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M. K. ELANGO
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The Flywheel Locator

Mark your four stages and two layers. Leave with one sentence: we are strongest at ___ and our weakest part is ___.

Length
6 questions · about 3 minutes
Scored out of
30
Benchmark
13
What it reads

Where your AI capability actually sits on the powertrain — and which part is holding the wheel.

From The AI Flywheel · ENGINE
The instrument

Flywheel Locator

01 / 06
Answer as the organisation actually behaves, not as the policy says it should.
Why this one

Own the road. Rent the car.

Foundation, Generative, Agentic, Physical. Plus DRIVE — the hub — and CORE — the rim. Six readings, one sentence.

The sentence is the deliverable. If you cannot say where you are strongest and where you are weakest in one line, you cannot brief a board, and you certainly cannot sequence ninety days of work.

Method

The benchmark, and how it was built.

A score is only as good as the thing it is compared against. So the benchmark carries a grade and a method, exactly like every other figure on this site.

The benchmark

13/30[C]Grade C · EstimateMean self-reported reading across organisations with a named AI budget. estimate from workshop sampling, as at 26 August 2026.As at 26 August 2026

Mean self-reported reading across organisations with a named AI budget. Grade [C] — estimate from workshop sampling, as at 26 August 2026.
[A]

Verified

Traced to a primary source — a filing, an audited statement, a contract, a dataset held by us — and the source is named.

[B]

Claimed

Reported by a credible party, including by us, but not independently traceable to a primary document.

[C]

Estimate

Modelled, sampled or directionally derived. Method stated. Treat as a shape, not a number.

The Evidence Log

What we do with your result The score is computed in your browser. Nothing is transmitted unless you ask for the detailed report, and in that case only the score, the trait breakdown and your email address are stored. Your result is never published, sold, shared or attached to your name in any material. Privacy
The questions

All 6, published in full.

Nothing is hidden behind the interaction. If you would rather read the instrument than run it — or run it on paper, in a room, with other people — here it is.

01 Foundation AI — How much of your operational data is clean, connected and queryable?
  1. 1Almost none
  2. 2One domain
  3. 3Two or three domains
  4. 4Most domains, with known gaps
  5. 5A governed layer everything reads from
02 Generative AI — Are any generative use cases producing measured value in production?
  1. 1No, pilots only
  2. 2One, value unmeasured
  3. 3One, value measured
  4. 4Several, measured
  5. 5Several, measured, and funding the next stage
03 Agentic AI — Do you run agents that take actions, not just produce text?
  1. 1No
  2. 2Prototypes only
  3. 3One in production, tightly scoped
  4. 4Several in production with human gates
  5. 5Agents are an operating model with named owners
04 Physical AI — Does operational data from production systems train anything physical or embedded?

Answer 1 without hesitation if this is not your sector. It is not a deficiency.

  1. 1Not applicable or not started
  2. 2Exploring
  3. 3A pilot exists
  4. 4One production system
  5. 5A closed loop, operating data to physical system
05 DRIVE · the hub — Before a build starts, is success written down and is there a data gate?
  1. 1Neither
  2. 2Sometimes, informally
  3. 3Success is written; no data gate
  4. 4Both, on the important builds
  5. 5Both, always, and a build has been stopped by the gate
06 CORE · the rim — Is governance treated as an unlock or as a brake?
  1. 1It is a brake and everyone routes around it
  2. 2A brake, formally complied with
  3. 3Neutral — a checklist
  4. 4An enabler on some workstreams
  5. 5The unlock. Governance is why we can ship to regulated customers

Scored out of 30. Published benchmark 13. Method and grade above.

The bands

What each range means.

Published before you take the test, so the reading cannot be tuned to flatter afterwards.

0–11

The wheel is not turning

There are parts, but no powertrain — one stage’s output is not another stage’s input. That is not a failure of ambition; it is a sequencing problem, and it is the most fixable state on this instrument.

12–19

Turning, slipping

Something compounds and something else leaks. Typically a strong generative layer sitting on a weak foundation, which caps how far the agentic stage can go. Name the weakest part and give it the next ninety days.

20–25

Compounding

The wheel turns and each stage is feeding the next. At this reading the binding constraint usually moves from technology to governance — which is the CORE argument, and it is good news.

26–30

The road is yours

A rare reading. The engine is model-invariant, which means the next model release is a fuel swap rather than a roadmap reset. Re-score with a sceptic and then go and standardise the win.

FAQ

Questions about The Flywheel Locator

Answered plainly, with the real figures. If something here is wrong, tell us and it goes in the log.

Foundation AI, Generative AI, Agentic AI and Physical AI — the four stages of the powertrain. Two further readings sit around them: DRIVE, the hub, which asks whether success is written down and a data gate exists before a build starts; and CORE, the rim, which asks whether governance is treated as an unlock or as a brake.

The wheel is turning when one stage's output is the next stage's input. The published bands read: 0–11, the wheel is not turning, because parts exist but no powertrain does; 12–19, turning but slipping, typically a strong generative layer on a weak foundation; 20–25, compounding, where the binding constraint moves from technology to governance; 26–30, a rare reading.

The instrument tells you to answer one without hesitation if physical or embedded systems are not your sector, and states plainly that this is not a deficiency. The reading out of 30 is a locator, not a league table — its deliverable is one sentence naming where you are strongest and where you are weakest.

The Flywheel Locator reads AI capability at the ENGINE altitude — what compounds over ninety days to five years — and scores out of 30 against a benchmark of 13. The AQ Score reads organisational architecture at the ORGANISATION altitude, three to five years, across twelve traits out of 60 against a benchmark of 27. Different instruments, different books.

The next ninety days belong to the weakest part; everything else waits. That is the programme AI Flywheel: The 90-Day Start — one workflow into production, measured honestly, with a named human owner — priced at ₹12L – ₹75L and banded by workflow complexity and whether data instrumentation is in scope. Starts are rolling rather than cohort-based.

The other instruments

Five more, one per altitude.

All six

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