AI maturity model
The 5 levels of AI adoption: an AI maturity model for engineering.
Where your engineering org is, what is required to be there, and what to measure to prove it. Five levels, and you cannot skip one: companies that jump from Level 1 to Level 4 without talent and measurement end up with a good-looking dashboard and no answer to what the AI line bought.
First presented at ELC meetup #39 in Prague. The meetup
Level 1
Nothing in production
Hackathons, pilots, one engineer using Copilot on her own card. No paying user has triggered an inference. No AI line on the P&L.
| KPI | Red | Amber | Green |
|---|---|---|---|
| AI-assisted PR rate | <10% | 10 to 30% | >30% |
| Days to first production AI feature | Never set | Slipping | <90 days |
| Paid AI seats deployed | <25% | 25 to 60% | >60% |
What is required to leave Level 1
One workflow chosen.
Internal, bounded blast radius. Not customer-facing on day one.
Baseline measured before any AI lands.
Lead time, tickets, cost per unit. Numbers a CFO can read.
Six-week timebox.
If it does not move the baseline number, kill it visibly.
One team owns pilot and production.
No throwing over the wall.
Next move: Pick one workflow. Baseline it. Ship in six weeks. Same team owns pilot and production from day one.
Level 2
Talent
Your org chart changed because of AI. Not your tooling, your org chart. A named owner runs AI enablement with budget.
| KPI | Red | Amber | Green |
|---|---|---|---|
| Engineers AI-fluent, audited quarterly | <30% | 30 to 70% | >70% |
| Net AI-driven org change, last 12 months | 0% | 5 to 15% | >15% |
| Single named AI-enablement owner | No | In name only | Yes, with QBR |
What is required to be at Level 2
Job descriptions list AI fluency as baseline.
Not a bonus. A requirement.
Headcount allocation has visibly shifted.
Fewer junior backfills, more AI-fluent senior hires. Or the other way round.
At least one role was eliminated or repurposed.
Because AI now does that work.
One named AI-enablement owner.
With a quarterly business review, not a Slack channel.
Next move: Stop measuring AI as a cost-saving tool. Start measuring it as a delivery accelerator, with a structure that compounds.
Level 3
Proof
You can answer one question with one number: what did AI cost us last quarter, and what did we get. If CFO and CTO disagree, you are not at Level 3.
| KPI | Red | Amber | Green |
|---|---|---|---|
| AI cost per shipped unit, tracked monthly | Untracked | Tracked, no threshold | Tracked, threshold at QBR |
| AI-attributable margin | Untracked | <2% | >2% |
| AI delivery instability vs non-AI work | 2x+ worse | 1.2 to 2x | Within 20% |
What is required to be at Level 3
AI is a named P&L line.
Owned by Engineering or Product. Not buried in a cloud bill.
A unit economic exists.
Cost per AI-assisted PR, per AI-resolved ticket, per unit of value shipped.
A counterfactual baseline.
What it would have cost without AI. No baseline, no proof.
Delivery stability tracked alongside throughput.
AI tends to lift throughput and drop stability. Measure only one and you miss the trap.
Next move: Build the agent that scores your AI output: per session, how long a human would have taken. That ratio is your Level 3 proof.
Level 4
AI-native
AI is not a tool your engineers use. It is a teammate in the build pipeline. Task complexity rising, autonomy rising, human turns per session falling.
| KPI | Red | Amber | Green |
|---|---|---|---|
| AI-merged PR rate, fully autonomous | <5% | 5 to 30% | >30% |
| Production AI features with CI eval coverage | <40% | 40 to 80% | >80% |
| AI-attributable EBIT, signed by the CFO | 0% | <5% | >5% |
What is required to be at Level 4
A customer-facing AI feature with an SLA and an on-call rotation.
Not a demo. A product.
Autonomous agents handle a measurable share of internal work.
Merges, ticket resolution, security patching.
An eval harness in CI.
Regressions block deploys. Quality and safety monitors page the on-call.
The CFO signs an AI-attributable EBIT number.
Not directional. Specific.
Next move: Find the next thing AI does that competitors cannot copy by buying the same models. That is Level 5, and it is a product question.
Level 5
Won the race
Your advantage is no longer "we have AI". It is a product that could not exist without your specific AI maturity. Rare, and probably temporary.
| KPI | Red | Amber | Green |
|---|---|---|---|
| Revenue from AI-dependent product capability | <5% | 5 to 20% | >20% |
| AI-native hiring premium vs market | 0% | <10% | >10% |
| Net-new AI-native bets in the roadmap, with owners | 0 | 1 to 2 | 3+ |
What is required to be at Level 5
A customer-facing moat competitors cannot buy.
Not the model. The capability around the model.
Net-new product lines exist because of internal AI maturity.
Things you could not ship before.
You hire talent others cannot.
Because AI work here is more interesting than elsewhere.
Velocity has changed category.
Not 20% faster. A different kind of work shipped.