AI Solution Design Model

Most AI projects start with a sentence like this:

“We want a bot that helps us stay in touch with customers.”

That is a useful starting point.

It is also nowhere near enough for someone to design the system properly.

The gap is usually in the middle.

The business knows the problem. The technical team knows how to build software. What is often missing is a clear description of what the AI solution actually needs to achieve, know, do, decide and control.

That is what the AI Solution Design Model is for.

It is a simple framework for non-technical business people who want to shape an AI solution before handing it over to a software architect, developer or AI team.

You do not need to know how AI works.

You do need to understand the work.

In the zip you get:

1. An example canvas

2. A canvas with the thinking prompts

3. A blank canvas

4. The full workbook to help you along where you may get stuck.

What the model helps you define

The workbook takes you through nine parts of the solution:

1. Outcome - what business result are we trying to create?

2. People - who is involved?

3. Workflow - how should the work flow?

4. Triggers - when should the solution do something?

5. Data & Context - what does it need to know?

6. AI Capabilities - what work should the AI perform?

7. Decisions & Actions - what may it recommend, decide or do?

8. Rules, Exceptions & Human Control - where are the boundaries?

9. Success - how will we know it works?

The workbook explains each block, shows an example, then gives you space to work through your own solution.

I use one example all the way through called KIT, a Keep In Touch system that helps someone maintain important business relationships.

Using the same example across all nine blocks makes it easier to see how a vague idea becomes a much clearer brief.

How I would use it

Pick one AI idea.

Do not try to map your whole company.

Sit with the people who understand the process and work through the blocks in order.

Keep the answers simple.

You are trying to get the business logic out of people's heads and onto the page.

You will probably find gaps.

That is useful.

You may realise that nobody has decided when the AI should act, where some information comes from, who approves a decision, or what should happen when the system is unsure.

Those are much cheaper problems to find before development starts.

What you should have at the end

You should finish with a business-side solution brief that explains the problem clearly enough for a technical team to start proper design.

The technical team can then work out the architecture, integrations, models, security, data flows and implementation approach.

The workbook stays on the business side of that line.

If you have an AI idea sitting in a notebook, meeting transcript or half-finished slide, start here.

Define the work first. Then design the technology.