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By Brian Powell, Global AEC Account Manager
This article was originally published in SMPS The Marketer, here.
Ask any senior proposal professional at a leading AEC firm what changed in the last two years, and the answer is not what you might expect. RFP volume is climbing, but the time spent per proposal is going down. Not because people are cutting corners, but because they are spending less time on boilerplate, reformatting, and hunting through shared drives for the right CV version. By leveraging AI to win back that time, proposal professionals are spending more of it on writing that speaks directly to the client’s needs. And because of that, these teams are winning more.
The firms pulling ahead are not doing it by hiring bigger proposal teams or working longer hours. They are doing it by leveraging AI to eliminate the rote tasks that have always competed with the work that actually wins RFPs: understanding the client, building the strategy, and crafting a response that demonstrates genuine expertise. AI-enabled proposal tools are what made that shift possible. But the technology is only part of the story.
The Pressure Behind the Shift
The volume pressure on BD and proposal teams is real and growing. Half of all organizations reported an increase in RFP volume in 2024, with pitch volume up year-over-year at 54% of firms1. For AEC specifically, the complexity compounds: the average RFP takes 16 days to complete —nearly double the cross-industry average of 9.3 days — and a median of 50 people contribute to a single response.
More volume, more complexity, and the same finite hours. Something has to give. For years, what gave was the quality of the thinking. Proposal managers spent their best hours on mechanics: assembling documents, chasing subject matter experts, reformatting CVs that lived in seventeen different versions across shared drives—and whatever time remained went to strategy and narrative. That equation is now reversible.
What AI Is Actually Freeing Up
The clearest near-term value in AI proposal tools is in structured, repeatable content. The sections that consume disproportionate time without ever being where submissions are won. Personnel sections, project descriptions, boilerplate qualifications. These are tasks where the firm’s existing experience should be the answer, and where the bottleneck has historically been the time required to locate, format, and tailor it.
When that content lives in a governed, structured library that AI can draw on with appropriate access controls, the math changes. A personnel section that previously required hours of manual extraction and formatting can now be produced in a single working session — 70 to 80 percent complete, ready for technical review rather than built from scratch. That time does not disappear. It moves to where it should have been going all along.
The industry data reflects this. Firms using AI-powered proposal management software reported a 72% positive impact on time spent completing requests, 66% improvement in response quality, and 64% faster time to personalize submissions. AEC firms in particular have moved quickly: 90% are using generative AI for researching and summarizing content, 80% for writing bios, and 70% for executive summaries.
The Work That Has to Happen First
Here is what the software vendors will not always tell you upfront: the efficiency gains do not arrive automatically. They arrive after you have done the organizational work that makes them possible.
Every firm that has gone through a serious implementation has encountered the same discovery phase. Content that has never been properly governed. CVs in inconsistent formats across dozens of offices. Processes that exist in people’s heads more than in documented systems. Confidential project data sitting alongside general content without clear access boundaries. None of that was created by AI. All of it is exposed by it.
GHD, the global engineering firm, encountered this directly. What began as a project to accelerate proposal drafting became a broader exercise in data governance and cross-functional alignment—pulling together proposal operations, IT, information security, and risk management in ways those teams had never previously needed to coordinate. The lesson, as their team put it: the internal alignment required turned out to be just as important as the alignment with the vendor2.
The firms that treat this discovery phase as part of the value move through it faster and build on a foundation that holds. The ones that skip it spend the better part of their implementation discovering what they should have known at the start.
Speed Alone Does Not Win RFPs
Capacity and efficiency matter—but they are inputs, not outcomes. The median new business win rate in AEC sits at 37%, while existing client win rates are substantially higher at 62%. That gap reflects what clients are actually evaluating: not whether you produced a compliant document on time, but whether you understand their project well enough to be trusted with it.
AI does not win RFPs. The people who understand the client do. What AI does, when it is leveraged well, is give those people back the time to do that work. When a BD director is not spending three evenings reformatting CVs, they are available to sharpen the strategy and write the section of the proposal that reflects genuine understanding of the client’s challenge. That is the shift worth pursuing—not faster proposals, but better ones, produced by people who finally have the time to make them better.
The firms that will pull ahead are not simply the ones that deployed AI first. They are the ones that used it to redirect their best people toward the work that actually determines who wins.
About the Author:
Brian Powell is the Global AEC Account Manager at ikaun, where he leads account strategy and client engagement for architecture, engineering, and construction firms worldwide. With close to a decade in the AEC industry — including prior experience at BST Global — Brian brings deep familiarity with the enterprise systems, operations, and business development workflows that AEC firms rely on day to day. At ikaun, he partners with firms across the globe to connect proposal strategy, knowledge management, and AI-enabled technology in ways that drive measurable impact on how teams win work.
References
1. 2025 Benchmark Research Report
2. PM Forum – Winning Work In the Age of AI
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