An AI agent is a program built around a language model that can take steps on its own: read a document, look up records, compare numbers, and draft an output or action. Unlike a chatbot that only answers questions, an agent works through a task, using tools and data it’s been given access to. How useful it is depends on what data it can reach and what it’s allowed to do.
Why it matters
Much of construction admin is repetitive checking: matching invoices to POs, chasing lien waivers, drafting RFI logs, flagging budget overruns. Agents can do the first pass on that work. But they can be wrong, so in finance and contracts they should propose, and people should approve.
Worked example
Illustrative: an agent reviewing this month’s AP on Riverside Medical Center finds INV-4471 ($48,200) exceeds PO-118’s remaining commitment by $6,150, notices Volt Electric’s 26 Electrical cost code is already 4% over budget, and sees lien waivers missing from Apex Steel and CoreDry. It drafts a hold on the invoice, a note to the PM, and waiver requests, and waits for approval.
Common mistakes
- Giving an agent write access to financial records with no approval step.
- Pointing an agent at disconnected systems and expecting reliable answers.
- Not logging what the agent did and who approved it.
How os.construction handles it
We’re building agents that work on the same data core as PM and accounting, draft actions, and wait for a person to approve them. They’re in development with founding contractors.