Phase 1 — define the problem

What you will learn What to investigate and what to write down. The numbers produced in this phase become the only basis on which success is later judged.

The purpose of this phase

Define a specific business problem AI can solve.

"Specific" is the operative word. "Let's improve customer support" is not specific. "Delivery status enquiries are 490 a month and take 4 minutes each" is.

Four activities

1. Analyse the current process

Look at how it is actually done. Not the procedure written in the document — the real one. They are almost always different.

Sitting next to the person and watching one item end to end is fastest. What comes out while you watch is the valuable part:

"Oh, the system is supposed to do this but it doesn't, so we keep a separate spreadsheet" "Only one person knows how to do this step" "We're supposed to check here, but when it's busy we just pass it through"

That is the real procedure, which is in no document.

2. Identify repetitive, time-consuming tasks

Attach a time to every step.

text

Invoice processing (per item)  1. download the attachment from email     30 sec  2. check contents (amount, line, account)  3 min  3. enter it into accounting                2 min  4. file and archive the original          30 sec  ────────────────────────────────────────────────  6 min each × 400/month = 40 hours/month

This is where which step is an AI target gets decided. Steps 2 (checking) and 3 (entry) are targets; 1 and 4 need only plain automation.

3. Assess AI suitability

Not every repetitive task is an AI target. Filter with this table.

Check	Suitable	Unsuitable
What is the input	documents, text, conversation	physical work, structured numbers only
Is judgement needed	there is a fuzzy judgement	100% expressible as rules (→ plain automation is better)
If it is wrong	reversible	not immediately reversible (→ needs human approval)
Exception rate	under 20%	half are exceptions (→ narrow the scope)

If it is "100% expressible as rules," there is no reason to use AI. Plain automation is cheaper and more accurate. AI is for the part you cannot write as rules.

4. Estimate ROI

text

Current cost:  direct time    40 hrs/month × labour rate = A per month  rework         19 hrs/month × labour rate = B per month  total          (A+B) per monthExpected saving:  human time remaining after automation  8 hrs/month (exceptions)  saving                                 (A+B) × ~80%Investment:  build          about 3 weeks  running cost   C per month (model usage etc.)

Note: this is a projection. It does not need to be accurate — the order of magnitude is enough. A plan that spends six months on a 40-hour monthly task has the wrong order of magnitude.

Output

List of suitable work & ROI projection

It does not have to be an elaborate document. One table will do.

Work	Hrs/month	Rework	Exceptions	Data	Est. saving	Rank
Invoice entry	40h	19h	12%	email + PDF	80%	1
Delivery enquiries	33h	—	8%	order DB	90%	2
Monthly report	16h	—	40%	several sheets	50%	3

Gate — to move on

Does every candidate have numbers for current time and cost?

This gate is the most frequently ignored, and ignoring it costs you latest. Ending up at the six-month review saying "it's definitely faster but I'm not sure how much" is Failure 2.

If you cannot get the numbers

Situation	What to do
No records exist	measure for just two weeks. The owner notes volume and time
It varies by person	write a range, not an average (4–9 min each)
Strong seasonality	write peak and off-peak separately
Truly unmeasurable	deprioritise it. What you cannot measure you cannot prove

Common mistakes in this phase

Collecting too many candidates

Starting with "let's gather everything" produces twenty and turns Phase 1 into two months. Look at three to five at a time and pick one. The rest are the next round.

Writing it at a desk without the owner

Only the owner knows the real procedure. Define it from documents and system screens and you miss every exception case. Those exceptions are what later break the POC.

Starting from "what should we use AI for"

Covered earlier, but worth repeating. Collect problems first, attach solutions later.

Check yourself

1. Why look at "the real procedure" rather than "the documented procedure"?

Answer

Because they are almost always different. "The system doesn't do it so we keep a spreadsheet," "only one person knows this step," "when it's busy we pass it through" — these are the real procedure and appear in no document. Miss them and the exception cases break the POC later.

2. Why should you not use AI for work that is 100% expressible as rules?

Answer

Because plain automation is cheaper and more accurate. AI is for the fuzzy part you cannot write as rules. Using it where rules work costs more and introduces room to be wrong.

3. What do you do if you have no record of current time and cost?

Answer

Measure for two weeks. The owner noting volume and duration is enough. If it varies by person use a range instead of an average; if it is seasonal, split it. A project you truly cannot measure gets deprioritised — what you cannot measure you cannot prove.

Next, the phase that confirms "can it be built" → Phase 2 — data and system assessment