AI Security
Privacy & Governance
Every week brings a new AI tool promising to save time or unlock some capability your business doesn't have yet. Some of them are genuinely useful. Some quietly introduce risk you won't notice until something goes wrong. The difference usually comes down to whether anyone actually evaluated the tool before it touched real business data—or whether it just got adopted because it looked useful in a demo.
Why this step gets skipped
Most small businesses don't have a formal vendor review process for software, let alone AI tools specifically. An employee finds something useful, starts using it, and it becomes part of the workflow before anyone with a risk lens has looked at it. That's not a discipline failure—it's just what happens without a lightweight process to catch it.
A practical AI vendor assessment checklist
Data handling
- What data does this tool collect, and where is it stored?
- Does the vendor use customer data to train their models? Can this be disabled?
- What's the data retention policy—how long is your data kept, and can you request deletion?
Security
- Does the vendor have recognized security certifications (SOC 2, ISO 27001, or equivalent)?
- Is data encrypted in transit and at rest?
- What access controls exist—can you restrict who on your team can use it, and see what they've used it for?
Compliance
- Does this tool's data handling meet any regulatory requirements that apply to your industry?
- If you handle EU or other regulated personal data, does the vendor support the relevant compliance frameworks?
Reliability and vendor stability
- How long has this vendor been operating, and how financially stable does it appear to be?
- What happens to your data and workflows if the vendor shuts down or gets acquired?
- What's their track record on uptime and support responsiveness?
Fit for actual use case
- Does the tool's risk level match the sensitivity of the data it will touch? (See our related post on data classification for AI use.)
- Is there a lower-risk alternative that accomplishes the same goal?
This doesn't need to slow anything down
A checklist like this takes fifteen minutes to work through for most tools—far less time than untangling a data exposure after the fact. The goal isn't to block adoption; it's to make sure someone actually looked before a new tool became part of how the business runs.
DAOVA helps businesses build a practical, repeatable process for evaluating AI tools before they touch business data. Explore AI Governance & Operations.
