Your team probably already uses AI to write parts of RFP responses. An AI agent takes on the steps around the writing: it screens new opportunities, builds the requirements checklist, and assembles the experience and CVs for your proposal lead to review.
Chat-based AI is now common in the industry. In BST Global's 2025 survey of architecture, engineering and construction leaders, 73% said they regularly use generative AI at work, and Deltek's 2025 Clarity study found proposal development was the industry's top use of AI. In practice that usually means someone opens a chat window, pastes in part of an RFP, asks for a section, and copies the result back. Each bid starts from scratch, and the steps in between are still done by hand.
That's the gap the Bank of Canada described this year: personal use of AI among Canadian business leaders is widespread, but operational use, where AI is built into how the work gets done, is still limited. More than three quarters of the leaders in BST Global's survey believe 20% or more of their work tasks could be automated.
What's the difference between AI chat and an AI agent?
A chat tool waits for someone to ask it something. An agent is set up once to carry out a defined task on a schedule, using your firm's own material, and hands the result to a person to approve.
For RFPs, an agent can work like this:
- Each morning it reads the bid alert emails your firm already receives and summarizes new opportunities against your go/no-go criteria, such as project type, size, location and deadline.
- When you decide to bid, it reads the RFP and any addenda and builds the requirements checklist: what's being asked for, the format, page limits and key dates.
- It searches your past proposals, CVs and project sheets, picks the closest matches, and assembles the relevant-experience section and tailored CVs in the client's format. When something is missing, such as a required role with no matching CV, it flags it.
- After each submission it records what was used, so the library stays current for the next bid.
Your proposal lead reviews everything, makes the changes and decides what goes in. The agent doesn't submit anything, and it won't invent a project or a credential.
Does proposal content leave our systems?
No. The agent runs inside the AI tool your firm already uses, for example Microsoft Copilot with your Outlook and SharePoint, or ChatGPT with access to your project folders, under the agreements you have now. It works best when past proposals and CVs sit in one folder the tool can read, so gathering them is usually the first step.
How do you know it's working?
Treat it as an investment you can measure. Record a baseline on your next few bids, then compare once the agent is running:
- Hours from a new alert to a go/no-go decision
- Hours per proposal on the sections the agent assembles
- How much your proposal lead changes what the agent prepares
- RFPs your team responds to per quarter
The last one matters most over time, because more bids from the same team is where the return shows up.
Where should a firm start?
Choose one RFP type you see often, such as municipal infrastructure or institutional renovations. Gather five or six past proposals of that type and your current CVs, set the agent up on your bid alerts, and run it on the next two opportunities with your proposal lead reviewing each step.
Sources BST Global AI and Data Insights Report 2025; Deltek 46th Clarity A&E study (2025); Bank of Canada: Survey evidence on firm AI adoption (2026).