Which AI tool purchase would you not repeat?

I

Imani Brooks

Community member

9h

I am trying to get a realistic read on which AI tool purchase would you not repeat.

Share mismatches, missing features, cost surprises, maintenance issues, and what you would buy instead.

What has actually worked (or failed) for your team? Specific examples, pricing traps, or vendor claims that did not hold up are especially useful.

598views8replies
R

Rina Deshmukh

Operations lead

8h

The vendor demo is not the product. Ask to see the same workflow run on your data, not their sample data. That is where connector gaps and permission issues show up.

T

Theo Lang

Customer success lead

7h

Measure rework, not just throughput. An agent that resolves 80% of cases but creates 30% more manual cleanup is not saving time.

Y

Yara Mendes

Senior engineer

6h

We learned the hard way that 'human in the loop' is not a checkbox. If the approval UI is buried or slow, reviewers will batch-approve without reading.

C

Cass Ortega

RevOps practitioner

5h

Security questions should be part of the first demo, not a procurement afterthought. Ask about retention, sub processors, prompt-injection testing, and audit logs before you waste time on a trial.

L

Leo Park

Customer success lead

4h

We ran a 3-week pilot with a similar brief. The biggest gap was ownership after launch — if ops cannot edit prompts and tools without engineering, it dies. Pick the platform your weekly owner can actually maintain.

A

Aria Voss

Strategy & architecture

3h

Agree on rollback and permissions before demos. We lost a week because the agent could write CRM fields with no audit trail. Make field-level history a go/no-go in the RFP.

F

Felix Kron

RevOps practitioner

2h

Budget-wise, usage pricing looked cheaper until support volume spiked. Model a bad week, not an average day. That alone flipped our shortlist.

H

Hana Ishikawa

Research analyst

1h

We compared two vendors on the same 20 tickets. Accuracy was fine; escalation quality was not. Score human handoff and confidence thresholds harder than model branding.