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Proving an AI Project Was Worth It

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Measure before you build

The most common reason an AI project cannot prove its value is that nobody recorded the baseline. Two weeks of timing the current process, before anything changes, settles the question permanently.

It costs almost nothing and it is impossible to reconstruct afterwards.

What to record

  • Time per item, sampled over a normal fortnight including a busy day
  • Volume per week, and how much it varies
  • Error rate, and what errors cost when they escape
  • Backlog age — how long things wait
  • What people stopped doing because of this work

Be honest about saved time

Six hours a week saved across four people is not one and a half days of capacity unless those people had something specific waiting. Otherwise it is a better week, which is worth having and is not a number for a business case.

The credible version names what the time went to: a backlog cleared, a role not backfilled, more calls made, faster response to customers.

Measures that survive scrutiny

MeasureCredible because
Roles not backfilledDirectly visible in payroll
Backlog eliminatedCountable before and after
Response time to customersMeasured by the system, not estimated
Errors preventedCountable, with known cost each
Volume handled without added headcountGrowth absorbed, evidenced

Review at ninety days

Not at launch. Quality settles about six weeks after first users, and behaviour change takes longer than that.

Book the review when the project starts, with the baseline attached. A scheduled review with a number is what protects a good system at the next budget round.

Frequently asked questions

What if the numbers are disappointing?

Then you have learned something for the cost of one project rather than five. Write it down honestly; it makes the next business case more credible, not less.

How long until return is visible?

Three to six months for most process automation. Faster where the saving is a backlog or a role; slower where it is distributed minutes.

Should we count quality improvements?

Yes, where you can count them — errors prevented, complaints avoided. Not as an unquantified assertion, which reads as an excuse.

Who should do the measurement?

Someone in the business rather than the supplier. Our numbers are useful; yours are believable.

Keep reading

About to start an AI project?

Spend two weeks measuring the current process first. It is the cheapest thing you will do and the only baseline you will get.

Book a free 30-minute call Get a project estimate WhatsApp us

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