AI won’t fix construction delays until jobsites fix data

Clay, New York, September 26, 2025

News Summary

Artificial intelligence cannot meaningfully reduce construction delays or budget overruns until jobsites collect structured, centralized data. The industry still relies on fragmented updates — messaging apps, paper checklists and scattered cloud folders — leaving analytics and AI models starved for reliable inputs. The piece compares construction to agriculture’s data-driven shift, highlights visual capture practices (helmet-mounted 360° cameras mapped to floor plans), and cites pilots: Zachry with ALICE for generative scheduling, Skanska’s Safety Sidekick, and Foresight’s consolidated forecasting. Practical steps: standardize workflows, digitize one process at a time, centralize records, and train teams so AI can deliver real value.

AI Won’t Fix Construction Delays Until Jobsites Feed It Clean, Centralized Data

Top line: Artificial intelligence will not solve construction delays or budget overruns without structured, centralized data. Most sites still rely on a patchwork of messaging apps, paper checklists and scattered cloud folders, and those tools and folders are often days out of date. With information fragmented and delayed, AI feels disconnected from the realities of daily work and remains a theoretical promise rather than a practical asset.

Why the data gap matters now

Two common industry statistics help explain the urgency: 20% of projects run late and 80% of projects go over budget. Those outcomes are directly linked to data gaps. AI can only work with what it understands; site activity needs to be documented in consistent, clear and connected ways. How data is captured matters as much as where it’s stored: if input is messy or inconsistent, AI models cannot produce reliable, actionable guidance.

What teams should do first

The practical path forward is clear. Implementing digital workflows and standardized data capture prepares jobsites for AI-driven insights. The prescription is straightforward: choose one frustrating process, digitize it, and structure the inputs so they become searchable and analyzable. Work from the same plans, in the same place — choose the right software, align on standardized workflows, and ensure the whole team is trained and confident using it.

Field and office must be connected. Connect site and office teams using shared systems that sync in real time so everyone is working with the latest updates in a single project space. Centralize project data in the cloud to ensure seamless access, live collaboration and easy analysis regardless of team location. Before AI can assist in construction, the right digital tool must be in place; before AI can elevate jobsite performance, teams must first bring their workflows together in one digital environment.

Concrete examples showing how structure unlocks AI

A construction scheduling example: one heavy-builder adopted a generative-scheduling engine and, years before rollout, standardized how takeoffs, crew rates and weather delays were logged across projects. Because inputs shared one format, the engine could ingest them and generate hundreds of buildable sequences in minutes. What once required a full-day workshop became a live “what-if” session where planners adjust a resource or constraint and the schedule updates in real time. Early trials surfaced sequences that trimmed the critical path by up to two weeks and highlighted risks before ground was broken. The lesson is simple: without consistent quantities, rates and calendars, even the best AI tools are ineffective; with them, AI becomes a fast, tireless, fact-driven planning partner.

A safety example: a large contractor moved years of safety observations, toolbox talks and near-miss reports out of siloed PDFs and spreadsheets into a central safety warehouse. The firm standardized hazard categories, severity ratings and jobsite metadata for every record. With a clean data model analysts produced reliable dashboards and trend maps rather than static summaries. The firm then launched a generative AI chatbot trained solely on the firm’s incident history and best-practice library so field supervisors can pose plain-language questions and receive instant answers with inspection excerpts and toolbox-talk scripts. Reported impacts included reduced time spent preparing toolbox talks and greater day-to-day engagement with site safety protocols.

A portfolio example: a global developer managing multiple builds consolidated scheduled exports into a single activity taxonomy, replacing annual uploads with weekly APIs. After mapping scattered files into a single clean dataset, the portfolio’s AI forecast engine delivered probabilistic finish dates and early-warning delay signals. Reporting costs fell dramatically and proactive resequencing avoided substantial delay costs. Structured data enabled these results; AI made them visible.

Visual capture as a keystone

Not all data is created equal. Photos and videos captured at the right moment, from the right place, with the right context are among the most valuable records. Examples of structured capture include photos and videos pinned to digital floor plans, automatically tagged with timestamps and location for accurate context; predefined digital forms and templates that guide on-site teams to consistently collect and report the right information; and centralized document management with workflows, approvals and records stored in one place for easy access and tracking.

When visual records are tied to digital floor plans, timestamped and tagged by location and trade, they become the basis for smart decision-making rather than just records. That process creates a complete, structured visual log of how a site evolved over time. Benefits include the ability to compare progress, check what’s behind walls, validate installations without demolition, prevent rework, support faster issue resolution and maintain compliance with verifiable records. Structured visual datasets will fuel AI tools that detect deviations, spot patterns and forecast delays before they become costly.

Forward-thinking teams are integrating visual capture into daily routines to build consistent, project-wide visual histories. Product examples exist that use helmet-mounted cameras to record site walks in 360° and automatically map imagery onto floor plans via an AI-powered platform. That structured visual documentation moves projects from reactive fixes to predictive, data-driven delivery.

Industry moves and local projects

A major chipmaker filed a 336-page site plan with the town for a proposed mega-fab on a 1,400-acre parcel in upstate New York. The submission provides the clearest look yet at the sprawling complex and focuses heavily on the first fab, which will be built at the northwest corner of the site. Each fab will cover 28 acres of land, and each would contain 600,000 square feet of cleanroom space plus substantial support and administrative space. The site-plan filing starts a town review to ensure conformity with building and zoning codes, and the town will review and vote on the plan and rezoning for the last three parcels. The filer plans to begin cutting trees and leveling the first 700 acres this November and expects to start construction on the first fab in late 2025. The entire campus could become the largest private development in that state’s history if all planned fabs are built, and the program includes large-scale utilities and treatment facilities and will be supported by an initial land sale arrangement with a public industrial development agency.

In regional business news, a large civil contractor reorganized its area operations to form a new transportation and water infrastructure specialty firm focused on tunnels, bridges, roadways and water systems. The new entity will operate as a subsidiary within the parent group and will combine three longtime regional firms into a single specialist organization, aiming for consistent operations and risk management in the New York metro area.

Employment and sector recovery

A statewide analysis found New York City’s construction industry remains smaller than it was before the pandemic. In 2024 the city averaged 143,100 construction jobs, an 11% decrease from 161,300 construction jobs in 2019. The state remained 4% below its 2019 construction employment levels, making it the second-slowest recovery of any state after West Virginia. The sluggish hiring is tied mainly to lagging demand for non-residential construction. Residential spending surpassed 2019 levels by 2023, reaching $22.8 billion, while nonresidential spending was $22.2 billion in 2023, 3% lower than in 2019. The report warned that staffing declines at permitting agencies and other external factors could further hamper recovery, and urged steps such as shoring up staff that process permits.

How to start: a short checklist

• Pick one process that frustrates the team and digitize it with a template or form.
• Standardize inputs — use the same nomenclature, trade tags and timestamps across projects.
• Centralize data in a cloud project space so the same plan set, images and records are available to all.
• Train the team so capture habits are consistent and reliable.
• Measure outcome — compare time saved, reduced rework and improved forecast accuracy before expanding.

Bottom line: Structured data is the backbone of any AI workflow. Take one process. Digitize it. Structure it. That’s how to prepare for AI.

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Deeper Dive: News & Info About This Topic

Additional Resources

• BoiseDev: Micron Clay expansion
• Wikipedia: Micron Technology
• The New York Times: OpenAI data centers in the United States
• Google Search: OpenAI data centers United States
• Crain’s New York: NYC construction jobs still below pre-pandemic levels
• Encyclopedia Britannica: New York City construction jobs
• Construction Dive: FlatironDragados forms SPC Construction
• Google Scholar: FlatironDragados SPC Construction
• CBS News: Construction continues on NYC’s first soccer stadium (video)
• Google News: NYC first soccer stadium construction

Author: Construction NY News

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