Is your business ready for AI?

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Start with the process
If your team cannot explain the workflow, AI will not fix the confusion
Before choosing a model, map what happens today.
What triggers the workflow? What starts the process (e.g., a request, event, customer action)?
Who touches it from start to finish? Which teams, people, or systems are involved?
What decisions are made along the way? Where are choices made and what rules or criteria guide them?
Where does information come from? What data, documents, or systems provide the inputs?
Where do delays, errors, or rework happen? What causes bottlenecks, mistakes, or repeat work today?
What does a good outcome look like? How do you know it worked? What does success look like for the business?
Fix the workflow before you automate the confusion.
The best AI projects usually begin with a process map, not a model comparison.

Is your data ready?
AI can only use information it can reach, understand, and trust
Accessible: Can the system actually reach the files, records, or applications it needs?
Current: Is the information updated often enough for the use case?
Consistent: Do names, fields, categories, and formats mean the same thing across systems?
Useful: Does the data contain what the workflow really needs to make a decision?
Permitted: Are you allowed to use the information for this purpose?
Owned: Does someone know who is responsible for keeping it accurate?
You do not need perfect data, but you do need data that is good enough for the decision being automated.

Can your systems connect?
AI needs a safe path to the software and information around it
Technical access
APIs or approved integrations
Database or document access
CRM / ERP / scheduling connections
Identity and user permissions
Control & security
Who can read what?
Who can change what?
Which actions need approval?
What gets logged for review?
Good AI access is specific, limited, and auditable.
Connection without permissions is a risk; permissions without connection is a dead end.

Do you have ownership?
AI projects need a business owner, not just a software owner
Business owner: Defines the outcome and decides whether the workflow is actually better.
Process expert: Explains how the work is really done, including exceptions and edge cases.
Technical owner: Maintains integrations, permissions, data access, and system reliability.
Human reviewer: Handles the cases where judgment, approval, or escalation is required.
Measurement owner: Tracks whether the project is saving time, improving quality, or producing ROI.
No owner = no one responsible when the workflow drifts.
AI is a business change project with technology inside it. Ownership needs to reflect that.

The AI readiness check
You do not need to be perfect: you need to be clear enough to pilot safely
We can name one specific business problem worth solving.
We understand the current workflow and where it breaks down.
The required data is accessible and reasonably trustworthy.
The systems can connect through approved, controlled access.
Someone owns the outcome and can make decisions about the process.
We know which actions require human approval or escalation.
We have a baseline and can measure whether the pilot actually helped.
If most of these are true, you are ready to test, not scale.
Start with one narrow pilot. Readiness is proven by controlled learning, not by buying more technology.

Lesson done.

Up next

Where do you start if you've never used AI?

Where does this fit your business? Get your AI plan

Swipe to see each slide.

The short answer

Your business is ready for AI when you can name one specific problem, explain the workflow, reach usable data, and have someone who owns the result. You do not need perfect data or to buy software first: if most of these are true, run one narrow pilot, a small controlled trial, rather than scaling up.

Three things to remember

01Map the current workflow first: what starts it, who touches it, where it breaks and what good looks like.
02Data needs to be reachable, current, consistent, useful, permitted and owned, though not perfect.
03Name an owner for the outcome, decide which actions need human approval, and record a starting measurement.

Every slide, in words

01
Is your business ready for AI?
AI readiness starts with the business, not the model
Being ready for AI does not mean buying AI software. It means having a problem, process, data, and owner clear enough to improve.
Problem: A specific bottleneck worth solving.
Process: A workflow your team can actually explain.
Data: Useful information in a form the system can access.
Owner: Someone responsible for the result.
AI readiness = business clarity + technical access
A messy process does not become a good process just because AI is added to it.
02
Start with the process
If your team cannot explain the workflow, AI will not fix the confusion
Before choosing a model, map what happens today.
What triggers the workflow? What starts the process (e.g., a request, event, customer action)?
Who touches it from start to finish? Which teams, people, or systems are involved?
What decisions are made along the way? Where are choices made and what rules or criteria guide them?
Where does information come from? What data, documents, or systems provide the inputs?
Where do delays, errors, or rework happen? What causes bottlenecks, mistakes, or repeat work today?
What does a good outcome look like? How do you know it worked? What does success look like for the business?
Fix the workflow before you automate the confusion.
The best AI projects usually begin with a process map, not a model comparison.
03
Is your data ready?
AI can only use information it can reach, understand, and trust
Accessible: Can the system actually reach the files, records, or applications it needs?
Current: Is the information updated often enough for the use case?
Consistent: Do names, fields, categories, and formats mean the same thing across systems?
Useful: Does the data contain what the workflow really needs to make a decision?
Permitted: Are you allowed to use the information for this purpose?
Owned: Does someone know who is responsible for keeping it accurate?
You do not need perfect data, but you do need data that is good enough for the decision being automated.
04
Can your systems connect?
AI needs a safe path to the software and information around it
Technical access
APIs or approved integrations
Database or document access
CRM / ERP / scheduling connections
Identity and user permissions
Control & security
Who can read what?
Who can change what?
Which actions need approval?
What gets logged for review?
Good AI access is specific, limited, and auditable.
Connection without permissions is a risk; permissions without connection is a dead end.
05
Do you have ownership?
AI projects need a business owner, not just a software owner
Business owner: Defines the outcome and decides whether the workflow is actually better.
Process expert: Explains how the work is really done, including exceptions and edge cases.
Technical owner: Maintains integrations, permissions, data access, and system reliability.
Human reviewer: Handles the cases where judgment, approval, or escalation is required.
Measurement owner: Tracks whether the project is saving time, improving quality, or producing ROI.
No owner = no one responsible when the workflow drifts.
AI is a business change project with technology inside it. Ownership needs to reflect that.
06
The AI readiness check
You do not need to be perfect: you need to be clear enough to pilot safely
We can name one specific business problem worth solving.
We understand the current workflow and where it breaks down.
The required data is accessible and reasonably trustworthy.
The systems can connect through approved, controlled access.
Someone owns the outcome and can make decisions about the process.
We know which actions require human approval or escalation.
We have a baseline and can measure whether the pilot actually helped.
If most of these are true, you are ready to test, not scale.
Start with one narrow pilot. Readiness is proven by controlled learning, not by buying more technology.

More in part 1

Next step

Where does this fit your business?

Six quick questions about your business, then your AI plan: what to start with, what a person still checks, and the lessons that go with it. Or bring it straight to a free thirty-minute call.

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