Rising construction costs, labor shortages and supply chain disruptions are increasing pressure on public infrastructure budgets and project management.
Public construction costs are ballooning in our cities.
This spring, construction materials were priced more than 50 percent higher than in February 2020, according to Associated Builders and Contractors, a national construction trade group. In the year to September 2026 alone, prices rose 11.2 percent, the biggest jump in nearly four years. Energy is adding to the bill too. Home electricity is expected to average about 18 cents per kilowatt-hour this year, roughly 37 percent more than in 2020. Those fuel and power costs end up in the bids that transit agencies, school districts and utilities have to pay.
Project risks are piling up as well. Tariffs on steel, copper and other metals keep supply chains unpredictable, and high borrowing costs make long projects more expensive to finance. The industry is also consolidating. Private equity firms and the biggest design companies are buying up mid-sized engineering and construction firms. Among the ENR 100, Engineering News-Record’s top-ranked design firms, the share that are employee-owned has dropped from 74 percent to 58 percent. Workers are hard to find, too. ABC says the industry needs 349,000 new workers in 2026 and 456,000 in 2027, mostly to replace people who are retiring. An owner must budget for the impacts from these risks.
Construction still runs more like a trade than an industry. Every bridge, tunnel and campus is one of a kind. Teams break up when the job ends, and lessons learned rarely become best practices for the next project. Data is rarely collected the same way from one job to the next. In a Dodge survey, 74 percent of U.S. contractors said their data quality was poor or only moderate. The vaunted, American Society of Civil Engineers still grades U.S. infrastructure a C, with roads and transit stuck in the D grade. At the same time, projects keep getting bigger and construction AI is growing fast. Procore and Autodesk both bought AI and field-data companies this year. But few leaders are showing how to use AI in project controls. In a survey of real estate and construction firms by RSM, a national consulting firm, about half of the companies whose AI pilots stalled said bad data was to blame.
That is why project controls matters so much right now. Integrated project controls puts cost, schedule and risk in one place. Transit agency owners get an early warning while there is still time to fix things, and solid backing for every dollar they ask a board, a regulator or the public to approve. When a project is set up with the right processes, dashboards and ongoing tracking, it builds a clean, consistent set of data. That data feeds the agency’s AI models, so its tools are dependable, usable and far less likely to hallucinate.
Transparency is just as important. Owners need dashboards that show the baseline next to what the project is actually costing, updated as work moves forward. Change orders, schedule logic changes and contractor performance each tell part of the story, and together they reveal how a project is really being built. Raw project data must be translated for decision-makers, turning thousands of line items into a clear picture a board can act on.
Saumil Maniar, a licensed Professional Engineer, has built his career on project performance. He is a Senior Director at PMA Consultants, an ENR-ranked national project management firm, where he has sharpened his trade in cost estimating, scheduling, risk management and change order negotiation for the MTA, the Port Authority of New York and New Jersey, the MBTA, LA Metro and the Federal Transit Administration. His work spans Grand Central Madison, the LaGuardia AirTrain, the Midtown Bus Terminal, the MTA’s congestion pricing program, a clean energy program, LA Metro’s Orange Line and Massachusetts’ East–West Passenger Rail. Programs like these generate huge volumes of building, cost, schedule and performance data, and when that data is captured well, it can transform how projects are delivered. A certified Professional Scrum Product Owner and Lean Six Sigma Green Belt, he brings an agile, systems approach to project controls, treating cost, schedule, risk and change as connected parts of one system that gets sharper with every update.
Experience like this is what the next wave of public investment needs. Budgets hold only when engineers who understand both the job site and the data are in the room when the next major project is planned.
Mr. Maniar built an integrated project controls framework that brings the cost estimate, cost breakdown structure, baseline schedule and risk register into one report. It adjusts for escalated prices and uses risk analysis to set contingency. Real project costs are rarely shared across the industry, so the framework gives owners a published best practice to see where their program stands in today’s dollars. Project controls leaders at other firms have used it on their own work. On one transit maintenance facility, a team cut overhead project costs by 7 percent.
His peers trust his judgment. He has reviewed technical papers for the Transportation Research Board of the National Academies and for the AACE International Conference & Expo, and he judged the Project Controls Expo USA awards. He is also a published contributor to AACE International Recommended Practice 142R-26 (RP 142-26), and peer reviewer for several others. His latest work, an AI Credibility Index for Cost Estimates, helps owners judge how far they can trust a project cost estimate built with AI.
The next decade will show whether America can rebuild without losing control of project costs. Mr. Maniar studied at Virginia Tech, whose motto, Ut Prosim, means “That I May Serve,” and he sees his work the same way. The people who pay for public projects deserve project metrics they can trust, from the tunnels under Grand Central to the next train line still waiting to be built.
