With so many vendors layering “AI” into their solutions, how do you cut through the noise to differentiate between marketing and actual value?

I will suggest to start with only 3 vendors, invite them to do a PoT with specific needs for this shot, let your team evaluate and compare pros and cons for your tech environment, discover if you need more knowledge to fully adopt this IA solution

Cutting Through AI Marketing vs. Real Value

This is something I have been dealing with for myself and my clients for the past several months.   Here is how I think of it.  The "AI" label has become the new “low-fat” sticker of tech—plastered everywhere, but rarely telling you what’s actually inside. To separate real value from marketing gloss, I use three filters:
 1. Business Problem Fit
Start by asking: What specific business problem does this AI claim to solve, and how does it tie to measurable outcomes I care about? If the answer is vague—“driving productivity” or “unlocking insights”—that’s a red flag. True value comes when the vendor can show you where in your workflow their AI moves the needle, whether that’s reducing time-to-quote, improving forecast accuracy, or cutting support costs.
 2. Transparency of the Model
Vendors don’t need to open their entire kimono, but they should be clear about what’s under the hood. Is the AI embedded rules-based automation dressed up with an “AI” sticker, or is it leveraging machine learning or generative models? Ask for details about data sources, model training, and how it adapts over time. If they dodge, you’re likely dealing with marketing vapor.
 3. Proof in the Field
Ask for case studies and metrics that go beyond anecdotes. Have they documented productivity lifts, cost reductions, or customer satisfaction gains? Can they give you references from companies of similar size or industry? Pilots with measurable KPIs are the best way to smoke out hype.

My rule of thumb: If the vendor can’t explain in plain English how their AI makes your people faster, smarter, or cheaper without relying on buzzwords, then it’s probably lipstick on a pig.

That’s how I cut through the noise: focus on fit, transparency, and proof. The rest is marketing static.

Hope that helps.