of large enterprises move quickly.
  • D = Ubiquitous: AI copilots become standard in most enterprises within 2 years.

Facilitator Guidance:

  • If >40% select A/B, expect skeptical participant behavior. Prepare for debate on plausibility.
  • If >40% select D, expect overconfidence. Use injects to surface execution barriers.
  • Outliers (A vs D) should be flagged for debrief discussion.

Question 2: Labor Displacement Magnitude (By 2029)#

Question Text: "By 2029 (3 years from now), approximately how many jobs in the US will have been structurally displaced by AI (meaning role eliminated, not retrained)?"

Answer Options:

  • A) Less than 500,000 jobs (minimal displacement)
  • B) 500,000 - 2 million jobs (moderate displacement)
  • C) 2-5 million jobs (significant displacement)
  • D) More than 5 million jobs (major structural displacement)

Scoring Rubric:

  • A = Optimistic on labor: Most workers will retrain into new roles.
  • B = Moderate: Some displacement but manageable transition.
  • C = Pessimistic: Significant net job loss. Retraining feasibility questioned.
  • D = Very pessimistic: Structural unemployment or major workforce dislocation.

Facilitator Guidance:

  • If cohort splits between A/B and C/D, expect tension in discussions about labor policy.
  • If cohort heavily selects C/D, expect aggressive labor protection proposals.
  • This question signals how participants will approach workforce transition strategies.

Question 3: Regulatory Posture (By 2028)#

Question Text: "By 2028, which best describes the regulatory environment for AI in the US?"

Answer Options:

  • A) Light-touch regulation: Industry self-regulation dominates; minimal binding government rules.
  • B) Sector-specific light regulation: Industry regulators (FDA, SEC, EEOC, state bar associations) issue guidance; enforcement is light.
  • C) Moderate federal regulation: Congress passes binding rules on transparency, explainability, audit rights; enforcement is increasing.
  • D) Strict regulation: Congress passes restrictive rules (liability caps, deployment restrictions, mandatory human oversight); enforcement is aggressive.

Scoring Rubric:

  • A = Pro-innovation: Low regulatory barriers; firms can move fast.
  • B = Cautious: Piecemeal guidance but no major binding rules yet.
  • C = Balanced: Rules will be established and enforced moderately.
  • D = Restrictive: Significant regulatory constraint on deployment.

Facilitator Guidance:

  • Project Threshold default assumes B->C transition (light guidance in early rounds, binding rules in later rounds).
  • If cohort clusters on A, they may be surprised by regulatory injects.
  • If cohort clusters on D, regulatory injects will feel realistic to them.

Question 4: Value Capture by Industry (Rank Top 3)#

Question Text: "Which three industries will capture the most economic value (earnings uplift, margin expansion, market share gain) from AI between 2026-2030? Rank them 1 (most), 2, 3."

Answer Options: (Select 3 from this list and rank)

  • Retail
  • CPG
  • Healthcare Provider
  • Healthcare Payer
  • Finance
  • Consulting
  • Law
  • Manufacturing
  • Logistics
  • Big Tech
  • B2B/B2C SaaS

Scoring Rubric (Aggregate):

  • Industries consistently ranked top 3: Finance, Big Tech, SaaS (usually expected winners)
  • Industries sometimes ranked: Consulting, Healthcare Payer, Logistics (emerging value capture stories)
  • Industries rarely ranked: Healthcare Provider, Manufacturing, CPG, Law, Retail (usually expected laggards due to regulatory/complexity/data constraints)
  • Outliers: Anyone ranking Healthcare Provider, Law, or Manufacturing as top 3 has a contrarian thesis

Facilitator Guidance:

  • If your industry representative is from a lower-ranked industry, they may rank their own industry higher. That's fine; creates ownership during exercise.
  • If cohort overwhelmingly selects same top 3, you have consensus on winners. Use that in debrief: "Everyone thinks Finance & Big Tech will win. What happens to the others?"
  • Outliers with idiosyncratic rankings should be probed: "You rank Law as #2. Why? What's your thesis?"
  • Compare rankings between related industries: Did anyone rank Consulting higher than Finance? Healthcare Payer higher than Provider?

Question 5: Regulatory Risk in Your Industry (Self-Assessed)#

Question Text (Asked by Industry): "In your assigned industry [INDUSTRY], how much regulatory risk do you foresee from AI deployment between 2026-2030?"

Options:

  • A) Very low risk: Regulation will not meaningfully constrain our AI strategy.
  • B) Low-to-moderate risk: Regulation may require compliance investments, but won't change our core strategy.
  • C) Moderate-to-high risk: Regulation could force us to pivot our strategy or slow deployment.
  • D) Very high risk: Regulatory restriction could prevent our AI strategy from succeeding.

Scoring Rubric:

  • A = Confident industry: Participant believes their industry has regulatory tailwinds.
  • B = Cautious: Compliance costs but manageable.
  • C = Wary: Real regulatory risk; strategy pivots likely.
  • D = Defensive: Regulation is a fundamental threat.

Typical Risk Profiles by Industry:

  • Healthcare Provider: 70-80% select C/D (clinical AI, FDA approval, physician liability)
  • Healthcare Payer: 60-70% select C/D (algorithmic coverage decisions, state insurance oversight)
  • Law: 60-70% select C/D (bar rules, malpractice liability, unauthorized practice concerns)
  • Finance: 50-60% select C/D (regulatory bifurcation, algorithmic fairness audits)
  • Consulting: 30-40% select C/D (client data handling, professional licensing)
  • Big Tech: 40-50% select C/D (antitrust, data privacy, content moderation)
  • B2B/B2C SaaS: 30-40% select C/D (data privacy, contractual liability)
  • Retail: 20-30% select C/D (labor risk more than regulatory)
  • CPG: 20-30% select C/D (consumer data privacy)
  • Manufacturing: 25-35% select C/D (safety regulations, OT system compliance)
  • Logistics: 20-30% select C/D (safety, autonomous vehicle regulation)

Facilitator Guidance:

  • Healthcare Provider and Law representatives will likely select C/D. That's appropriate; use it to frame decisions.
  • If a Healthcare Provider representative selects A/B, they're either optimistic or not thinking deeply. Prompt them: "FDA approval timelines are 12+ months. How does that affect your deployment timeline?"
  • Industry-specific outliers are interesting. If a Big Tech representative selects B while others in cohort select C/D, that person has a specific view worth probing.

Question 6: Market Concentration Trend#

Question Text: "By 2030, will AI lead to greater market concentration (fewer, larger players) or market decentralization (more competition from new AI-native entrants)?"

Options:

  • A) Significant decentralization: AI tools will be so widely available that new entrants can compete with incumbents. Market share will disperse.
  • B) Slight decentralization: New entrants will emerge, but incumbents will retain most share.
  • C) Stable concentration: Market structure will remain roughly as it is today.
  • D) Increased concentration: Large, well-capitalized incumbents will pull away. Mid-market players will consolidate or exit.

Scoring Rubric:

  • A = Optimistic on disruption: Participant believes AI democratizes competition. Incumbents are vulnerable.
  • B = Slightly optimistic: Some new entrants but incumbents retain advantage.
  • C = Neutral: No major shift in market structure.
  • D = Pessimistic on disruption: Participant believes AI reinforces incumbent advantage.

Distribution Benchmarks:

  • 10% select A
  • 25% select B
  • 20% select C
  • 45% select D

Facilitator Guidance:

  • Majority will select D (consolidation). This is the Project Threshold default.
  • Anyone selecting A/B is betting on disruption. This person may be a VC investor or entrepreneur skeptical of incumbents.
  • Use this question to prime M&A discussions in the exercise. Expect participants to consider acquisitions by Round 3-4 if they're trailing.

Question 7: Tail Risk / Black Swan Event#

Question Text: "What's the event you worry about most between 2026-2030? (Select one)"

Options:

  • A) Major AI system failure (misdiagnosis, trading error, autonomous vehicle crash) causing significant harm and regulatory backlash.
  • B) Synthetic media / deepfake incident undermining trust in information and institutions.
  • C) AI-driven market manipulation or systemic financial risk.
  • D) Severe labor dislocation and political backlash forcing rapid regulatory reversal.
  • E) None of the above; I think tail risks are overstated.

Scoring Rubric (Aggregate):

  • Count distribution of tail risk concerns.
  • A/B/C/D: Participant has identified a specific systemic risk.
  • E: Participant is risk-neutral or dismissive of tail risks.

Distribution Benchmarks:

  • 25% select A (major incident)
  • 20% select B (deepfakes)
  • 20% select C (financial manipulation)
  • 25% select D (labor dislocation)
  • 10% select E (overstated)

Facilitator Guidance:

  • If cohort heavily selects A/B/C, they're primed for crisis injects. Use injects to surface their concerns realistically.
  • If cohort heavily selects D (labor), frame debrief around policy responses and stakeholder management.
  • Anyone selecting E is an optimist. They may be surprised by injects. Use that surprise as a teaching moment.
  • Use this question to foreshadow injects: "Several of you are worried about deepfakes. That will come up in Round 3."

Question 8: Most Important Strategic Question (Open-Ended)#

Question Text: "What's the single most important strategic question your organization is grappling with in AI? (100 words max)"

Examples of Good Answers:

  • "How do we move fast enough to keep up with larger competitors while managing execution and governance risks?"
  • "How do we balance AI-driven efficiency with labor protection and brand reputation?"
  • "How do we navigate regulatory uncertainty while committing capital to long-term AI investments?"
  • "How do we compete with AI-native startups that have no legacy systems or embedded organizational constraints?"
  • "How do we preserve our junior talent pipeline when AI can perform 60-70% of entry-level work?" (Consulting/Law specific)
  • "How do we transition our billable hour model without destroying revenue during the transition?" (Law specific)

Facilitator Guidance:

  • Read all open-ended responses before the exercise.
  • Identify common themes. If multiple participants mention "execution risk," that's a signal the cohort is worried about capability constraints.
  • Look for outlier concerns. If one person mentions "AI-driven market manipulation as systemic risk" and no one else does, that person is flagged for systemic risk concern.
  • Use these responses to personalize injects. If cohort is worried about execution, create injects that test execution capability.
  • In debrief, reference these responses: "Earlier, you said your biggest concern was execution risk. Did the exercise validate that? Did you find your execution assumptions too optimistic?"

Survey Administration Guidance#

When to Administer:

  • 1-2 weeks before exercise
  • Digital form preferred (Google Forms, Qualtrics) for easy aggregation
  • Paper forms acceptable if digital infrastructure unavailable
  • Completion time: 15-20 minutes
  • Request brief written responses for Q8 (open-ended)

How to Analyze Results:

  1. Aggregate Results (5 min): Create summary showing distribution of answers to Q1-Q7. Example output:

    Q1 (Adoption Speed): A: 10%, B: 30%, C: 40%, D: 20%
Q3 (Regulatory Posture): A: 8%, B: 32%, C: 42%, D: 18%
Q6 (Concentration): A: 12%, B: 28%, C: 18%, D: 42%

  2. Identify Outliers (10 min): Note individuals with idiosyncratic responses:

    • "John (Finance) selected very pessimistic on adoption (A) but optimistic on labor (A). That's coherent: slow adoption = less displacement."
    • "Sarah (Consulting) selected pro-disruption (A) on Q6 but very pessimistic on regulation (D). She thinks regulation will be so restrictive that new entrants can't compete anyway."

  3. Thematic Analysis of Q8 (10 min): Group open-ended responses by theme:

    • "Execution & Capability Risk" (mentioned by 5 participants)
    • "Labor & Workforce Transition" (mentioned by 6 participants)
    • "Regulatory Uncertainty" (mentioned by 4 participants)
    • "Business Model Disruption" (mentioned by 3 participants — especially Consulting, Law)
    • "Market Consolidation Pressure" (mentioned by 3 participants)

How to Use Results During Exercise:

  1. Before Exercise Starts:

    • Present 1-minute summary of aggregate results: "Most of you expect rapid adoption and increased concentration. A few of you are more pessimistic on regulation."
    • Call out themes from Q8: "Several of you flagged execution risk as your biggest concern. We'll test that in the exercise."

  2. During Exercise:

    • Reference baseline assumptions when adjudicating: "Your decision assumes light-touch regulation, which is consistent with your Q3 answer (A). But the scenario is modeling binding regulation by Round 3. That assumption is being challenged."
    • Use outliers to fuel debates: "John selected very pessimistic adoption. When competitors announce rapid deployments, are you still skeptical? What would change your view?"

  3. During Debrief:

    • Compare initial assumptions to post-exercise views: "Before the exercise, 40% of you selected C (rapid adoption). After seeing injects and competitive pressure, do you still think adoption will be that fast? How did the scenario challenge your assumptions?"
    • Highlight learning: "You were right to worry about labor dislocation (Q2). The scenario bore that out. Your concern was prescient. Now, what do you actually do about it in your real organization?"

Document Version: Project Threshold V7.4 — Pre-Exercise Diagnostic Survey Last Updated: March 2026 Format: Single 8-question survey; V7.4 eleven-industry configuration (5-11 participants + 1-2 facilitators), individual participant model