When customers ask about AI, give them a ranked plan, not a product list

Use Case Foundry gives managed service providers a repeatable way to find which AI work each customer should fund first, with the reason behind every rating. It also writes down what must be in place before that work starts, such as governance and monitoring, data access, and integration, which is usually the MSP's work.

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How it works for one customer

From first read to scoped project.

Step 1

First read: run a free pre-assessment from the customer's website and public information, before the first meeting.

Step 2

Validate: use the customer meeting to confirm workflows, costs, data access, and constraints instead of rebuilding basic context.

Step 3

Rank: every opportunity is rated for value, practicality, company advantage, and evidence quality, with the written reason and the conditions before a pilot.

Step 4

Scope: the MSP turns the prerequisites and the pilot the customer selects into a project, delivered with the vendors it already works with.

What the ranking hands to the MSP

The work that has to come first is usually yours.

Governance · contact-center sample

Evaluation and monitoring guardrails — Every automation option in the 41-opportunity ranking depends on it, because a wrong automated answer creates complaints and regulator escalation.

Data access · contact-center sample

Get the outage feed shared first — A $700,000-a-year pain waits because the data sits with a team that has not shared it. The first project is access, not a bot.

Integration · contact-center sample

Platform and CRM integration — Marked as implementation-partner work, because interface mapping is required before the selected pilot can run.

Governance · finance sample

Guardrails before anything posts — Required before any AP or close automation is allowed to post, because a wrong posting causes direct client loss.

Ranked low · finance sample

General support assistant — Ranked 20th of 22. No recorded pain supports it, so being easy to deploy does not make it the first project.

Where AI conversations stall

Customers are asking for AI guidance. Without a structured way to answer, the conversation becomes a product demo or a licence discussion, and it stalls when the budget holder asks what it will return and what has to change first. Doing proper discovery for every customer is consultant work that most MSPs are not staffed for.

What the MSP gets for each customer

A first read from the customer's website and public information, before the first meeting. See the sample pre-assessment.
A ranked roadmap with four ratings for every opportunity, the written reason behind each, and what must be true before a pilot. See the contact-center and finance samples.
The prerequisites, written down: the governance, data access, and integration work each opportunity depends on, tied to the business case that justifies it.
A pilot package for the opportunity the customer selects, ready for the delivery team.

What stays with the MSP

The customer relationship, the project, and the fee. White-label assessments are available per named customer.
Product choice. Use Case Foundry ranks the work, not vendors. Which products deliver the prerequisites and the pilot stays with the MSP and its distributor.
Delivery. Integration and deployment are marked as partner work, not done by Use Case Foundry.

For distributors

A distributor can offer this to its MSP partners as AI enablement: the same discovery method across partners and, for each customer, a written list of prerequisites and pilot requirements before vendor selection starts.

Best fit

MSPs whose customers are asking about AI beyond licences, who have someone able to lead a customer conversation, and who can deliver data, governance, security, or integration projects.