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moatmri Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan. safe community 2026-05-31

MoatMRI — AI Disruption Pressure Analysis

Where does intelligence pressure break this system first?

When to Use This Skill

  • "Is my business at risk from AI? Where am I most exposed?"
  • "How would an AI-native startup take over my market?"
  • "What should I do in the next 90 days to defend against AI disruption?"
  • "I'm doing due diligence on [company] — what's their AI displacement risk?"
  • "Where does my competitive moat actually hold against AI pressure?"

How It Works

Step 1 — Gather Inputs

Ask if not provided:

  • Industry (e.g., "real estate", "community banking", "retail pharmacy", "law firm")
  • Entity type (e.g., "independent broker", "solo practitioner", "regional franchise")
  • Target name (optional — specific organization for named analysis)

Limitations

  • Produces strategic risk analysis, not audited market research or investment advice.
  • Depends on current company, market, regulatory, and competitive context supplied by the user or gathered from reliable sources.
  • Treats disruption scenarios as planning tools; scores should be revisited as new evidence appears.

Step 2 — 10-Vector Pressure Map

Score AI disruption pressure across exactly these 10 vectors (0–10):

# Vector What to Measure
1 labor_substitution Which roles/functions are directly automatable
2 customer_interface How AI changes how customers reach this entity
3 knowledge_commoditization Does AI commoditize the expertise this entity sells
4 pricing_pressure Does AI enable lower-cost competitors to undercut
5 supply_chain_automation Does AI change input costs or supplier relationships
6 data_moat Does this entity have proprietary data AI can't replicate
7 trust_relationship_moat How much does customer loyalty protect against displacement
8 distribution_channel_disruption Does AI create new channels that bypass this entity
9 regulatory_compliance_exposure Does AI alter the regulatory or liability landscape
10 decision_speed_gap Does AI accelerate decisions in ways that disadvantage this entity

For each vector produce: score, headline, near_term (12 months), far_term (3 years).

Aggregate risk score: mean of all 10 vectors. Flag any vector ≥ 7 as critical.

Step 3 — AI Front-Door Takeover Storyboard

6-step narrative of how an AI-native competitor displaces this entity:

  1. The entry point
  2. The wedge (first 10% of market)
  3. The acceleration (what makes it compound)
  4. The tipping point (when incumbent can't recover)
  5. The aftermath
  6. The survivor profile

Step 4 — 90-Day Counterstrike Plan

  • Track A (Days 0–30): Immediate defense — what to stop, what to protect
  • Track B (Days 31–60): Intelligence-layer build — data/relationships to fortify
  • Track C (Days 61–90): Offensive positioning — use AI pressure as competitive weapon

Best Practices

  • ✅ Score all 10 vectors before calculating aggregate — resist stopping at obvious ones
  • ✅ Keep the storyboard specific to industry/entity, not generic disruption narrative
  • ✅ Track C should be actionable within 90 days, not aspirational 3-year strategy
  • ❌ Don't conflate data_moat with trust_relationship_moat — they protect differently

Additional Resources