AI MSP Index — Directory of AI-Native MSPs

The AI MSP Index is the independent benchmark for AI adoption in managed services: the criteria that define an AI-native MSP, and the AI tools MSPs actually run on. Every entry below is a reviewed, published listing with its own page.

Launch the desktop

The definition

What is an AI-Native MSP? — the definition and the criteria for inclusion.

The AI-Native MSP criteria

An MSP qualifies for the index on at least one of these seven criteria. Each page sets out what the criterion means, what it looks like in a real operation, and what evidence we accept.

Product-led sales — Most MSPs are sold, not bought. A product-led MSP inverts that, and the inversion shows up in the contract long before it shows up in the marketing.
Automated onboarding — Onboarding is the most labour-intensive month of an MSP relationship and the one clients judge hardest. It is also the easiest place to see whether the automation is real.
AI-first ticketing — This criterion is about order of operations, not outcomes. Whatever the channel, the first thing that touches the ticket is an agent.
AI ticket resolution — Closing five per cent of tickets with AI is an improvement. Closing most of the Tier 1 volume is a different business model. This criterion is about which one you are running.
AI-maintained documentation — Every MSP has documentation. The question this criterion asks is whether it describes the environment as it is today, and what keeps it that way.
Margin and headcount — An MSP where the numbers are indistinguishable from a conventional shop is a conventional shop with better marketing.
Client transparency — Disclosure is now the criterion with a regulatory floor underneath it, and the floor is lower than what a client will actually ask for.