Investor Conversations: How to Talk About Your AI Strategy Without Hype

What Investors Are Actually Asking

When an investor asks about your AI strategy, they're really asking:

• "Is this defensible?" → Can someone else just add GPT to their product and catch up?
• "What are the margins?" → How much does AI cost you per customer?
• "Is this a feature or a company?" → Does AI justify a standalone business?
• "Do you understand the technology?" → Or are you just riding hype?

The Moat Question

Bad Answer

"We're building proprietary AI models."

Red flags: You can't outspend OpenAI. Foundation models are commoditizing.

Better Answer

"Our moat is structured context, not models. We've organized [domain] knowledge in a way that makes any AI dramatically more useful. This takes time to build and compounds with usage."

Best Answer (with proof)

"Here's what we've built:
- 500k structured records with relationship data
- 2 years of user interaction patterns
- Domain-specific retrieval that GPT can't replicate

Result: 40% better task completion vs. vanilla GPT.
This advantage grows as we add more data."

The Margin Question

Bad Answer

"We're focused on growth, we'll optimize margins later."

Red flag: You don't understand your unit economics.

Better Answer

"Our AI costs:
- $0.02 per user interaction average
- ~15% of revenue at current pricing
- We've reduced this 60% in 6 months through:
  - Better context retrieval (fewer tokens)
  - Caching common queries
  - Model routing (use cheaper models where possible)

Path to 5% of revenue within 18 months."

The Defensibility Timeline

What VCs Worry About

// The nightmare scenario
Month 0: You launch AI feature
Month 3: Competitor sees it working
Month 6: Competitor launches their version
Month 9: They have same capabilities, bigger distribution

// You lost.

How to Address It

"Our lead time compounds:

Year 1: We have X structured records, competitor has 0
Year 2: We have 5X records + 1 year of learning, they have X
Year 3: We have 10X records + insights, they're still catching up

The data advantage accelerates. We're always 18-24 months ahead."

Questions You Should Expect

"What happens when AI gets cheaper?"

Good answer: "Great for us. Our value is in the context layer, not the inference. Cheaper AI makes our structured context more valuable, not less."

"What if OpenAI/Google builds this?"

Good answer: "They're building horizontal platforms. We're building vertical depth in [domain]. They can't have deep context in every industry. We're the context layer for [specific market]."

"How do you know AI isn't just a feature?"

Good answer: "The feature question is about value creation vs. value capture. We capture value through [sticky data layer/network effects/workflow integration], not just the AI feature itself."

Metrics That Matter

// Metrics to show
{
  "ai_usage_retention": "85% still using after 30 days",
  "context_depth_per_user": "Growing 20% MoM",
  "task_completion_rate": "40% better than alternative",
  "cost_trend": "Down 60% in 6 months",
  "user_time_saved": "8 hours/user/week"
}

// Metrics that don't matter as much
{
  "total_ai_queries": "Vanity, doesn't show value",
  "model_accuracy": "Hard to verify, sounds like hype"
}

Red Flags to Avoid

• "We're building AGI" → No you're not.
• "Our AI is better than GPT-4" → Extraordinary claims require extraordinary evidence.
• "AI is our entire strategy" → What's the actual product?
• "We can't share our approach" → Sounds like you don't have one.
• Heavy jargon → "RAG pipeline with multi-modal embeddings" sounds like hiding behind complexity.

The One-Liner

End your AI discussion with a crisp summary:

"We're building structured context for [domain].
AI models come and go—context compounds.
Today's advantage: [X records, Y users, Z insights].
In 3 years: [defensible position statement]."

What Investors Want to Hear

1. You understand the technology—enough to know what's yours vs. commodity.
2. You understand the economics—AI costs, margin trajectory, pricing strategy.
3. You have a real moat—not "we use AI" but "we have defensible context."
4. You're building for durability—not just the current AI hype cycle.

Talk about AI like you understand it, not like you worship it. That's what separates fundable companies from noise.