SIAM meets AI: your next vendor never sleeps and never shows up to the service review.

Most IT organizations already struggle to hold multiple MSPs accountable. Now add AI platforms, each with its own roadmap, its own pricing model and its own definition of “resolved.”

When something breaks, the MSP blames the platform, the platform blames the data, and the business blames IT.

I’ve seen the fix work. I restructured a $20M managed-services contract around a formal SIAM (Service Integration and Management) model, aligning every supplier to shared milestones, KPIs and monthly and quarterly service reviews. Later, governing an MSP under an SLA-tied model, the same discipline exposed and closed a service-credit gap.

AI vendors belong in that model. Here’s how I’d bring them in:

1. One integrator, one scorecard. Whoever owns service integration owns the AI vendor too. No side deals.
2. Contract for outcomes, not licenses. Resolution rates, accuracy and user satisfaction, with service credits when they slip.
3. Share KPIs across the chain. If the AI handles a request badly and the MSP inherits an angrier user, both should see it in the same review.
4. Plan the exit on day one. Your knowledge, your data and your workflows should leave with you.

AI doesn’t remove the need for vendor management. It adds a vendor that works around the clock and only attends the service review if you make it.

Next and last in the series: the metrics that matter now.

Leaders running multi-vendor environments: are your AI vendors held to SLAs yet, or are they still “just software”?