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The next big infrastructure project may be different from any seen in more than 50 years.
Contractors were speculating about what to build on London’s newest underground route, the Elizabeth Line.
Not guessing. No improvement. guess.
Construction on the capital’s £19bn Crossrail project has gone ahead of design. Workers installed systems, dismantled them, reinstalled them. They called it “hokey cokey”. Management teams with competing incentives clashed across sites. Information from the ground level traveled up the chain and disappeared into meetings.
There was no effective visibility for two years.
The project opened four years late and was £3 billion over budget. But here’s what matters: Crossrail is not an outlier. This is ideal.
Another major LNG project, a $10+ billion initiative critical to US energy security, suffered a major setback in May 2024 when its prime contractor, nearly 80 percent complete on the first train, laid off thousands of workers and filed for bankruptcy. This result shows that even a 100-year-old company, with all the existing systems and equipment, could not manage the project successfully. The construction of trains two and three is incomplete.
fragmentation problem
The construction industry is set to invest $50 billion in planning technologies between 2020 and 2022 alone, from BIM software and AI analytics to project management platforms.
But here’s what actually happens on the projects.
Teams use AutoCAD or 3D for design, SAP for procurement, project scheduling, documentation systems, and more. Each system speaks its own language. Data does not flow between them.
The result is severe fragmentation. Information gets stuck in silos. Teams can’t share, sync, or act on critical data when needed.
organizational fracture
Technological fragmentation is bad enough. Organizational structure makes it worse
Construction projects are run like a relay race, with runners changing between sprints. Designers delegate to engineers. Engineers hand over the work to contractors. Contractors hand over to subcontractors.
Each handoff loses information. The context disappears. Critical decisions are taken in the same silo, but dependent teams are kept in the dark until the last moment.
Most planning systems serve only the small functional team that uses them. Other teams that rely on that information are left behind.
cognitive ceiling
In a typical mega-project, the reality changes daily. 20 to 100 data points shift every 24 hours: design updates; supply chain disruptions; weather delays; labor availability; regulatory changes; equipment failure; Stakeholder decisions.
A human project manager tracking these variables is like a person trying to play chess on 50 boards simultaneously while the rules change in the middle of the game.
We have reached the peak. The complexity of the project has outstripped human processing capacity.
Performance Gap and Master Builder Thinking*
AI systems are already demonstrating what happens when you remove that limit. Sequence optimization used to take two weeks but now takes one day. A security observation workflow that required 30 days for 5,000 workers is now completed in 24 hours.
These are not minor improvements. They are different ranges of ability. Technobuilt, a leader in built environment technology, has been providing such capabilities to major project owners and engineering contractors for the last few years.
Technobuilt was brought in to assist one of America’s largest energy projects after its first phase had encountered serious difficulties with the contractor and other project systems not working. Early performance reviews of Technobilt’s technology have shown improvements of more than 30 percent in complex energy infrastructure and data centers. Additionally, Technobuilt is also helping one of the world’s largest data center hyperscalers reduce delays and accelerate their project timelines.
Platforms like Technobuilt’s PACE OS consolidate fragmented data and systems into intelligent containers – or digital construction blocks. The platform contextualizes information related to design, supply chain and execution in real time. It provides a single window to the truth that updates as conditions change, and provides decision makers with the power of a digital master builder a shortest path to intelligence.
The results are projects that can guarantee cost, schedule, and carbon budget.
insurance tipping point
This is where the math becomes uncomfortable for traditionally managed projects.
The gap in insurance and financing for infrastructure and energy projects with high performance risk is already large. When AI systems can demonstrate guaranteed results, traditional approaches become comparatively uninsurable.
Why would an insurer back a project with a 90 percent chance of significant overrun when AI-managed options could prove to have controlled delivery?
The industry knows this: 65 percent of construction professionals now view the role of AI in project management favorably. Only 13.5 percent people are skeptical.
Change is already happening.
what will 2029 look like
If you’re planning to build a $500 million infrastructure project over five years, your project management team will look very different.
50 percent fewer humans will be needed for roles in planning, coordination and supply chain tracking. AI agents will handle the synthesis of daily variables, sequence optimization and risk identification.
Humans will focus on final approval, complex scope interpretations, and overcoming obstacles. Foremen are still needed for physical construction. Complex process design still requires human expertise.
But coordination layer, information synthesis, real-time optimization? That’s the AI field now.
Digital ledger execution and rapid learning can now position the project manager back as a master builder with clarity and confidence that never existed before in this industry.
binary options
If we look at major projects getting off the ground today without this technology, it is like seeing a repeat of Crossrail. Warring Incentives. Information black hole. Contractors are estimating. Waste of billions.
Historically, there is a 90 percent chance that these projects blow well over budget and are painfully delayed. AI does not eliminate all project risks. But this eliminates the range of risks caused by information fragmentation and human cognitive limitations.
This is the biggest risk.
The question is not whether AI will help manage your next mega project. The question is if that doesn’t happen will you still be competitive?