Free AI Adoption Resources and Readiness Checklist

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AI readiness checklist.

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Direction We can name one or two workflows that clearly cost timeSpecific tasks, not a general wish to use AI. Someone owns AI adoptionA named person with time and authority to move it forward. Leadership agrees on why we're doing thisSaving time, improving service, reducing errors, or something else.

Data and systems The data for those workflows is in a system, not in people's headsA CRM, shared drive, ERP or database. We can export or connect to our main systemsYour software has an API, export or integration options. We know which data is sensitiveCustomer, employee, health or financial information is identified.

People and policy We have a written AI use policyEven a one-page version counts. We know which AI tools people already useIncluding personal accounts used for work. Staff have had some practical AI trainingBeyond a single demo.

Measurement We've measured how long the target work takes todayA rough baseline is enough. We've agreed what success looks likeTime saved, response speed, error rate or similar. There's a plan for human reviewWho checks AI output, and when.

Template outline

What an AI use policy should cover.

A good policy is short enough that people read it. Use these headings as a starting point, then see our full guide.

01
Purpose and scope
Why the policy exists and who it applies to, including contractors.
02
Approved tools
Which AI tools are allowed, on which account types, and how to request a new one.
03
Data rules
What must never go into AI tools, such as customer, health, financial or confidential information, unless the tool is approved for it.
04
Human review
Which outputs must be checked by a person before they're used or sent.
05
Disclosure
When customers or clients should be told AI was involved.
06
Ownership and questions
Who owns the policy, how often it's reviewed, and who to ask.

Due diligence

Questions to ask any AI vendor.

Ask these before you sign. Vague answers are an answer too. More in choosing an AI vendor.

Data
Is our data used for training?
Get the answer in the contract or data processing terms, not just a sales call.
Data
Where is it stored, and for how long?
Retention, deletion on request, and which subprocessors are involved.
Security
How is access controlled?
Single sign-on, role-based permissions and audit logs.
Quality
How do you measure accuracy?
Ask how they test, and whether you can test with your own examples first.
Exit
Can we get our data out?
Export formats and what happens to your data if you leave.
Compliance
Will you sign what we need?
Such as a data processing agreement or, for health data, a BAA.

Reading list

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AI readiness checklist.

What an AI use policy should cover.

Purpose and scope

Approved tools

Data rules

Human review

Disclosure

Ownership and questions

Questions to ask any AI vendor.

Is our data used for training?

Where is it stored, and for how long?

How is access controlled?

How do you measure accuracy?

Can we get our data out?

Will you sign what we need?

Trusted outside resources.

Keep learning.

Find out where AI can help your business.