The Method / 01 · Assess

Should we invest in AI — and where?

The assessment answers this with evidence, not a pitch. Two to four interviews, a scored readiness dial, and what to do first: which tools fit your work, what’s safe for your clients’ information, and a usage policy you can adopt. Delivered in about a week, at a fixed, published price.

$2,000 fixed~1 week60–90 min readout

Where to start

The free Check vs the paid Assessment

	The Opportunity Check	The Assessment
PRICE	Free · runs in your browser	$2,000 fixed · published
TIME	Two minutes	About a week
INPUT	Eight questions, rough math	Interviews with the people who do the work
OUTPUT	A pointer: where AI could earn its keep	A scored baseline + what to do first
ENGINE	The same one. The Assessment replaces rough math with real numbers.

How it works

Three steps. Light lift from your team.

1Listen. Two to four short interviews plus one working session — an executive sponsor, two or three frontline operators, a tooling or IT lead. 60–90 minutes each, inside a normal day.
2Map. Offsite work mapping workflows and filtering opportunities: impact on hours or revenue, effort to build and maintain, risk and data sensitivity, fit with your existing stack.
3Readout. A 60–90 minute session with the ranked opportunity map, what to do first, and a check of which funding programmes may apply — in plain English, built to be argued with.

AI Adoption AssessmentWorked example

01 The scorecard

Readiness is 56 / 100 — the equal-weighted mean of the five pillars below, and reported as exactly that. The gap is governance and tooling, not people: literacy already sits above the mean because staff didn’t wait for permission to start.

Readiness by pillar, each scored out of 100
Pillar	Status	Score	Evidence
Process clarity	Strong	71 / 100	Dispatch runs on a documented playbook; billing partially mapped
Team literacy	Ready to train	66 / 100	Informal ChatGPT use in customer email — capability waiting for structure
Data hygiene	Watch	54 / 100	TMS records clean; billing lives in fragmented spreadsheets
Tooling coverage	Gap	48 / 100	Consumer tools only; no business tier, no shared accounts policy
Governance & security	Start here	42 / 100	No usage policy in force while customer data flows through public chatbots

Readiness today · equal-weighted: 56 / 100
Day-90 target: 68
Recoverable capacity identified: ~11 hrs/wk

Worked example — Northshore Logistics is a fictional client · Zaiphr AI

The scorecard: five pillars, one equal-weighted score · worked example

What you leave with

Four documents, built to be used.

DOC 01

Top opportunities

Ranked by impact, effort, risk
Hours saved per opportunity
Realistic now vs later
The recommended start

DOC 02

Which tools fit

A comparison for your setup (Copilot, ChatGPT, Claude…)
One clear recommendation
The compliance and privacy points that apply
What to do first

DOC 03

Safe-use rules

What data goes in, what never does
Do-and-don’t guidance for staff
Tool configuration notes
Incident response checklist

DOC 04

Rollout & training plan

Training steps that fit your schedule
Change support so habits stick
Internal office-hours cadence
A measurement plan for impact

Fit

Who it’s for — and who it isn’t.

A good fit if

You run a 1–50-person business and the same hours keep disappearing into re-keying, triage, or reporting
You’ve tried AI tools and they didn’t stick
You want to know what’s safe and what to do first before spending on builds
You’d rather hear “don’t build anything yet” than buy a pitch

Not the right week if

You need a vendor to validate a decision that’s already made
Your team genuinely can’t spare three hours of interviews
You already have a working AI roadmap — go straight to Build

The honest exit: if AI isn’t a fit right now, the report says so — that’s the point of paying for evidence instead of a pitch.

Run the Opportunity Check Book a fit call