AI Readiness and Financial Feasibility
Can your business carry AI, where does it pay, and is the move fundable?
Before a rupee is spent, three answers decide everything: whether the business can carry AI, where it would move the P&L, and whether the move is worth funding. Almost everyone reaches for tools. We start here, because most of the distance between a pilot and a return is data, process and operating model. Not the model.
Roughly 80% of the work between an AI pilot and a real return is readiness: data, process, people, governance. Skip it and you join the 95% of pilots that never reach production. So we run the diagnostic we would run before any structural intervention, now with an AI lens, and we cost the answer.
- 01
The readiness of your data systems, at the point a decision uses them
Not the way a system stores it. What is structured, what is trustworthy, and whether it is reachable at the exact moment someone has to act on it.
- 02
Your organisational design, and where decisions actually get made
Who signs off, who is consulted, and where a decision truly happens, versus where the org chart says it does.
- 03
Process maturity, as work happens on the floor, not as the SOP reads
The real routine, the workarounds, the steps nobody wrote down but everybody runs. AI lands on the actual process, so we map the actual process.
- 04
People capability: who can carry this, and what they would need
The skills in the building today, the gap to close, and where the change lands on the people it affects.
- 05
Every critical workflow, marked task by task for what AI can carry
AI is excellent at one task and confidently wrong at the next that looks identical. Each task gets classified: automate, assist, or leave to a person.
- 06
Each use case, taken apart until it is specific enough to cost
“AI in the supply chain” becomes a defined prediction, on named data, against a decision, with a measure. One is a wish. The other you can fund.
- 07
What a wrong answer costs, and then the financial case
A false alarm and a miss almost never cost the same. Over-rejecting a good batch wastes material; letting a defect reach the customer can lose the account. Someone has to put numbers on that gap, because until they do, even a perfect model cannot know what “good” means. With the costs named, we build the financial case: where AI pays, what it takes, and whether it is fundable.
Everything is a prediction
Most business AI today is cheap prediction: data you have becoming information you do not. Priced that way, the decision stops being about technology and becomes a number. And the scarce input is not the model, it is knowing what a wrong answer costs, which almost nobody has written down.
The readiness scorecard
Five dimensions decide whether AI can land: data infrastructure, technical talent, process maturity, leadership alignment, and cultural readiness. Most businesses find their data and processes are worse than they thought. Better to find it here than in production.
Binary calls, not heat maps
Every finding is ready or not ready, fundable or not. A colour-coded heat map tells you nothing you can act on. A binary call, costed and stage-gated, does.
A ₹500 Cr auto-components manufacturer
Three plants, two thousand SKUs, an ERP installed but barely used. The pain everyone pointed to was quality control: could AI catch defects before they reached the OEM?
We decomposed it. The prediction was sound and the vision technology is well solved. But the QC records were on paper, the sensor data was never logged, and there was no structured history to train on. The technology was commodity. The readiness was zero.
The honest answer was: not yet, and here is the six-month data foundation that makes it fundable. That answer saved a year and a budget.
- No push to deploy.
- Binary calls, not heat maps.
- The output is mostly honest noes.
- The yeses come specific, costed and stage-gated.
- A readiness scorecard across five dimensions
- A financial baseline with AI impact modelled against it
- A ranked use-case portfolio any vendor could build from
- A clear, costed go or no-go on each
The confidence to fund the right move. Or to keep the capital.