Callahan Construction Managers

By Adam Petersen 

The construction industry has a long-standing problem. We are “data rich and insight poor.” We generate massive amounts of information on every project. We rarely connect it across the lifecycle or to the next project. 

I recently attended ENR FutureTech 2026 in San Francisco. Leaders from across the AEC sector came together to talk about the reality of AI, robotics, and digital transformation. The message was consistent and clear: the technology is no longer the bottleneck; it’s the humans in the loop. 

At Callahan Construction, we are taking a measured approach to this era. Here is what we learned at FutureTech, and how we are applying it internally and on our projects. 

The Reality of AI Implementation 

Alan Espinoza, founder and CEO of Reconstructive AI, opened with a number that landed hard: 95% of AI pilots fail to deliver long-term value¹. Not because the technology is flawed, because implementation teams fail to capture its value. 

AI is an amplifier. It scales what works. It also exposes what is broken. If a workflow is inefficient, adding AI makes it fail faster. It is a known and reported fact that the construction industry loses $88 billion annually to rework². Ninety-six percent of our data goes unused³. You cannot automate your way out of bad processes. That reality does not slow us down, it sharpens our focus. 

At Callahan, we diagnose before we automate. Before introducing any new software, including AI, we map actual workflows in the field, not the theoretical ones drawn up in the office. We identify friction points, whether in subcontractor payments, RFI routing, or material procurement. A process must be clean, proven, and understood before we layer on automation. 

The Data Trust Deficit 

A number that kept surfacing throughout the conference: 87% of contractors believe AI will make a meaningful impact. Only 26% believe their data is ready for it. 

AI cannot reason with fragmented PDF drawings or inconsistent equipment tags. It needs structured, reliable data. During the “Transformative Power of Data” panel sponsored by Trimble, leaders from Hensel Phelps and DPR Construction made the same point: digitization is not transformation. Changing how workflows run is. 

We are making a conscious effort to address this data readiness gap in a more disciplined and holistic way. That starts with treating models, drawings, and project information as part of a connected system rather than disconnected inputs. By building a stronger foundation for how data is structured, shared, and trusted, we put ourselves in a position to use AI where it adds real value. The result is a more reliable process and better outcomes across the project team. The Evolving Standard of Care 

This is the shift that carries the most weight. AI is moving from competitive advantage to baseline expectation. Within a few years, failing to use AI for complex design review or safety monitoring may be treated as a failure to meet the industry standard of care. 

Platforms like LightTable already use AI to review plans for coordination gaps, code issues, and constructability, catching multimillion-dollar errors before a shovel hits the ground. Companies like Document Crunch apply AI to contract review, surfacing risk language in seconds. 

This shift demands rigorous governance. Free, public AI tools pose real risks to project confidentiality and intellectual property. At Callahan, we deploy enterprise-grade, secure solutions that protect our clients’ data. We are transparent with our clients and trade partners about the tools we use, the way we use them, and the safeguards in place to protect their data. That transparency is not simply a matter of policy. It is fundamental to how trust is built and maintained. We are equally clear that AI does not replace accountability. Human judgment, expertise, and oversight remain essential.  

Preparing for an Autonomous Future 

The timeline for autonomous construction has accelerated. Labor shortages and a massive project backlog have pushed robotics and machine control to commercial viability faster than expected. We saw case studies of Bedrock Robotics retrofitting existing excavators with autonomous capabilities on live Zachry Construction projects. We saw 3D concrete printers reaching scale and cost parity. 

Fully autonomous job sites are still far ahead of us. But the foundation is being built today. Reality capture and drone capture are where we are focused right now. Callahan already partners with OpenSpace, whose CEO Jeevan Kalanithi spoke on the “Scaling Up with Reality Capture” panel. Our superintendents use OpenSpace daily to document site progress at the ground level. Drone capture adds the aerial layer, giving us a complete picture of the site at any point in time. Together, these tools create a continuous, accurate record that supports coordination, documentation, and eventually, the autonomous workflows that are coming. 

The Callahan Approach: Exploring New Frontiers 

The firms that win in this era will not be the ones that bought the most software. They will be the ones that did the unglamorous work: cleaning their data, standardizing their processes, and building a culture that demands accountability alongside change. That commitment to getting better, even when it is slow and unsexy, is what separates the firms that talk about excellence from the ones that deliver it. 

At Callahan, we are not chasing hype. We are actively evaluating pilot opportunities with measurable ROI. Our tech committee reviews solutions across the full project lifecycle, from pursuit and preconstruction through field execution, with one filter: does it solve a real problem and deliver a result we can measure? 

We diagnose first, then fix the underlying issue. We automate only what is proven to work. That is how you build with certainty. 

Written 95% by humans. The other 5% is between us and AI