> For the complete documentation index, see [llms.txt](https://docs.themspkb.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.themspkb.com/ai-for-msps/ai-in-the-msp-stack/where-were-going/positioning-and-preparation.md). # Positioning & Preparation ### Introduction MSPs can't win on AI by being “first.” The opportunity is to be the **trusted partner who makes AI safe**: governed, explainable, and client-ready. SMBs will lean on their MSP not for AI hype, but for assurance that new tools won’t create compliance, liability, or trust problems. *** ### **Strategic Positioning** **MSP Opportunity:** Position as the "safe AI adoption partner" for SMBs by: * Providing governance expertise clients lack internally * Managing AI vendor relationships and compliance * Offering hybrid human+AI service delivery models * Building AI literacy among client staff *** ### **Preparation Framework** **Policy:** * [ ] Draft AI Acceptable Use Policy * [ ] Create client AI disclosure template * [ ] Document shadow AI detection **Vendor:** * [ ] Audit all AI features in stack * [ ] Review DPAs for training opt-outs * [ ] Negotiate liability + residency terms **Staff:** * [ ] Train on **output verification** (not just prompts) * [ ] Add AI steps to incident response * [ ] Run tabletop exercises for AI misfires **Ongoing:** * [ ] Track false positives and misses * [ ] Log AI-assisted actions for audit * [ ] Maintain manual fallback for critical workflows *** #### Bottom Line MSPs win client trust not by selling AI as revolutionary, but by proving **it won’t outpace accountability.** Strategic positioning is simple: govern it, explain it, and keep people in the loop. The MSP that makes AI safe is the MSP that keeps the client. {% hint style="info" %} These steps respond directly to the regulatory, audit, and vendor trends outlined in [**Where We’re Going**](/ai-for-msps/ai-in-the-msp-stack/where-were-going.md) {% endhint %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.themspkb.com/ai-for-msps/ai-in-the-msp-stack/where-were-going/positioning-and-preparation.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.