Evaluating AI vendors is like speed dating with Fortune 500 consequences. Get it wrong, and your data leaks, your budget bleeds, and your team is stuck explaining “why the chatbot keeps crashing.” Get it right, and you've got an edge that scales faster than your competitors can Google “What is an LLM?”
Here’s how business leaders—especially in sales, marketing, and operations—can sniff out the real deal from the vaporware in five no-BS categories.
1. Use Case Fit: Does It Solve Your Actual Problem?
AI isn't magic. It’s math wrapped in marketing. So start with your use case.
- Manufacturing: Does the AI optimize supply chain lead times or just create fancy dashboards?
- Product companies: Does it reduce churn or just send you alerts about churn?
- Service firms: Does it increase utilization or just generate insights you already knew?
Ask vendors:
“Show me how your system solved this exact problem—on budget—for someone in my industry.”
2. Data Strategy: Who Owns It, Touches It, and Trains With It?
If your data is the new oil, don’t give the refinery away.
- Can you keep your data private and portable?
- Is their model being trained on your data? If yes, for whose benefit?
- Do they support your compliance needs (e.g. HIPAA, GDPR, SOC 2)?
Ask vendors:
“How do you handle model retraining, data isolation, and customer-specific outputs?”
3. Integration & Time-to-Value: Does It Play Nice and Deliver Fast?
You want AI that plugs into your CRM, ERP, or workflow tools without an army of consultants.
- Do they have real APIs or just promises?
- How long to get a basic use case live?
- Can your internal team support it after go-live?
Ask vendors:
“What’s your average customer onboarding time, and can I talk to one?”
4. Transparency & Explainability: Is It a Black Box or a Control Tower?
Executives need more than “the model said so.”
- Can it explain why it made a decision?
- Are there controls for bias, hallucinations, or rogue automation?
- Do they offer audit trails?
Ask vendors:
“Can I see how the model arrived at a recommendation—in plain English?”
5. Vendor Stability & Roadmap: Are They Built to Last or Built to Flip?
There’s a graveyard of AI startups with slick decks and no traction.
- Do they have customers you've heard of?
- Do they show year-over-year revenue growth?
- Are they venture-funded with a 12-month runway or profitable?
Ask vendors:
“What percent of your revenue comes from customers like me—and what’s your churn rate?”
AI Prompts
Use these ChatGPT prompts to get sharper before signing that contract:
- Create a vendor evaluation scorecard for AI tools used in sales enablement.
- What questions should I ask an AI vendor before integrating into our CRM?
- Evaluate the top 3 vendors for AI-powered customer support in B2B SaaS.
- Compare the risks and benefits of hosted vs on-premise AI models.
- Build a 10-question RFP for evaluating AI vendors for marketing automation.
Final Thought
Choosing an AI vendor isn’t just a tech decision—it’s a leadership one. You’re betting part of your operation’s future on their stability, your data’s safety, and their ability to drive measurable results. Demand specifics. Ignore buzzwords. And if they can’t show ROI in 90 days, walk.
|
Previous |
Next |
