How does a services business use AI without commoditizing what it sells?
By automating delivery overhead rather than delivery judgment. Proposal and SOW drafting, time and project reporting, knowledge capture from engagements, and the service desk load if you run managed services. For MSPs specifically there is a second opportunity: building an AI practice you sell to your own clients, which 48% of MSPs say clients want and only 13% currently earn meaningful revenue from.
- Increase revenue
- Improve operational efficiency
- Reduce cost
Professional Services & MSPs
Automate the overhead, not the judgment
A services business sells judgment. Automating the judgment commoditizes the thing you charge for, which is the real risk in this sector and the reason many firms have hesitated.
The overhead around the judgment is another matter. Proposals rewritten from scratch when a similar one exists. Knowledge that leaves when the consultant rolls off. Time reporting chased every Friday.
What we build
Proposal and SOW drafting from prior engagements and your methodology, with the partner editing rather than starting from a blank page. Turnaround and win rate both move.
Engagement knowledge capture, so the next team inherits what the last one learned. This is the asset most services firms believe they have and do not.
Service desk triage, summarization, and documentation for anyone running managed services, where the sequence is triage first, governance before production, and a named approver on anything touching a client system.
The second opportunity for MSPs
Kaseya’s 2026 survey of more than a thousand MSPs found 48% ranking AI and automation as the top client need for 2026, while only 13% earn meaningful revenue from it. That gap is a practice waiting to be built: an assessment template you can run in a week, governance packages by client size, tiered runbooks, technician enablement, and a pricing model.
You own it and sell it under your name. We stay behind you on the engagements that need more depth than the template covers.
Typical projects
- Proposal and SOW drafting from prior engagements and your actual methodology
- Engagement knowledge capture, so the next team does not start from nothing
- Service desk triage, summarization, and documentation for managed services
- Time and project reporting assembled rather than chased
- For MSPs, an AI consulting and governance practice you deliver under your own name
The same work, by business function
How it starts
A three-week assessment scoped to this area: where the hours actually go, what is worth building, and what to fix first. You keep the findings whether or not there is a next part.