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Answers to the questions companies ask about AI agents: what they need, when they may act alone, who is accountable, and what the law asks.

• What an AI agent needs to do real work

  Why a chat tool does not finish the job, and what a knowledge worker needs: your language, its own records, tools, access, rules and limits, a logbook, and an operator who signs off.

• The data foundation, explained

  Pipelines bring data from the systems you already run into one warehouse in your own cloud, and every figure traces back to its record.

• When may an AI agent act on its own?

  A step of an AI agent's work may act alone once it has proved reliable on four tests. Some steps always go to a person.

• Who is accountable when an AI agent makes an entry?

  When an AI agent prepares or posts an entry, the company stays accountable, through management and the operator. What the law says, and how to show it.

• What does the EU AI Act ask of a company that uses AI?

  For everyday use of AI at work, one duty applies today: support your staff's AI literacy. Heavier rules apply only to high-risk uses, from December 2027.

• What are guardrails for an AI agent, and who enforces them?

  Guardrails are the limits an AI agent cannot cross, enforced outside the model in access rights and code.

• What are evals for an AI agent, and how do you use them?

  Evals are repeatable tests that run an AI agent on known cases and check the result. What to test, when to run them, who owns them, and how cases grow.

• What is structured output, and why does an AI agent need it?

  Structured output makes an AI answer in fixed, named fields a system can read and check. How it works, how to check it, and what it does not guarantee.

• What is an agent harness, and why does it matter?

  An agent harness is the software around an AI model that gives it instructions, tools, access, memory and a working loop. What it decides, and how to choose.

• What are tools for an AI agent, and which does it need?

  A tool is a function an AI agent can call, such as reading the ledger or creating a draft entry. How tool calls work, and which tools a finance agent needs.

• What is an AI foundation, and why build it first?

  An AI foundation is everything your agents need to know about your company, written down so AI can use it. What goes into it, and why it comes first.

• What is AI infrastructure for a small company?

  AI infrastructure is the setup that lets AI agents do real work in your systems safely. What each part is, who controls it, and what to set up first.