Round 2: Acceleration#

Part of the Project Threshold Tabletop Exercise V7.4 — Consolidated Round Materials

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Round 2: ACCELERATION#

6–18 Months (~August 2026 – August 2027)#

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A. ROUND OVERVIEW#

Twelve months have passed. AI momentum is visible now in earnings, employment data, and market valuations. The bifurcation between early adopters and laggards has accelerated sharply. Agentic systems are moving from lab demo to limited production. Autonomous trading, AI-assisted hiring, and autonomous logistics are beginning to show visible economic impact. The regulatory environment is hardening. Labor unrest is mounting. This round tests whether each industry participant's Round 1 decisions deliver returns or backfire.

Time Period: 6–18 months (August 2026 – August 2027) Key Theme: Acceleration and visible differentiation between winners and losers Macro Scenario: Agentic AI at 60% autonomous trading; AI recruitment filtering 80% of applications; autonomous logistics at 30% of long-haul routes; back-office unemployment at 8%; AI Accountability Act advancing; deepfake fraud $3B; Nasdaq down 18% from highs; market volatility increasing.

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B. SITUATION UPDATE#

(To be read aloud by facilitator at round open.)

Twelve months have passed. The AI momentum is unmistakable in earnings, employment data, and market valuations. The bifurcation that emerged in Round 1 has accelerated sharply.

Model Capabilities & Competitive Landscape: Frontier labs have released new model generations with meaningfully improved reasoning, multi-modal capabilities, and latency suitable for real-time interaction. Code generation is now reliable enough that junior developer productivity has visibly increased. Agentic systems (AI that can autonomously execute multi-step tasks with periodic human validation) are moving from lab demo to limited production in specialized domains: data analysis, customer service, supply chain optimization, autonomous trading at 60% capability. A notable open-source release has narrowed the capability gap with frontier models for many applications, triggering competitive price pressure and commoditization. The conversation has shifted from "Will AI be impactful?" to "Who will capture the value?"

Enterprise Adoption & Financial Results: Earnings season (Q2-Q3 2027) reveals stark divergence. Large, well-capitalized enterprises that deployed AI in Round 1 are reporting measurable financial benefits: productivity gains of 15-25%, margin expansion of 100-200 bps in some cases. Software companies and financial institutions are leading; they are guiding higher FY2027 earnings driven explicitly by AI productivity. However, a subset of enterprises—those that deployed AI without adequate change management or governance—are reporting integration failures, productivity gains that failed to materialize, and writedowns of AI-related investments. The divergence is driving a "winner-take-most" dynamic: capital and talent are flowing to proven AI adopters, while laggards are struggling to catch up.

Labor Market Transformation: The labor market is showing visible stress. Certain occupational categories—data entry, junior analysis, routine coding, claims processing, customer service agents—are declining in headcount. Unemployment remains around 4% in aggregate, but job displacement is concentrated in specific geographies (back-office unemployment now at 8%) and demographics (less-educated workers, those in routine cognitive roles). Union activity has intensified: strikes and organizing campaigns have occurred at two major tech companies and one large consulting firm, explicitly around "AI and jobs." Calls for government support (retraining, wage insurance) are increasing from labor groups and progressive lawmakers. Three states (California, New York, Washington) have begun AI-era workforce transition planning. Consumer advocacy groups are launching campaigns against "AI layoffs."

Valuation & Capital Markets: AI-beneficiary stocks have continued to rally, but more selectively. Investors are increasingly discriminating between proven winners (cloud providers, large enterprise software, financial services companies with AI deployment success) and speculative plays. Mega-cap tech companies have hit valuation multiples unseen since the dot-com era. Venture capital is consolidating: mega-funds are leading large Series B/C rounds, while smaller VC firms are struggling to raise capital. The "hot" part of the venture market is now "AI adoption enablers" (consulting, integration, training, change management), not pure model or data companies. Nasdaq is down 18% from highs due to profit-taking and growing concerns about profitability timelines.

Regulatory Landscape Crystallizing: Regulatory certainty is increasing. The SEC has finalized guidance on AI disclosure and risk management. The FDA has finalized clinical AI guidance; several healthcare systems have deployed diagnostics under these guidelines. The "AI Accountability Act" is advancing in Congress—it would require explainability, bias auditing, and third-party audit trails for AI systems used in high-stakes decisions. The EU's AI Act is now in enforcement phase, creating compliance costs and precedent-setting litigation. State regulations are proliferating. Notably, no major federal labor-specific AI legislation has passed, but several proposals are in Congressional committees with bipartisan interest.

Fraud & Security Threats: Deepfake fraud has emerged as a significant threat. The first coordinated deepfake fraud ring was detected, targeting financial institutions and retail companies. Losses to deepfake fraud are estimated at $3B globally in 2027. Regulatory and law enforcement response is intensifying. Authentication technologies (digital signatures, blockchain, biometric verification) are becoming a growth market, but adoption lags behind the problem. Media coverage is sensational, amplifying public anxiety about AI-generated disinformation.

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B1. AI ADOPTION ARC DISTRIBUTION#

Facilitator Note: Distribute Phase 2 (Acceleration) from AI Adoption Arcs to each participant. This provides each industry's updated AI adoption trajectory based on Round 1 decisions and macro developments.

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C. CORE INJECTS (2-3 Maximum)#

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R2-01: Regulatory Backlash#

Classification: Regulatory Signal / Enforcement Action Time: Opening (start of round)

Narrative: Three concurrent regulatory actions land on participants simultaneously. The SEC launches trading audits on AI-driven autonomous trading systems, questioning risk controls and backtesting methodologies. The FDA delays approvals for two AI diagnostic systems, citing inadequate real-world validation and bias testing. A coalition of state attorneys general announce coordinated enforcement actions against financial institutions using AI credit scoring systems without adequate bias auditing. The message is unmistakable: regulators are shifting from "guidance" to "enforcement." Healthcare Provider, Healthcare Payer, and Finance participants face immediate cost pressure and execution delays. Compliance budgets double or triple. The window for aggressive, loosely-governed AI deployment has closed.

Ambiguity/Unknowns:

• How severe will enforcement actions be? Fines? Forced system shutdowns?
• Will enforcement slow or accelerate AI innovation in regulated industries?

Industry Impact:

Facilitator Guidance:

• SEC trading audits will force firms to document model performance, backtesting, and stress-testing methodologies. Several firms will be forced to reduce AI trading exposure.
• FDA delays will set back clinical AI deployments by 6-12 months in some cases.
• State enforcement actions will trigger a wave of bias audits and remediation efforts across financial services.
• Compliance costs will increase 200-300% for firms that aggressively deployed AI without governance. This is a major penalty for Round 1 aggressive strategies.
• Firms that built proactive governance in Round 1 will face minimal friction; they will be positioned as "responsible actors" and gain competitive advantage over penalized peers.

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R2-02: Market Stress Event#

Classification: Market Signal / Macro Shock Time: Mid-round (Day 1 afternoon or Day 2 morning)

Narrative: A "flash crash" event occurs in early August 2027, triggered by a cascade of AI trading systems executing simultaneously in response to a volatility spike. The crash itself is brief (30-45 minutes), but the reputational damage is significant. Nasdaq drops 4% intraday; circuit breakers halt trading twice. Regulators issue emergency statements questioning the safety of autonomous trading systems. Several pension funds and asset managers announce they are reviewing their AI trading exposure. The Nasdaq finishes the trading season down 18% from July highs. Investor confidence in AI-driven market infrastructure is shaken. Market volatility increases significantly. Credit markets tighten slightly. This is the first visible "black swan" event attributed to AI systems, and it triggers a broad reassessment of AI risk across the board.

Ambiguity/Unknowns:

• How quickly will market confidence in AI systems recover?
• Will this trigger broader regulatory constraints on autonomous trading?

Industry Impact:

Facilitator Guidance:

• The flash crash is not a catastrophic failure—AI systems recovered gracefully and circuit breakers worked as designed. But the psychological impact is large.
• Finance participants that have AI trading systems will see immediate margin pressure and forced risk reductions.
• Nasdaq down 18% from highs signals broader profit-taking and growth concerns. Valuations may compress across the board, not just AI-heavy industries.
• This is a "black swan" that was theoretically predictable but practically ignored by risk managers. It raises questions about whether other AI systems have similar hidden risks.
• Consulting participants will see demand surge for "AI risk management consulting." This is a new revenue stream.

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R2-03: Labor and Social Backlash#

Classification: Labor/Social Signal / Union Action Time: Mid-round (concurrent with or just before R2-02)

Narrative: Workers at a large technology company strike over AI-related grievances regarding invasive monitoring, speed-up requirements, and job security threats. The strike settles after 3 weeks with: (1) Transparency on AI-assisted tasks; (2) Human oversight requirements for employment decisions; (3) $10M retraining fund. The settlement becomes a precedent. Three other companies face union organizing campaigns explicitly around AI. Progressive politicians call for federal AI labor standards; business groups counter that overregulation will stifle productivity gains. Consumer advocacy groups launch campaigns against "AI layoffs." Multiple newspapers run investigative stories on AI-driven job displacement in specific communities. Public sentiment on AI shifts noticeably. Retail workers, call-center workers, and back-office workers are organizing.

Ambiguity/Unknowns:

• Will the settlement become a template for other negotiations?
• Will political pressure for federal AI labor standards build into binding law?

Industry Impact:

Facilitator Guidance:

• The struck company sees modest productivity gains (5-8%) vs. projected 20%+; transparency requirements add friction.
• Worker retention improves (20-30% higher in retraining cohorts vs. layoff scenarios).
• Other companies are quietly executing AI headcount reductions via "voluntary severance" before labor standards solidify.
• Firms that transparently manage workforce transitions will avoid union action and maintain brand reputation; firms that execute silent headcount reductions will face backlash.
• This is a major penalty for Round 1 aggressive headcount reduction strategies. Firms that chose aggressive optimization will now face union action and retraining costs.
• Firms that chose transparent transition or "AI + Human" will be positioned as responsible actors and gain reputational advantage.

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D. OPTIONAL INJECTS (Use Only If Table Finishes Early)#

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R2-OPT-01: Deepfake Fraud Ring#

Classification: Security / Fraud / Regulatory Time: Mid-round to late round (Day 2 morning or afternoon)

Narrative: A sophisticated deepfake fraud ring is detected. The ring used AI-generated video and audio to impersonate C-suite executives and initiate fraudulent wire transfers totaling $85M across multiple financial institutions and retail companies. One victim company—a major financial institution—suffered a $20M loss before fraud was detected. The incident makes international headlines: "AI Deepfakes Used in $85M Fraud Ring." Law enforcement launches investigation. Multiple companies announce emergency reviews of authentication and transaction controls. Regulatory bodies issue urgent guidance on deepfake detection and authentication. Media speculation runs wild: "Is video evidence unreliable now?" "Can we trust any digital communication?"

Ambiguity/Unknowns:

• How widespread is deepfake fraud risk?
• What authentication technologies will be effective?

Industry Impact:

Facilitator Guidance:

• This incident is not an existential threat to AI or digital communications, but it is a major psychological shock.
• Companies with robust transaction controls and human oversight will survive with minimal damage.
• Companies that relied on AI authentication alone will face significant reputational damage and fraud losses.
• Authentication technology and fraud detection consulting become high-growth markets.

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E. FACILITATOR MARKET SHOCK (3 minutes)#

The facilitator imposes external Market Shocks on 2-3 industries. This replaces the former IC Constraint Imposition — the facilitator acts as the market, not a participant role.

Facilitator Script (Read Aloud):

"The market doesn't wait for consensus. Based on macro developments — regulatory actions, competitive moves, and market dynamics — the following industries are facing an external shock this round."

Procedure:

Constraint Menu (select one per targeted industry; cannot impose same type on multiple industries):

1. Regulatory Halt: Regulators have announced a review of AI deployments in this industry. All new AI projects are frozen for this round — no new pilots, no expansion to new sites, no go-live on tools still in testing. The participant's strategy must work within their current AI footprint.

2. Labor Cost Surge: Union negotiations, wage competition, or mandatory retraining obligations have driven labor costs sharply higher — enough to compress margins and force trade-offs. Any strategy that depends on labor-intensive rollout now costs significantly more. The participant must narrow scope, slow timelines, or offset the pressure.

3. Capital Tightening: Market conditions have significantly reduced available capital. The board has pulled back discretionary spending authorization. Capital-intensive strategies (large infrastructure investments, acquisitions, multi-site expansions) are constrained. The participant must go capital-light or justify a smaller, more focused investment.

4. Reputational Pressure: Public backlash — workforce displacement, algorithmic fairness, or customer trust erosion — has forced a defensive posture. Stakeholders expect visible action. Aggressive AI expansion without a credible "responsible transition" component will be scored harshly. The participant must address the backlash in their strategy.

5. Competitive Response: A major competitor has used AI to aggressively undercut pricing, poach customers, or leapfrog product capability. The threat is immediate and material. Purely internal-facing or long-horizon strategies that ignore the near-term competitive threat are risky. The participant must defend their position.

6. Litigation Risk: The industry faces active or imminent AI-related litigation — algorithmic bias, labor displacement, IP disputes, or product liability. Legal exposure is material and uncertain. Any strategy that expands litigation surface area carries additional risk. The participant should reflect the legal overhang in their reasoning.

Key difference from Industry Health Signal constraints: Market Shocks can target ANY industry — including well-performing ones. Health Signal constraints are mechanical consequences of poor cumulative scores. Market Shocks reflect external forces that hit regardless of performance.

Facilitator Guidance:

• Prepare constraint selections before the round begins — do not deliberate in front of participants.
• Target industries where constraints create the most interesting strategic tension, not just the weakest performers.
• Constraints interact with Round 1 decisions: an industry that chose "aggressive" strategy and then receives a constraint will face severe pressure. An industry that chose "prudent" strategy will be better positioned to absorb it.
• Announce quickly and move on. This is a 3-minute mechanic, not a deliberation.

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E1. INDUSTRY HEALTH SIGNALS — ROUND 2#

Facilitator Note: After scoring Round 1 decisions and applying fallbacks, announce Industry Health conditions for each industry. This is the first time conditions are announced.

Procedure:

1. Calculate cumulative aggregate score for each industry (Round 1 scores only at this point)
2. Look up condition in the table: Surge (+15+), Tailwind (+6 to +14), Steady (-5 to +5), Headwind (-6 to -14), Crisis (-15 or worse)
3. Announce condition for each industry (~2 minutes)
4. For Headwind industries: impose one additional constraint from the constraint menu
5. For Crisis industries: impose two constraints; inform participant their primary decision must include a defensive component

Note: Facilitator Market Shock constraints from Section E are separate from Health Signal constraints. An industry could receive both a Market Shock constraint AND a Health Signal constraint if their Round 1 performance was poor AND the facilitator also targeted them.

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E2. COLLECTIVE BONUS (Optional, within Cross-Industry Discussion)#

Facilitator Script (Read Aloud):

"Does anyone want to recognize an especially strong strategy this round, or flag one that seems particularly risky?"

Procedure:

Scoring:

• If 3+ participants agree an industry has a strong strategy: +2 cumulative score bonus
• If 3+ participants agree an industry has a risky strategy: -2 cumulative score penalty
• Maximum one +2 and one -2 per round
• If no consensus or no one speaks up, no bonus applied

Facilitator Guidance:

• The Collective Bonus creates lightweight peer accountability without forcing participation.
• Encourage participants to cite specific reasoning if they do nominate.
• Announce results openly — nominations are public, not anonymous.
• In Round 2, nominations should reflect how well participants adapted to new information from Round 1 results and this round's injects.

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F. PRIVATE CARD DISTRIBUTION#

Facilitator Note: Distribute the appropriate Private Information Card from Private Cards to each participant face-down. Round 2 uses Private Card 2. Card 2 is unique per industry—each participant receives information specific to their industry. Private cards contain updated industry-specific data, financial metrics, competitive intelligence, or internal developments relevant to each participant's decisions in this round. These cards are intentionally asymmetric—participants have incomplete information about other industries' actual performance from Round 1, forcing reliance on public injects and cross-industry inference.

Private cards are used in Rounds 1-3 only. Round 4 operates on symmetric information.

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G. INDIVIDUAL INDUSTRY DECISION SUBMISSION REQUIREMENTS — V7.4#

Each industry participant submits:

1. Industry Decision (1 REQUIRED):
   • Each participant must submit an explicit decision for their industry per round.
   • Use banded framework: avoid invented precision, use directional language.
   • Address how you're responding to any Market Shock constraints or Industry Health Signal constraints imposed in this round.

Submission Format:

[INDUSTRY NAME] — ROUND 2 DECISION

CONSTRAINT IMPOSED: [Name of constraint, if any — Market Shock or Health Signal]
Response to Constraint:
  [How are you adapting strategy in response?]

DECISION TITLE: [Title]

RATIONALE:
  [Why this choice? How does it respond to R2 injects and constraints?]

BANDED ASSESSMENT:
  - Spend/Commitment: [Band]
  - Time-to-Impact: [Band]
  - Execution Complexity: [Band]
  - Dependency: [Band]
  - Scale: [Band]

EXPECTED OUTCOME:
  [What do you expect in Round 3?]

INDUSTRY REPRESENTATIVE: [Name]

Time to Submit: 18 minutes after injects and Market Shock constraints are announced.

Key Notes:

• One decision per participant per round.
• Banded framework prevents false precision and focuses discussion on real trade-offs.
• Address constraint response explicitly if one is imposed on your industry.

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H. INDUSTRY HEALTH UPDATE — ROUND 2#

Round 2 Industry Health conditions will be updated at the start of Round 3 based on cumulative scores (R1 + R2), including any Collective Bonus adjustments (+2/-2 per round). Strong Round 2 performance can shift an industry from Steady to Tailwind; poor performance can drop an industry into Headwind.

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End of Round 2 Materials