AI is the product.
Your moat is built around AI. Your category exists because AI made it possible. The company has no version of itself that survives without frontier model access.
Examples: Anthropic, OpenAI, Cursor, Perplexity, Glean.
Pick this only if AI being commoditized would end the company. If AI is your accelerant, you are a Compounder, not a Native.
Existing moat, AI as multiplier.
You have a real business that pre-dated the AI wave. AI is the leverage, not the moat. The People Ops question is whether the existing institution can absorb AI-native operating norms before a Native challenger erodes the moat.
Examples: Google, Adobe, Salesforce, Atlassian, Microsoft.
Pick this only if you can name your pre-AI moat in one sentence. If you can't, you are a Spectator hoping AI gives you one.
Regulated, deliberate, safety-first.
You operate in a regime where the cost of being wrong is asymmetric. Your AI adoption is correctly slow. Your People Ops job is to build AI-era talent density without breaking the regulatory or safety posture that defines you.
Examples: Banks, defense, healthcare systems, central infrastructure operators.
Pick this only if 'we move slowly because the cost of failure is regulatory or human-life' is true. If you move slowly because of habit, you are a Spectator.
Talking about AI, not yet operating around it.
You have AI initiatives, AI working groups, an AI strategy slide. You do not yet have an AI-era operating model. This is the most common honest answer for established companies in 2026, and naming it is the prerequisite for moving out of it.
Examples: Most Fortune 1000 outside tech, most enterprise SaaS over 15 years old, most legacy services firms.
If you cannot point to a single team whose operating cadence has been redesigned around AI in the last 12 months, this is you. The diagnostic still works. The rating just calibrates against what 'great' looks like at this tier.