AI Agent
An AI agent uses a language model and connected tools to carry out multi-step tasks. For example, it can read a bid invitation, check it against go/no-go criteria, and create an opportunity in the CRM.
Why it matters in construction
Preconstruction includes many small but necessary tasks: logging an owner call in the CRM, moving an opportunity to the right stage, finding a client’s last three bids, or checking whether a requested superintendent is already committed. Those tasks add up, and CRM data often falls behind.
An agent can carry out those tasks rather than assist with only one step. It reads the email, determines what changed, updates the records, and reports its work. A person reviews the result.
How it works
- Goal. The agent receives an objective from a person, such as “prep the go/no-go packet for the Harbor Point RFP,” or from a trigger, such as a new email.
- Plan. The language model breaks the goal into steps: read the RFP, pull the client’s history, compare it with scoring criteria, and draft a summary.
- Tools. Each step uses a tool, such as a document reader, CRM query, calendar lookup, or file writer. The model can use only the tools it has permission to access.
- Check results. The model uses each result to choose the next step. If it cannot find a client in the CRM, it can flag the issue or create a contact if that action is allowed.
- Set guardrails. Limit the systems and actions the agent can access, require approval for risky actions, and log its activity.
- Report. The agent returns a summary of what it did and what remains unresolved.
Planning, acting, checking results, and repeating separates an agent from a single prompt. Reliability also depends on good tools, narrow permissions, and clear stopping rules.
Example in practice
Suppose a regional GC’s business development lead forwards an invitation to bid for a $14M charter school to the precon inbox. An agent picks it up. It extracts the owner, architect, bid date, and delivery method, finds the architect in the CRM with two prior projects and a $9M win, creates the opportunity, sets the stage to “Qualifying,” and runs the firm’s go/no-go rubric: known architect, within the sweet spot on size, bid date 19 days out, public work with a 10 percent bid bond.
It drafts a scoring summary of 71 out of 100, posts it to the precon channel, and adds the bid date to the calendar. On Monday morning, the precon director adjusts the self-perform score and makes the go/no-go decision.
Frequently asked questions
How is an AI agent different from a chatbot?
A chatbot responds to a question. An agent receives a goal, chooses steps and tools, carries them out, and stops when it has finished or needs a person to decide.
What can an agent actually do in a GC's systems?
Whatever tools it is connected to. Common examples are reading inbound email, updating CRM records, pulling project data from the ERP, drafting documents, and sending notifications. It cannot touch a system it has not been given access to.
Should an agent be allowed to act without approval?
For low-risk, reversible actions like logging a call or updating a stage, yes. For anything involving money, commitments, or external communication, most GCs require a person to approve before the agent proceeds.
Go deeper
- From the blog Agentic: What It Means, and What It Means for Construction A working definition of agentic AI for construction teams, plus the utility versus security tradeoff every GC should understand before buying.
- From the blog The Days of Manually Updating Your CRM Are Over CRM hygiene was a preconstruction discipline — logging calls, updating bids, chasing estimators. With a preconstruction AI agent, that category is gone.
- From the blog Why MCP Is the Most Important Acronym Since BIM Model Context Protocol lets AI agents operate your software instead of helping you operate your software. Here's why that matters to GCs.