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How is AI Driving Efficiency in Construction? By Supporting People
How is AI Driving Efficiency in Construction? By Supporting People
6 minute read
How AI delivers value today looks different from what early conversations may have promised. DPR's Hrishi Maha shares where AI is driving efficiency in construction workflows today (and where it can’t, yet).
6 minute read
As the leader of DPR’s Data and AI group, Hrishi Maha shapes and drives the company’s enterprise-wide Data and AI strategy, guiding DPR’s evolution into a truly data-driven organization. With more than 15 years of industry experience, Maha has played a pivotal role in elevating operational efficiency across the construction lifecycle and embedding advanced AI and technology solutions throughout the company.
by Hrishi Maha, Data & AI Leader
AI is no longer theoretical in construction. It is already being used across projects, sometimes in visible ways, often quietly embedded into day‑to‑day work. But how AI delivers value today looks different from what many early conversations promised.
Initial expectations focused on sweeping transformation: fully optimized schedules, automated decision‑making, and step‑change productivity gains across entire projects. While those possibilities continue to evolve, that is not where the most meaningful progress is happening today.
The real impact is far more targeted. AI is proving most effective when embedded into everyday workflows to support the people making decisions, not replace them. Understanding that distinction clarifies both where AI is driving value now and where limits remain.
Where AI Is Delivering Value Today
The most effective applications of AI are practical, focused and closely aligned with real project workflows. Rather than operating as standalone tools, they are integrated into how teams already plan and execute work.
Access and Synthesize Information Faster
Project teams manage an overwhelming volume of data across schedules, budgets, RFIs, submittals and historical records. Finding what matters, when it matters, can be difficult and time‑consuming.
The value is not in having more data. It is in reducing the effort required to understand it. By lowering cognitive load, AI helps teams move more quickly from information to insight, and then from insight to action.
What does AI look like in practice at DPR?
AI is navigating records by synthesizing information within a single, integrated environment. Instead of manually pulling reports from multiple systems, teams receive consolidated views, such as AI‑generated trade partner summaries, that surface performance insights and potential risks in one place.
Identify Patterns Across Past Projects
By analyzing historical data, AI can surface patterns that inform early decisions such as staffing strategies, sequencing approaches and risk considerations based on similar past projects.
For our customers, this creates confidence earlier in the process. Projects can be staffed more appropriately from the outset; risks can be anticipated sooner and delivery can become more predictable. Shifting staffing decisions from reactive to data‑informed can help teams address uncertainty earlier and establish a stronger foundation for execution.
What AI tools are DPR teams using?
DPR uses tools like “Predict My Team” to recommend staffing strategies during the opportunity phase. Instead of relying solely on individual experience or limited reference points, teams can draw from patterns across comparable projects to build a more informed starting plan.
Inform Decisions Before Work Begins
AI is also helping teams evaluate options earlier, before plans are locked in. Rather than relying on a single path forward, teams can explore multiple scenarios and compare sequencing options, schedule impacts and resource trade‑offs.
By identifying patterns that may signal cost, schedule or safety risks, AI can help teams surface potential issues earlier. This gives project teams more time to adjust, align and mitigate risk before work begins, when decisions are least expensive to change and have the greatest impact.
Interact With Information Not Just Access It
Despite advancements in technology, project teams still spend significant time organizing information, summarizing reports, and connecting insights across systems. The unintended result of this is slower decision making and delayed answers, which can undermine the experience for our customers and project stakeholders.
AI can reduce this friction by removing much of the manual effort associated with information management. Instead of searching for information, teams can interact with it by asking targeted questions and receiving relevant, contextual insight in real time.
For customers, the benefit is clarity and responsiveness. As project data continues to grow, AI helps teams cut through the noise, respond faster and stay aligned as conditions evolve. The outcome is less friction, clearer communication and a more seamless project experience. Teams spend less time finding information and more time applying it.
How is DPR leveraging AI for better information management?
At DPR, shifting through priorities is enabled through internally developed AI tools that provide access to knowledge across internal platforms and project guidance. Teams can surface the right insight at the right moment, supporting disciplined thinking before action.
AI Supports Expertise It Doesn’t Replace It
As AI becomes more embedded in project delivery, we must be clear about the role it plays. The goal is not to replace human judgment, but to strengthen it. This keeps accountability, context and decision‑making firmly in human hands.
AI is best understood as an assistant, not a decision maker. It can process large datasets, identify patterns and compare options at a speed no team could replicate manually. What it cannot do is fully understand site conditions, stakeholder priorities, trade‑offs or risk tolerance. Those require experience and judgment.
The most effective model pairs AI with human expertise:
- It supports decision-making rather than automating it
- It strengthens expertise instead of replacing it
- People remain accountable for outcomes
AI does not inherently understand business conditions or project complexity. Its effectiveness depends on:
- Connected, reliable data that reflects real project conditions
- Integration into existing workflows so insights arrive when decisions are being made
- Transparency, so teams understand how insights are generated and where limits exist
- Skilled teams who can interpret outputs and translate insight into action
How does DPR balance AI with human expertise?
At DPR, this balance reinforces disciplined thinking before disciplined action. AI improves how teams access and interpret information. People provide meaning, context and accountability. Together, they support better decisions and more reliable outcomes.
From Efficiency to Better Outcomes
AI is often framed in terms of efficiency. Saving time and reducing manual effort are important, but they are not the full story. The greater impact is what efficiency enables.
When teams can access information faster, explore more options, and identify risks earlier, they can make better‑timed, higher‑quality decisions with greater confidence. In construction, decisions made early in a project have exponentially greater influence than those made later. AI is most valuable when it shifts insight earlier, not when it reacts after the fact.
That is where AI is contributing today:
- Supporting greater predictability
- Helping teams identify late-stage risks earlier
- Increasing confidence in planning and delivery decisions
How does DPR's business focus influence its use of AI?
This aligns with a core focus at DPR: delivering more predictable outcomes by improving how and when decisions are made across the project lifecycle.
A Practical Path Forward
The pace of AI innovation is accelerating. New tools, assistants and point solutions are emerging rapidly across the construction ecosystem.
The challenge is not access to capability, it is application. Many solutions can address isolated tasks effectively, but meaningful impact requires integration into broader workflows, data environments and decision processes.
What is the impact of AI on how DPR delivers projects?
At DPR, the focus is on embedding AI in ways that enhance how teams already work, rather than introducing parallel systems that create friction.
AI is already shaping how projects are planned and delivered, but its role is more grounded than early expectations suggested. It is not simplifying complexity or replacing teams. It is helping teams navigate complexity more effectively.
For owners and project teams, the takeaway is straightforward: focus less on adopting AI quickly and more on applying it where it delivers clear, measurable value. The most meaningful innovations are not the ones that sound the most advanced. They are the ones that work.
Ultimately, AI is another tool that helps us do what we set out to do at DPR: build great things with greater clarity, confidence and predictability.
Posted on May 19, 2026
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