A communications team buying an AI tool is making a data decision as much as a software decision. The questions that matter at procurement aren't about features — every tool demos well. They're about what happens to the information the team puts in.
Quick answer. When buying an AI tool, the features are the easy part. The procurement questions that matter are about data: is your input used for training, how long is it retained, what are the security terms, and what happens to your data if you leave. Ask those before signing — not after.
Features are not the decision
Every AI tool looks impressive in a demo, and most of them genuinely work. That's exactly why features can't be the basis of the decision — they don't separate the options. What separates them is the terms underneath: how the vendor treats the data a team feeds it, day after day, on client work.
Question | What you're checking |
|---|---|
Training | Is our input used to train the vendor's models? On which tiers is that on or off? |
Retention | How long is our data kept? Can we set or shorten that? |
Security | What encryption, access controls, and certifications are in place? |
Access | Who at the vendor can see our data, and under what conditions? |
Exit | When we leave, what happens to our data — is it deleted, and how do we confirm it? |
Tier | What specifically changes in data terms between the consumer, team, and enterprise tiers? |
A vendor that answers these cleanly is a vendor a team can put client work into. A vendor that's vague on them is telling you something.
Individual vs. team vs. enterprise
The tier is itself a data decision, not just a price one. Team and enterprise tiers generally carry stronger data terms — training off by default, admin controls, clearer retention. For a team handling client material, that isn't a premium upgrade; it's the baseline. Consumer logins are the wrong surface for client work regardless of how capable the underlying tool is.
Contract red flags
Watch for vague or shifting language on training use; no straight answer on retention; no deletion-on-exit commitment; and consumer-grade terms presented as if they were business terms. Any one of these is a reason to slow down.
Consider a team that picked the cheaper of two tools on features and price, signed quickly, and discovered afterward that inputs were used as training data by default and there was no clean process to retrieve or delete its data on exit. The tool worked well. The terms were the problem — and the terms were knowable before signing.
Frequently asked questions
What should a communications team ask before buying an AI tool?
Six things: whether inputs train the vendor's models, how long data is retained, the security terms, who can access the data, what happens to it on exit, and what changes between tiers.
Is the enterprise tier worth it?
For client work, usually yes — not for features, but for the stronger data terms and admin controls. Treat it as the baseline, not an upgrade.
What's the biggest procurement mistake?
Buying on features and price without reading the data terms — and discovering the terms only after client material is already in the tool.
