AI automations & workflows
Where AI earns its place
Each one replaces assembly work with an automated draft, summary, or score - and keeps the decision with the person accountable for it.
How it's built
Automating an undefined process just produces the wrong output faster. Ownership, definitions, and data sources get fixed first.
AI drafts, summarizes, scores, and routes. Anything that reaches a customer or changes a forecast goes through a named human owner.
Most workflows run on your existing CRM, support desk, CS platform, and data warehouse. New tools are recommended only when the gap is real.
Each workflow ships with a baseline and a success measure - hours reclaimed, coverage gained, or signal caught earlier - before the next one is built.
How the engagement runs
Typically 4 to 8 weeks for the first workflows, depending on data readiness. Your team owns everything at the end.
Shadow the real workflow, measure where time goes, and inventory the systems and data each step depends on.
Score candidate workflows on time reclaimed, risk reduced, and data readiness. Pick the two or three that earn their place.
Design the workflow with explicit human checkpoints, build it on your stack, and pilot with a small group of CSMs.
Document, train, and hand ownership to an internal operator with a measure that shows whether it's working.
Common questions
That's not the goal this work is designed around. The aim is to take assembly work - summarizing, reporting, triaging - off your CSMs so their time goes to customer conversations that change outcomes. Whether that changes future hiring plans is a leadership decision made with real data after workflows are running, not a promise made up front.
Usually not to start. Most CRMs, support desks, and CS platforms now include AI features, and general-purpose language models connect to them through standard integration tools. The recommendation is vendor-neutral and might be to use what you already own, add a lightweight integration, or buy - whichever the evidence supports.
That's common, and it's one of the first things assessed. Some workflows - like summarizing call notes - work well on messy inputs. Others, like risk scoring, need agreed definitions first. Part of the work is sequencing the workflows so early wins don't depend on a data project that isn't finished.
Workflows are designed inside your existing security and vendor-approval process, using tools your company has already approved or approves during the engagement. Customer data handling, retention, and model-provider terms are reviewed with your security owner before anything goes into production.
It can be scoped on its own when the operating model is already sound. More often, the Blueprint identifies which workflows are worth automating, and this engagement builds them. Automating before diagnosing risks speeding up the wrong process.
Next step
Tell me where your team's time goes today. I'll tell you honestly which workflows are worth automating now - and which need a process fix first.