Construction's $1.3 Trillion Productivity Problem

Bassem Hamdy · CEO, briq · Oct 2025

The construction industry's productivity gap costs the global economy $1.3 trillion annually. AI is the key to closing it.

McKinsey estimated that closing the productivity gap in construction could boost the industry's value added by $1.6 trillion annually. Let that number sink in. While virtually every other major industry has seen significant productivity gains over the past two decades, construction productivity has remained essentially flat — and in some measures has actually declined. This isn't just an industry problem; it's an economic crisis hiding in plain sight.

The numbers are staggering. Construction accounts for 13% of global GDP, yet it ranks among the least digitized industries in the world. Labor productivity in construction has grown at only 1% annually over the past two decades, compared to 3.6% for the total economy and 7.7% for manufacturing. If construction had kept pace with the overall economy, the industry would be generating trillions more in value.

So where does all that productivity go? I've seen it firsthand at hundreds of construction companies: it's lost in manual data entry, in chasing paper invoices, in reconciling spreadsheets, in re-keying information across disconnected software systems. It's lost in the 17-day month-end close processes, in the hours spent manually coding cost data, and in the weeks of back-and-forth on change orders that could be resolved in minutes with the right information.

The back office is the biggest culprit, and it's the area most ripe for AI transformation. A typical mid-size contractor has a finance team spending 60-70% of their time on data processing tasks — entering invoices, matching purchase orders, generating payroll, reconciling accounts. These are precisely the kinds of high-volume, pattern-based tasks that AI handles exceptionally well. When we deploy our platform at a new customer, it's common to see a 60%+ reduction in processing time within the first quarter.

But the productivity problem extends beyond the back office. Estimators spend days analyzing bid packages that AI can summarize in minutes. Project managers manually compile data from five different systems to produce a weekly report. Superintendents fill out daily reports by hand that AI could generate from field data automatically. At every level, people are doing work that machines could do faster and more accurately.

The path to closing this gap isn't about replacing people — it's about deploying AI as an amplifier. A single accounts payable clerk working with AI can process the invoice volume that previously required a team of four. An estimator supported by AI-powered scope analysis can evaluate twice as many opportunities with higher quality takeoffs. The math isn't complicated: when every person in your organization is 2-3x more productive, the entire enterprise transforms.

What makes me optimistic is that we're still in the early innings. AI adoption in construction back-office functions is around 34%, which means two-thirds of the industry hasn't even started. The companies moving now are establishing competitive moats that will be very difficult to overcome. They're learning faster, accumulating better data, and building organizational muscle around AI-augmented workflows.

The $1.3 trillion productivity problem isn't a mystery. We know where the waste is, and we now have the technology to eliminate it. The question isn't whether AI can close the gap — it's how quickly the industry will adopt it.