STIVGUIDE
How to roll out AI agents in your company
A step-by-step plan for rolling out AI agents across a company: choosing the first workflow, setting permissions and approvals, measuring results, and expanding without losing control.
THE SHORT ANSWER
Roll out AI agents one workflow at a time: choose a high-value process with clear rules, connect only the systems it needs, require approval for consequential actions, measure results against a baseline, and widen the agent's scope only when the record shows it is reliable.
1. Choose the first workflow
- Repetitive enough that preparation takes real time.
- Clear enough rules that a reviewer can judge the output quickly.
- Measurable, with a baseline you can record before starting.
- Owned by one team that wants it to work.
2. Set permissions and approvals
Connect only the systems the workflow needs and scope access to the role. Decide in advance which actions need approval and who approves them. Anything external or financial should start with approval required.
3. Run it with review
For the first weeks, have the agent prepare and propose while people approve, edit, or reject. Every edit is information about where the playbook needs to be clearer.
4. Measure against the baseline
- Time from request to completed work.
- Share of outputs approved without edits.
- Errors caught at review, and errors that got past it.
- Time the team spends reviewing compared with doing the work by hand.
5. Expand deliberately
Widen pre-approved activity for action types with a consistent record, then add the next workflow or division. Keep one approval model and one audit trail as you grow, so control doesn't fragment across tools.
Where STIV fits
STIV is built for this path: start with one division, approval gates and an audit trail from day one, and expand to more divisions, or STIV Unified, when the results support it.
Questions, answered
Which department should start first?
The one with a repetitive, rules-based workflow and a team that wants it. Finance reconciliation, sales follow-up, and support triage are common starting points.
How do we get employees to trust AI agents?
Keep people approving consequential actions, show the sources behind every draft, and widen autonomy only when the record supports it.
Should we build our own agents or buy?
Building gives full control but requires ongoing engineering for permissions, approvals, and auditing. Buying makes sense when those controls are what you need most.