Construction is About to Leave $124B on the Table Due to Outdated Bidding

Technology First Read Construction is About to Leave $124B on the Table Due to Outdated Bidding Contractors must deal with a rapidly changing bidding environment, bidding AI startup founder Shiva Dhawan writes Somewhere right now, a contractor’s bidding window is closing while an invitation to bid sits unanswered in an estimator's inbox. Another contractor with a healthy backlog just passed on a qualified opportunity because no one had time to price it. I see this pattern constantly in my work with contractors who deploy Beam AI. Before a project can be built, it has to be found, quantified, priced, and bid. Yet, when estimating teams run out of capacity, projects don't just get delayed; they disappear. The work is never pursued, never won, and never becomes construction output. That makes preconstruction one of the industry's most overlooked capacity challenges. Output Is Lost Long Before Crews Mobilize Deloitte's 2026 Engineering & Construction Industry Outlook estimates that persistent labor shortages could cost the industry nearly $124 billion in lost output. The report highlights an urgent workforce challenge: construction needs nearly 500,000 additional workers this year, while the industry's aging workforce and shrinking talent pipeline make that increasingly difficult. As alarming as those numbers are, they tell only part of the story. The report assumes output is constrained only when labor is unavailable in the field. In reality, another capacity constraint emerges much earlier, during preconstruction. Long before crews are mobilized, estimating teams determine which opportunities will become projects. And this distinction matters because construction output doesn't begin when the first crew arrives on-site. It begins when someone translates drawings into quantities, quantities into costs, and costs into a competitive bid. Every project starts in preconstruction. Yet preconstruction has rarely been viewed as a strategic capacity function. Contractors meticulously track backlog, labor productivity, and project margins, but few measure a simpler question: How many qualified opportunities did we never have the capacity to pursue? Looking for quick answers on construction and engineering topics? Try Ask ENR, our new smart AI search tool. Ask ENR → Your Estimating Capacity Sets Your Revenue Ceiling For decades, that tradeoff was unavoidable because estimating remained largely manual. Advances in AI are beginning to challenge that assumption. Preconstruction platforms can now automate the repetitive tasks that consume experienced estimators' time — performing takeoffs, extracting quantities, reviewing drawings, and organizing project documents — so estimators evaluate more opportunities without sacrificing quality. Artificial intelligence changes the equation from "How many estimators do we have?" to "How much estimating capacity can we create?" Consider a masonry contractor in Wisconsin whose estimating team consistently capped out at roughly 25 takeoffs each month. That limit wasn't just an operational metric; it became a revenue ceiling. Every qualified opportunity beyond those 25 takeoffs represented work the company simply didn't have the capacity to pursue. The same pattern repeats, no matter the trade. For a drywall and demolition contractor, the bid volume dropped almost immediately after losing a key estimator, even though field operations remained unchanged. The real bottleneck wasn't labor; it was capacity upstream. After introducing AI into its estimating workflow, the company doubled its bid volume target, not by hiring additional estimators, but by removing much of the repetitive work that had constrained them. In both cases, the limiting factor was estimating capacity. Once that bottleneck was removed, the firms were able to pursue more business. Count How Fast You Convert Demand Into Bids Construction productivity has focused on field execution: labor hours, equipment utilization, prefabrication, and schedule performance. Those metrics remain essential, but they capture only part of the equation. In today's market, productivity must also include how efficiently contractors convert demand into bids. Every unanswered invitation to bid represents lost capacity. Every opportunity declined because an estimating team is overloaded represents potential revenue that disappears before construction even begins. These losses rarely appear on a balance sheet, yet collectively they shape how much work the industry is capable of delivering. Measure The Work You Never Had Capacity To Pursue If productivity begins in preconstruction, contractors need better ways to measure it. That means looking beyond bids submitted and asking what prevented qualified opportunities from being pursued in the first place. Start with three questions: How many qualified bids went unanswered? How much estimating time was spent on repetitive work? How much revenue was left behind because capacity ran out before demand did? Once contractors begin measuring those questions, the next step becomes obvious. Automation increases the number of opportunities a business can realistically pursue. By shifting repetitive tasks to AI while preserving human judgment where it matters most, contractors can expand bid capacity without expanding headcount at the same pace. At the individual firm level, that means pursuing more work without a proportional increase in overhead. Across the industry, it means unlocking estimating capacity that has always existed but has never been fully utilized. Viewed through that lens, Deloitte's $124 billion projection is both a warning that construction needs more workers and a signal of a larger opportunity. The industry's next competitive advantage will come from expanding the capacity of every estimator already on the team, because long before labor shortages limit what gets built, estimating capacity determines what gets bid. Shiva Dhawan is co-founder and CEO of Attentive.ai, an AI-powered bidding startup.