Dawn Sizer Talks AI Vendor Vetting with CRN: Don't Let Three Chatbots in a Trench Coat Sell You AI

Her core framing: choosing an AI vendor deserves a materially higher bar than a normal vendor decision, because if the tool fails, recovery isn't simple. She pushed the room past buzzwords and vague answers, toward direct questions: does this vendor have real AI engineers on staff, or is it a handful of bolted-together tools? How many other MSPs has it actually worked with, since many claiming "we've got AI" have worked with none?

Funding runway, who's backing the company, and whether it's built to scale or built to be acquired all matter as much as the product itself.

Country of incorporation, whether data leaves the country, who owns it once it's in the system, and how many hands client data passes through along the way, these aren't fine print. They're front-page questions. If a vendor can't sketch its own architecture, even roughly, that's a reason to walk away. She also raised a plainer operational question: how does the AI get stopped if it misbehaves?

A second MSP CEO quoted in the same piece, Travis Woods of Fort Point IT, echoed the same call for deeper vendor transparency.

Covered by CRN.