Managed AI vs MSP AI add-ons vs AI consultancies
Three ways to get AI into a 30–500 person company, compared on what you actually receive, who runs it after launch, and how the bill is shaped.
Managed AI vs MSP add-on vs consultancy comes down to who builds the workflow and who runs it afterward. Your MSP's AI add-on usually means platform seats (Copilot or a secure chat workspace) plus the security around them. A consultancy builds something and hands it over. A managed AI provider builds workflows into your systems and keeps operating them for a monthly fee. They can work together.
If you run a 30–500 person company, you may already have two of the three in some form: an IT provider that has started offering AI, and a consultant or vendor who pitched a project. This post sets the three options side by side so you can see what each one delivers, what each one leaves to you, and where they overlap. For the definition of the service model, see What is managed AI operations?.
What does your MSP's AI add-on actually include?
AI is now a standard line on the MSP menu. Informa's 2026 MSP 501 survey of more than 600 providers found that 91% of MSPs offer or use AI, up from 79% the year before, according to Channel Insider's coverage. Distributors are building for it too: Pax8 has announced what it calls "Managed Intelligence", tooling for MSPs to deliver AI across their small-business clients.
In practice, the add-on most companies get today looks like this:
- Licensing. Microsoft Copilot seats, or seats on an AI platform the MSP resells.
- Security and governance. Data loss prevention, sign-in policies, and controls over which tools staff can use.
- Rollout and training. Turning it on, a lunch-and-learn, help-desk tickets when it misbehaves.
That is valuable work, and it is squarely the MSP's job. Your IT provider already owns your tenant, your identity setup, and your devices. Nobody is better placed to turn on AI safely.
What it usually does not include is custom work against your own business processes: pulling quote data from email into the ERP, reviewing contracts against your clause library, answering staff questions from a specific SharePoint library with the right permissions, then watching that workflow every week. The same survey reports that the share of MSPs providing custom AI solutions grew from 21% to 36%. Growing, but still a minority. Custom build and run work needs people most MSPs have not hired.
What does an AI consultancy deliver?
An AI consultancy diagnoses, recommends, and often builds a pilot or a first system. The deliverable is a roadmap, a prototype, or a working build, plus documentation. Then the engagement ends.
That handover is the point of the model and also its weak spot. After handover, someone on your side owns:
- Hosting and the cloud bill.
- Monitoring the workflow for silent failures, not just checking that the server is up.
- Testing replacements when a model provider retires a version.
- Fixing connectors when Microsoft or Google changes a permission setting.
- Answering "why did it do that?" from the logs.
If you have engineers whose job is running production systems, that is fine. Most 30–500 person firms have a controller, an ops manager, and an MSP. The consultant's build becomes a ticket nobody can close.
What does a managed AI provider do differently?
A managed AI provider builds and operates. The same team that finds the workflow builds it into Microsoft 365, Google Workspace, SharePoint, Teams, or your line-of-business systems, then hosts, monitors, updates, and supports it month to month.
At West Palm AI, that covers:
- Finding the workflows worth automating, starting with a free AI opportunity assessment.
- Building them into the systems you already run.
- Connectors that bring your company data into the ChatGPT, Claude, or Copilot your team already uses, respecting existing permissions.
- Hosting, monitoring, model and security updates, and integration maintenance.
- Usage and cost oversight, with expected model usage included in the quote.
- Business-hours support, a monthly value report, and a quarterly review.
What we do not do: general IT help desk, devices, networking, or identity administration. Those stay with your MSP.
Who owns what after launch?
This is the question that separates the three options. Picture the AI workflow failing on a Tuesday afternoon.
- MSP add-on. The MSP owns the platform: licensing, access, security. If the issue is a seat or a policy, they fix it. If it is a custom workflow someone built on top, it is usually out of scope.
- Consultancy. After handover, you own it. The consultant may help on a new statement of work.
- Managed AI provider. The provider owns the AI layer and is on the hook for the fix. You own the work, the data, and the access rules. Your MSP still owns the IT environment underneath.
The cleanest arrangement has no gaps: the MSP owns the tenant and identity, the managed AI provider owns the workflows running inside it, and your team owns the business decisions.
How is each one priced?
- MSP AI add-on. Usually per seat, per month, on top of your existing IT agreement, sometimes with a project fee for rollout. The seat price often tracks the platform's list price plus a margin.
- AI consultancy. A fixed-fee or time-and-materials project, sometimes followed by a retainer for changes. The large number comes first.
- Managed AI. One monthly fee that covers the build and the operation. West Palm AI's starts at $6,000/month, with no paid discovery project, the first workflow live within 30 days, and a 90-day opt-out. The fee rises with workflows, connected systems, and expected usage.
For a full breakdown of managed AI pricing and how to compare quotes, see How much do managed AI services cost? and our pricing page.
When is each option the right call?
Your MSP's AI add-on is right when the goal is safe, general access: everyone gets an assistant, the data stays governed, and nobody is pasting client files into a free consumer tool. Start here if you have not.
An AI consultancy is right when you have engineers who will own production systems after handover, or when you need a one-time study rather than a running system.
Managed AI is right when you want specific workflows built into your systems and want someone else to keep them running, without hiring an internal AI team. If you are weighing that against a hire, read Managed AI vs hiring an AI team.
Many companies need the first and third together. That is the setup we prefer.
How can an MSP and a managed AI provider work together?
The pattern shows up in partner conversations. One of the first replies to our MSP partner outreach this month came from an owner whose firm had just started reselling an AI platform to its clients. The question was polite and direct: they already had AI covered, so what did we have in mind?
Our answer was that the platform is the best possible starting point, not competition. It gives clients seats and a secure place to use AI. What usually comes next is a client asking for something specific, such as quotes, invoices, or intake forms pulled straight into their ERP or CRM, or an agent that works against their own documents. That is custom build work, and then someone has to keep it running. Most MSPs do not want to staff for that.
So there are two ways to partner:
- Referral. The MSP introduces clients who want more than the platform covers. We scope, build, and run the managed AI service, and the MSP earns a share of first-year fees. The MSP keeps the relationship and the infrastructure.
- White-label. We deliver the managed AI service under the MSP's brand as part of its AI offering.
Either way, the MSP has more to sell alongside the platform without hiring for it, and the client gets one coherent setup instead of three vendors pointing at each other. The partner program is laid out on the MSP page.
Where to start
If you are a business owner, ask your MSP what its AI add-on covers after launch, and ask whether it partners with anyone for custom workflows. If you would rather start with us, Book a workflow call. The first step is a free assessment of where your team's time goes. If you prefer to write first, use the work-with-us form.
If you run an MSP, the MSP page explains the referral and white-label options. West Palm AI is based in West Palm Beach, Florida, and partners with providers across the US. The about page covers who you would be working with.