AI OPPORTUNITY ASSESSMENT

AI Opportunity Assessment: Where Should AI Actually Fit in Your Business?

A structured assessment for identifying where AI can create practical value, where human judgement must remain, and which workflows are not ready for automation.

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AI Opportunity Assessment — Where Should AI Actually Fit in Your Business? Portfolio sample document showing assessment framework, opportunity map, and prioritisation logic.
01
THE PROBLEM

AI adoption often starts with the wrong question

The question is not simply whether AI can perform a task.

The real question is whether AI can improve the workflow without creating more review, confusion, risk, or hidden dependency than the value it adds.

Businesses often begin with tools or automation before they have clarified:

  • which workflows are worth improving
  • whether the task is suitable for AI
  • whether the source material and inputs are ready
  • where human judgement must remain
  • who will own, review, and maintain the workflow
  • what the operational risk is if the output is wrong

Use AI where it creates measurable value inside a workflow with clear inputs, defined boundaries, appropriate human judgement, and accountable ownership.

02
ASSESSMENT CRITERIA

Five areas used to assess an AI opportunity

01

Business value

Does the opportunity improve time, cost, quality, capacity, revenue, or decision speed in a way that can be measured and justified?

02

Task suitability

Is the work repeatable, bounded, and describable, or is it highly ambiguous and dependent on judgement that cannot be specified in advance?

03

Input readiness

Are the source material, data, context, constraints, and examples stable and consistent enough for reliable AI use without constant manual correction?

04

Human judgement

Where must approval, interpretation, ethics, sensitivity, authority, or accountability remain human-led, and what happens if that boundary is not defined clearly?

05

Operational fit and risk

Who owns, reviews, approves, and maintains the workflow, and what is the operational consequence if the AI output is wrong, incomplete, or misused?

03
DECISION LOGIC

Not every AI opportunity should move directly into automation

Each candidate use case is assessed against the five criteria and assigned one of four decision outcomes.

Proceed to controlled pilot

Use when there is clear value, usable inputs, manageable risk, and a defined human role.

Redesign before pilot

Use when the opportunity is valuable but the workflow has weak inputs, unclear handoffs, undefined acceptance criteria, or unclear ownership.

Keep human-led

Use when the task depends heavily on judgement, sensitivity, authority, or accountability.

Do not prioritise

Use when the business value is low, the process is unstable, or implementation effort is likely to exceed the benefit.

04
ILLUSTRATIVE EXAMPLES

How different AI opportunities may be assessed

Internal meeting summaries and action capture

VALUEHigh
READINESSHigh
RISKLow to medium
ASSESSMENT DECISION

Proceed to controlled pilot with approved inputs, fixed output structure, and human confirmation

Drafting routine client follow-up emails

VALUEMedium to high
READINESSMedium
RISKMedium
ASSESSMENT DECISION

Pilot after workflow design, with defined context, tone, exclusions, approval, and escalation rules

Automated client recommendations

VALUEHigh
READINESSLow
RISKHigh
ASSESSMENT DECISION

Do not automate yet. Keep final recommendations human-led

Reformatting approved content for multiple channels

VALUEMedium
READINESSHigh
RISKLow to medium
ASSESSMENT DECISION

Suitable for early implementation with locked source content and claim validation

05
RECOMMENDED SEQUENCE

A controlled path from opportunity to pilot

01

Choose a bounded workflow

Select one workflow with clear value and limited downside if the output is wrong.

02

Define the human-AI boundary

Specify what AI may support and what a person must review, decide, or approve.

03

Lock sources and constraints

Fix the source material, context, constraints, exclusions, and acceptance criteria before generation begins.

04

Assign ownership

Name the source owner, reviewer, approver, and workflow owner before the pilot starts.

05

Run a measurable pilot

Track output quality, review time, correction patterns, and operational risk throughout.

06

Use evidence to scale, redesign, or stop

Base the next decision on what the pilot evidence shows, not on initial expectations.

06
DELIVERABLES

What an AI Opportunity Assessment provides

AI opportunity map

Candidate use cases ranked by value, readiness, risk, and decision status.

Prioritised shortlist

The small number of opportunities worth piloting first, with a clear rationale.

Human-AI decision boundaries

Clear definition of what AI may support and where human judgement or approval must remain.

Readiness gaps and pilot recommendation

The prerequisites, controls, owners, measures, and evidence needed before scaling.

07
RESOURCE

View the sample assessment

The source document explains the opportunity screening criteria on page 1 and provides the opportunity map, prioritisation logic, recommended sequence, and deliverables on page 2.

PORTFOLIO SAMPLE ONLY · NO CLIENT DATA IS INCLUDED

08 · NEXT STEP

Need to decide where AI should fit before you invest?

An AI Opportunity Assessment helps clarify which workflows are worth pursuing, which need redesign first, and where human judgement must remain.

It is designed for businesses that want a practical starting point rather than a list of tools or generic automation ideas.