Deployed Works Guide
For organisationsHow To Scope AI Implementation Work You Don't Fully Understand Yet
Describe the workflow, outcome, data, risks and first test before choosing an AI tool or provider.
How To Scope AI Implementation Work You Don't Fully Understand Yet guide trailer
A short walkthrough for this guide will appear here.
Audience
For organisations
Founders, operators, capability buyers, product leaders and startup or scaleup teams
Time
2 minute read
Outcome
Describe the workflow, outcome, data, risks and first test before choosing an AI tool or provider.
Share this guide
PDF guide
Share this guide with your team.
Download the PDF for meetings or offline use. The web guide has the latest version.
Related guides
Guide summary
What this guide helps you do
Who it is for
Best fit readers
- A founder who can see an AI or automation opportunity but cannot yet name the right solution.
The problem
Start with the problem, not the model.
AI implementation work is hard to scope because the buyer may not know what is technically possible, the available data may be unclear, the workflow may be poorly documented and stakeholders may expect different things from the same project. AI may not be the right answer.
AI scoping map
Map the work before guessing the model.
Use this canvas to turn a vague AI opportunity into a practical first specialist conversation.
Workflow
Affected process
What process, decision or handoff is affected?
Pain
Current friction
What is slow, manual, inconsistent, risky or expensive?
Data / systems
Inputs and tools
What information, tools or systems are involved?
Desired outcome
Better state
What should be faster, clearer, cheaper or more reliable?
Specialist question
First provider ask
What do you need a provider to diagnose, design or build?
Diagnose / design / build
Decide the first phase before asking for a build.
Start with the problem, not the model
Do not start with “we need an AI agent.
Map the workflow and affected decision
Name the process, decision or handoff that is affected.
List the systems and data involved
Describe the tools, records, messages, documents or databases involved, even if you do not know whether the data is ready.
Choose the first phase: diagnose, design or build
Use diagnose when the problem is real but the workflow, data or approach is unclear.
Make risks and constraints visible
Call out security, compliance, access, human review, decision ownership, stakeholder expectations and anything the provider should not assume.
Give timeline and budget signal
A rough range is enough.
Example
Vague request into useful brief
Before: “We need AI for support. ” After: “We receive around 800 support tickets a month.
Template
AI implementation capability brief checklist
Current workflow: Current pain: Users or teams affected: Tools and systems involved: Data sources: What has already been tried:
Common mistakes
Avoid these traps
- Starting with an AI buzzword instead of a workflow.
- Assuming an agent is the answer.
- Hiding uncertainty from providers.
Checklist
Ready to publish when
- I can name the workflow or decision affected.
- I can explain the current pain.
- I can list the systems and data involved.
- I can describe what better would look like.
FAQ
Questions this guide usually raises
Do we need to know the exact AI solution before starting?
No. You do not need to know the exact model, agent pattern or automation architecture.
What if AI is not the right answer?
That is a valid outcome of the first phase. A provider may recommend simpler automation, data cleanup, reporting changes, workflow redesign or a narrower pilot before AI implementation makes sense.
Take it with you
Share this guide with your team.
Download the PDF for meetings or offline use. The web guide has the latest version.
Share this guide
Use the canonical page link. No social scripts or tracking widgets are loaded.
Use the guide
Not sure yet is still a valid starting point.
If you can describe the problem and the outcome you want, you can start a capability brief and let the first conversation clarify the work.
