Score readiness before asking the team to adopt AI
For a 75-person managed service provider, AI readiness is less about enthusiasm and more about operating clarity. The RSM middle-market AI survey shows middle-market AI adoption accelerating, while the OECD report on AI adoption by small and medium-sized enterprises emphasizes that smaller firms need process ownership, data quality, skills, and governance before tools become business value.
The assessment should score eight dimensions: workflow value, source-data quality, system access, permission boundaries, review rules, adoption friction, measurement clarity, and leadership ownership. That score tells the firm which workflow can safely move first.
Use the SMB AI readiness assessment as the base. The goal is not to slow down AI use. It is to choose the first workflow with enough control to survive production.
Choose a workflow with a human review path
The best first workflow for a 75-person managed service provider is usually repeated, text-heavy, and already painful: intake summaries, project status reports, vendor ticket summaries, knowledge search, proposal preparation, or client-update drafts. A readiness assessment should reject workflows where no one owns the output or the source data is scattered across uncontrolled channels.
The NIST AI Risk Management Framework gives the right operating frame: govern, map, measure, and manage. In plain terms, name the owner, approved sources, reviewer, exceptions, logs, and value measure before launch.
For managed service and IT-heavy teams, security controls matter early. CISA AI data security best practices and the NIST Cybersecurity Framework 2.0 are useful references for source access, permissions, and support workflows that may touch sensitive operating data.
Turn readiness into a production decision
The Deloitte State of AI report reinforces that AI value comes from process change. The assessment should end with one of three decisions: launch one governed workflow, fix readiness gaps first, or stop the proposed use case because value or risk is not clear.
The Gartner agentic AI project forecast is a useful warning against expanding into agentic AI before cost, value, data quality, and controls are clear. A 75-person managed service provider should prove one assistant workflow before moving to more autonomous coordination.
The next step is the 90-day implementation plan. Use it to move from readiness score to owners, controls, and weekly value checks.
