STIVGUIDE
AI agents for business: what they can and can't do
A plain guide to AI agents for business: what an AI agent is, the work it handles well today, where it still needs people, and how to start safely.
THE SHORT ANSWER
An AI agent for business is software that can carry out multi-step work toward a goal, such as qualifying a lead, reconciling an account, or preparing a contract review, using the company's systems and data. Agents handle preparation and routine steps well; people still need to own judgment calls, relationships, and consequential decisions.
What makes it an agent, not a chatbot
A chatbot answers a question. An agent works toward an outcome: it reads from connected systems, decides on next steps, prepares outputs, and can take actions within the permissions it has been given.
Work agents handle well
- Collecting status from many sources into one briefing.
- Qualifying and routing inbound requests against clear criteria.
- Drafting follow-ups, replies, and reports for review.
- Comparing documents against a playbook and flagging deviations.
- Reconciling records and flagging variances.
- Watching workflows for delays and repeated manual steps.
Where people are still needed
- Decisions with real financial, legal, or reputational consequences.
- Relationships and negotiations.
- Situations the company has no rules or precedent for.
- Setting the policies, playbooks, and limits agents follow.
How to start safely
- Pick one workflow with clear rules and a measurable outcome.
- Give the agent read access first, then narrow write access.
- Require approval for anything external or financial.
- Review the audit trail before widening what the agent may do alone.
Where STIV fits
STIV provides AI agents for seven business divisions, run from one command center with approval gates and an audit trail. Companies can start with one division and expand when results support it.
Questions, answered
Will AI agents replace employees?
In practice they take over preparation and routine steps, so people spend more time on decisions and relationships. Whether that changes headcount is a business decision, not something the software decides.
What data do AI agents need?
Access to the systems involved in the workflow, scoped to what the role requires. Starting read-only limits risk while the team evaluates results.
How long does it take to see results?
It depends on the workflow. Starting with one well-defined process makes results easier to measure early.