AI Vendor Selection Playbook.
Every vendor sounds brilliant in the demo. This is how you separate signal from noise before you sign anything.
After this lesson you'll know
- The 7 red flags that disqualify an AI vendor immediately
- A structured demo checklist you can bring to any sales meeting
- How to negotiate AI contracts without getting locked in
- The build-vs-buy decision matrix for executive teams
The AI vendor market is a minefield.
There are now over 14,000 AI startups competing for your budget. Most of them are wrappers around the same foundation models you could access directly. Some are genuinely transformative. The difference between a $200K mistake and a 10x productivity gain often comes down to how you evaluate before you buy.
The playbook below is battle-tested. It comes from watching organizations make every possible vendor mistake and distilling the patterns into a repeatable process.
7 red flags that should end a conversation.
If they won't tell you what model they're built on, they're hiding something. Most enterprise AI tools use OpenAI, Anthropic, or open-source models underneath. That's fine. Lying about it isn't.
Ask: "What happens to our data after we cancel?" If the answer is vague, walk away. Your data should be exportable, deletable, and never used for training without explicit consent.
"Our customers see 400% ROI" means nothing without knowing who, how, and over what timeframe. Demand case studies with named companies and verifiable metrics.
Any vendor confident in their product will let you test it on real data for 30-90 days. Annual contracts with no trial period are a red flag.
AI costs are dropping every quarter. If a vendor's pricing model gets dramatically more expensive as you scale, their economics don't work. You'll be paying for their inefficiency.
No responsible AI vendor makes this claim. AI augments teams. Vendors who promise to eliminate headcount are selling a fantasy and setting you up for implementation failure.
If they're handling your enterprise data without SOC 2 Type II, ISO 27001, or equivalent certification, they're not ready for enterprise customers. Full stop.
Your AI demo checklist.
Bring this to every vendor meeting. Score each item 1-5. Any vendor scoring below 30/50 doesn't make the shortlist.
Does it connect to your existing stack? CRM, ERP, data warehouse? Native integrations beat "we have an API" every time.
How long from contract signing to first measurable result? Anything over 90 days for a SaaS tool is a warning sign.
Run their tool on 100 real examples. Measure accuracy yourself. Don't trust their benchmarks.
Can you see WHY the AI made a decision? Black-box AI is unacceptable in regulated industries and risky everywhere else.
What happens when the AI gets it wrong? Is there a human escalation path? How does the system learn from mistakes?
Can you set guardrails, restrict data access, manage permissions? Enterprise AI without governance features isn't enterprise-ready.
Who helps when things break? Dedicated CSM? 24/7 support? Community forum? Match the support level to your team's technical maturity.
Where is the product going? How do they handle model upgrades? A vendor that won't share their roadmap doesn't trust you as a partner.
How easy is it to leave? Data portability, contract flexibility, migration support. The best vendors make it easy to leave because they know you won't.
Talk to at least two current customers in your industry. Ask what surprised them. Ask what almost made them cancel.
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