Advertise on podcast: A.I. Excellence in Construction: Research Briefings

Episode summary: Construction firms now review A.I. tools before release, but few have designed how each individual output gets checked. This episode looks at the patterns that actually shrink the checking burden, using the 2026 A.I. Excellence in Construction report and field observations from Placer's A.I. peer groups. What you'll learn: • Why the most mature builders use A.I. to create scripts, buttons, and dashboards that contain no A.I. when they run, and what that removes from the review pile. • How an invoice cost-coding workflow changes when project managers see only the mismatches instead of approving every line. • Why citations and polished formats have not shortened review on their own, and what missing company context does to output people cannot explain. • What testing against known answers looks like on a construction project, and why one model checking another shares its blind spots. Who this is for: • Construction executives, innovation/digital leaders, operations, and IT/security teams who want a pragmatic way to prioritize A.I. pilots. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction

Episode summary: Nearly 6,000 executives report almost no productivity gain from A.I. while seven in ten of their firms use it. Four new studies trace the missing hours to checking A.I. output. This episode reads that research through the 2026 A.I. Excellence in Construction report to show where the checking lands inside a contractor. What you'll learn: - Why the macro productivity data still shows almost no A.I. signal, and what Apollo's chief economist means when he calls the payoff a forecast rather than an observation. - How much of the saved time goes back into verification, from roughly 37% in Workday's 3,200-person study to nearly half of scientists losing more than a quarter of their gains. - Where the checking lands in construction, with in-house counsel, senior estimators, and project engineers carrying the review step the tool cannot finish. - Why the same tool is cheap to verify on a fire-rating question and expensive on a code synthesis, using the report's engineering-documentation benchmark. - What the report's guidance on human provenance, golden sets, and spot checks means for any firm still quoting hours saved as a gross number. Who this is for: - Construction executives, innovation/digital leaders, operations, and IT/security teams who want a pragmatic way to prioritize A.I. pilots. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction

Episode summary: Three new 2026 studies test whether A.I. makes people lazy learners. This episode walks through what they found and applies it to how construction firms onboard new project engineers, using examples from the 2026 A.I. Excellence in Construction report. What you'll learn: - Why people who used A.I. for about ten minutes solved fewer problems on their own and gave up more often, while people asking for hints held steady. - What a Middlebury experiment found about students who used A.I. as a tutor, and why their gains lasted a week after the A.I. was gone. - How Fortis used an A.I. onboarding coach to cut new project engineer ramp-up from months to weeks, and why its use tapered off. - What a rookie PE's first two weeks with a 400-page spec book look like when A.I. explains the spec instead of answering for them. Who this is for: - Construction executives, innovation/digital leaders, operations, and IT/security teams who want a pragmatic way to prioritize A.I. pilots. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction

Episode summary: AT&T now routes 45 billion A.I. tokens a day to the cheapest model that meets its quality bar and reports cutting costs by as much as 90 percent, with open models taking a growing share. This episode asks what that shift means for a contractor whose A.I. arrives inside Procore, Copilot, or a startup's product. What you'll learn: - Why a large enterprise moved most of its everyday A.I. work onto open models it can run itself, and which parts of that decision transfer to a builder. - How an owner's "no A.I." clause becomes a hosting decision once a firm can run open-weights models inside its own environment, using Sundt's approach as the example. - What "USB-C for models" means in practice at Rogers-O'Brien, and why portability at the integration layer decides whether a contractor can ever switch models. - How the report's rule to tier the work, not the technology, sorts jobsite tasks into the ones that need a frontier model and the many that don't. Who this is for: - Construction executives, innovation/digital leaders, operations, and IT/security teams who want a pragmatic way to prioritize A.I. pilots. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction

Episode summary: Three contractors at the A.I. Excellence in Construction Virtual Summit, held in collaboration with AGC of America, explained how they decide which A.I. platforms to commit to, wait on, bypass, or replace with something built in-house. Their answers differ. Their conclusion about which layer a contractor must own does not. What you'll learn: - How Cerris scored Copilot, Procore's agents, Autodesk's A.I., and Document Crunch against three questions, and why one firm landed on four different verdicts. - Why RNGD built a data layer four years before it built an agent, and what a drayage ticket posting itself to an invoice reveals about the order of operations. - What Zachry means by rent, control, and own, and why decades of operational context is the one thing it will not hand to a platform. - What all three panelists stopped believing this year about which platform would win, and what replaced it. Who this is for: - Construction executives, innovation/digital leaders, operations, and IT/security teams who want a pragmatic way to prioritize A.I. pilots. From the Builder Track of the A.I. Excellence in Construction Virtual Summit, in collaboration with AGC of America. Panelists: Luke Kotz (Cerris), Will Cotton (RNGD), Ranjeet Gadhoke (Zachry Construction).

Episode summary: Vendors, CEOs, IT directors and project managers each want something different from A.I., and construction firms are getting pulled four ways at once. Builders in the Placer Solutions A.I. peer groups describe what happened when a consultant's central hub pitch met 30-plus disconnected systems, and what actually moved things forward. What you'll learn: - Why a third-party A.I. hub pitch stalled at one heavy civil contractor, and what the firm built in its place after an ownership change put every employee in the stakeholder seat. - How a former-project-manager business solutions team let IT step back to governance while operations people evaluated the tools. - What a strategic initiatives director did when executives split between "use A.I. for everything" and "nobody will learn anything," and why an outside framework broke the deadlock. - Why two field tools that worked perfectly in the office never reached a single technician, and the field-champion rule one MEP contractor adopted as a result. Who this is for: - Construction executives, innovation/digital leaders, operations, and IT/security teams navigating A.I. adoption decisions. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction Learn about the peer groups: https://www.placersolutions.io/peer-groups

Episode summary: A superintendent with no coding background built a live, multi-project risk dashboard in about seven working days. A VP of construction cut a month-end reporting cycle from ten hours to 45 minutes. Both stories come from construction leaders in the Strategic A.I. Peer Groups for Builders. What you'll learn: - How a superintendent who had never written code shipped a live risk dashboard scoring schedule, financials, quality, and safety across four divisions, and surfaced 200-plus open RFIs nobody had aggregated. - Why the strongest build in the group deliberately removed A.I. from the finished product and shipped as a plain website instead. - How a VP of construction got a month-end consolidation from ten hours to 45 minutes, build time included, and how he spot-checked it before trusting it. - What a senior operations manager walked out with after a one hour session run purely to show non-technical people what an agent is. Who this is for: - Construction executives, innovation/digital leaders, operations, and IT/security teams navigating A.I. adoption decisions. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction Learn about the peer groups: https://www.placersolutions.io/peer-groups

Episode summary: Two A.I. labs disclosed in July that their models breached real companies during testing, entering through weak passwords and vendor software. This episode translates those incidents for construction: why contractor risk now lives in the platforms you license and which controls are still yours. What you'll learn: - What actually happened in the July 2026 OpenAI and Anthropic incidents, told in plain language for builders rather than security specialists. - Why third-party involvement in breaches roughly tripled in three years, and what that means for contractors who run their business on cloud platforms. - How to treat the A.I. agents arriving inside your ERP and project management stack like employees, with defined access, supervision, and audit trails. - What questions to put to your platform vendors this quarter, drawing on new federal guidance for buying software and adopting agentic A.I. services. Who this is for: - Construction executives, innovation/digital leaders, operations, and IT/security teams who want a pragmatic way to prioritize A.I. pilots. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction

Episode summary: A.I. agents are starting to help negotiate and evaluate on behalf of construction firms. Two new studies show they misread who they are negotiating with and favor A.I.-written submissions. This episode maps the exposure in buyout, change orders, and correspondence, and the ownership rule that contains it. What you'll learn: - Why A.I. agents negotiate as if every counterpart is a perfect calculator when only about 1 in 8 people actually behave that way. - What the hardball default costs in a subcontractor buyout, where the study's calibrated move earned roughly six times the machine-calibrated one. - How A.I. evaluators picked A.I.-written pitches 89% of the time versus 36% for humans, and what that means for RFP and prequal screening. - Where to draw the line so the A.I. proposes the position but the person who holds the relationship owns what goes out. Who this is for: - Construction executives, innovation/digital leaders, operations, and IT/security teams who want a pragmatic way to prioritize A.I. pilots. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction

Episode summary: New research from Boston University and BCG shows that putting A.I. agents on the org chart changes how carefully managers check their work. This episode runs the findings against construction workflows, starting where the stakes concentrate. What you'll learn: - Why calling an agent an employee cut error detection by 18 percent at firms that already list A.I. agents on their org charts. - How managers substituted escalation for their own review, requesting outside checks 44 percent more often while catching fewer errors themselves. - How firms keep oversight intact through accountability culture and a doctrine of treating agents like interns. Who this is for: - Construction executives, innovation/digital leaders, operations, and IT/security teams who want a pragmatic way to prioritize A.I. pilots. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction

Episode summary: Across Placer Solutions A.I. peer groups, the builders getting reliable results have stopped tuning prompts and started managing context. This episode follows one subcontractor who rebuilt bid intake around that idea and cut setup from days to under a minute. What you'll learn: - Why the firms making real progress shifted their effort from better prompts to controlling what the model actually sees. - How one chief of staff turned a four-hour-to-two-day bid setup into one that finishes in under sixty seconds. - What makes context management uniquely hard in construction, where almost nothing repeats and every field question is fresh. - How the same discipline scales from version control on a single workflow to certified data products at the largest builders. Who this is for: - Construction executives, innovation/digital leaders, operations, and IT/security teams navigating A.I. adoption decisions. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction Learn about the peer groups: https://www.placersolutions.io/peer-groups

Episode summary: Construction peer groups spent early 2026 moving onto Claude and Cowork faster than any other A.I. tool. Then Anthropic shipped its most capable model yet, Fable 5, and the government suspended it three days later. The episode connects the adoption, the leap, and the new model-layer vendor risk. What you'll learn: - Why builders converged on Claude and Cowork, from an 11-page executive brief produced in about 30 minutes to a working web app built in under two hours. - What made Claude Fable 5 a genuine leap, including a top independent ranking and a reported 50-million-line codebase migration done in a day. - How the firms adopting fastest were already locking Claude down over data exposure and connector-license questions. - Why a government order pulling Fable and Mythos overnight is the clearest case yet for investing in your own harness and governance. Who this is for: - Construction executives, innovation/digital leaders, operations, and IT/security teams navigating A.I. adoption decisions. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction Learn about the peer groups: https://www.placersolutions.io/peer-groups

Episode summary: Per-token A.I. prices have fallen sharply, yet construction firms are spending more than ever. This episode traces the gap to consumption, not price, and reads the May 14, 2026 repricing moves from Anthropic and OpenAI through what builders are already doing that drives the meter up every month. What you'll learn: - Why per-token prices can fall 80 to 90 percent while your monthly A.I. bill keeps climbing, and which number actually matters. - What changes when an assistant stops being a chatbot and becomes a doer that plans and executes a full workflow. - How heavy ingestion of spec books, sub quotes, and project data quietly drives token consumption in construction. - What the May 14 Anthropic and OpenAI subscription changes mean for the A.I. tools your teams are already using. Who this is for: - Construction executives, innovation/digital leaders, operations, and IT/security teams who want a pragmatic way to prioritize A.I. pilots. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction

Episode summary: The capabilities that used to require a big firm's budget are getting cheap. Across Placer Solutions A.I. peer groups, smaller builders are retiring legacy estimating software outright, collapsing contract and safety review into a generalist plus a model, and shipping production tools in hours. What you'll learn:- Why a twelve-person preconstruction team fully retired On-Screen Takeoff for Togal after back-testing it to near-exact quantities, and what "retire, don't pilot" really signals.- How a CFO and a superintendent built a safety-review GPT in about four hours that now saves four to six hours per subcontractor plan.- What it means that a specialty sub with no estimating department built a production bid-intake workflow in roughly a day.- Where the advantage gets fragile: workarounds, governance gaps, and the builds firms abandon.Who this is for:- Construction executives, innovation/digital leaders, operations, and IT/security teams navigating A.I. adoption decisions. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction Learn about the peer groups: https://www.placersolutions.io/peer-groups

Episode summary: When we published the 2026 A.I. Excellence in Construction report, we placed construction workflows on METR's pace-of-change chart. Six months later, the chart has been outpaced. We unpack what's changed and the harder question that follows. What you'll learn:- Why the original METR chart on page 15 has been outpaced and which construction workflows now fall inside the capability envelope of frontier A.I.- How Stanford's 2026 A.I. Index and OpenAI's GDPval benchmark independently corroborate the trajectory from different methodologies.- What Princeton's peer-reviewed Kapoor et al. research shows about the 50x cost gap between benchmark-winning agents and deployable ones.- Why the binding constraint for construction firms is no longer capability but the discipline to turn it into deployment. Who this is for:- Construction executives, innovation/digital leaders, operations, and IT/security teams who want a pragmatic way to prioritize A.I. pilots. Full report & free sample: https://www.placersolutions.io/product/agi-in-construction