Consigli CIO Sees Biggest AI Impacts in Estimating

Why It Matters

AI‑enhanced estimating cuts cycle time, improves transparency, and reduces disputes, giving contractors a competitive edge. The shift also forces firms to manage AI spend and meet rising workforce expectations.

Key Takeaways

• AI improves estimating by automating data analysis and version control
• Innovation and VDC teams pilot AI, field crews handle daily use
• IT oversees AI governance, ensuring security and data integrity
• Workforce now expects AI tools as standard resources
• AI cost visibility prompts firms to plan capacity and budgeting

Pulse Analysis

Estimating has long been a bottleneck for contractors, relying on scattered spreadsheets, manual version control, and fragmented documentation. By feeding historical bid data, material costs, and schedule assumptions into generative AI models, firms can instantly surface discrepancies, quantify trade‑offs, and generate narrative explanations for stakeholders. This not only accelerates the bid cycle but also creates a transparent audit trail that owners can review, reducing disputes and improving confidence in the projected budget. As AI algorithms become more adept at interpreting unstructured construction data, the accuracy gap between early design and field execution narrows dramatically.

Consigli’s approach layers responsibility across three pillars. The innovation and Virtual Design and Construction (VDC) teams act as testbeds, rapidly prototyping AI tools and measuring ROI before wider rollout. Field crews, who live the daily realities of a jobsite, then adopt the vetted solutions, providing real‑time feedback on usability and safety impacts. Meanwhile, the IT department enforces enterprise‑wide standards for data security, model governance, and infrastructure scalability, ensuring that AI deployments do not compromise confidential project information. This coordinated model balances agility with risk management, a template other contractors are beginning to emulate.

The shift from novelty to necessity brings new financial considerations. As AI licences, cloud compute, and data‑curation costs scale, firms must embed these expenses into project budgets and evaluate long‑term ROI. Simultaneously, a growing segment of the construction workforce now views AI access as a baseline tool rather than a perk, influencing talent attraction and retention. Companies that proactively manage AI spend while fostering a culture of rapid learning will gain a competitive edge, delivering faster, more accurate estimates and smoother handoffs from design to construction.