The Reality Gap: John Ryan on Why Construction Tech Must Be Built from the Ground Up

In the rapidly evolving landscape of construction technology and AI, few voices are as grounded in reality as John Ryan, Director of Symterra. We recently had the pleasure of hosting John on the Project Flux podcast, where he shared his refreshingly candid perspective on the disconnect between tech promises and on-site realities, and why construction technology needs to be built from the ground up—not the boardroom down.

The Accountability Gap

What keeps John up at night isn't the latest AI model or blockchain application—it's accountability. "If something ever goes wrong, whether it's commercial or safety or something else happens, it's somebody who's going to court or adjudication in a commercial dispute," he explained. "None of the people who are promising the world of tech and leveraging and this that are going to actually be stood up there in front of court."

This accountability gap creates a fundamental problem: whilst tech companies can make grand promises with minimal consequences for failure, it's the construction professionals who bear the ultimate responsibility when things go wrong.

John drew a compelling parallel with autonomous vehicles, where car manufacturers are grappling with ethical dilemmas about how their AI should respond in potential accident scenarios. "We end up having the car companies having to deal with that ethical decision making as to what is the least amount of damage and who then is responsible for that being caused," he noted. "We've got that in construction where we're using AI generators, BIM models and all the other bits and pieces... And ultimately who's going to jail for that?"

The construction industry faces a unique challenge compared to other sectors: the lag between design failures and their consequences. John pointed to the Grenfell tragedy as a sobering example: "The failures happened many years before the fire happened. It's just that the fire was at a different time." This extended timeline—from design through construction to eventual use—means that construction's accountability issues play out over years rather than the immediate feedback loop seen in sectors like automotive.

Reading through the Grenfell inquiry, John reflected, is "heartbreaking" precisely because the disaster seems so preventable in hindsight. "If only there was one person in the room sometimes going just said, look lads, that's 50 grand is nothing. I don't understand this. I'm not a materials expert. This is a big complex issue outside of my expertise. Let's just get a subbie in." It's what he calls the "swiss cheese effect" of decision making—where multiple small failures align to create catastrophic outcomes.

Data Silos and the 5% Problem

When the conversation turned to AI's potential to help prevent such failures through better data analysis, John highlighted another fundamental challenge: the fragmentation of construction data.

"There's a problem with some of that in the sense of the data exists in silos across different subcontractors and suppliers and design houses," he explained. "There's no one project bucket. I know there's technically meant to be, but that's the project bucket I sent to you as the client. It's not the one that I've got in my back pocket of what I'm actually doing."

This creates what might be called the "5% problem"—where only a tiny fraction of relevant project data is actually available for analysis: "Out of all of that, of the 100% of data actually related to a project, you're getting 5% tops. Of that 5%, what's actually useful or beneficial for decision making that you can train a business on is probably 5% of that."

The result? "You end up having, you know, you're missing 95% of the decision making."

What data actually matters? According to John, it's not the minutiae of which paintbrush a decorator uses, but rather "capturing change, capturing the initial design, approved for construction, and then any change on that." This focus on change management and risk profiles emerged as a key lesson from the Grenfell inquiry and represents an area where technology could genuinely add value—if it can overcome the silo problem.

Tech Built by Outsiders

Perhaps the most fundamental issue John identified is that construction technology is often created by those with limited understanding of construction itself: "If you look at all the big multi-billion dollar construction tech software out there, pretty much every single one was started by somebody with limited or no construction experience."

This disconnect leads to what John describes as "solutions looking for problems" rather than technology designed to address genuine on-site challenges. It's why he left his role on the Tideway Super Sewer project to enter the tech space—"because the tools were not built for use on the ground."

The gap between tech demos and reality is particularly stark. John described how tech demonstrations often take place on empty sites during weekends "because that team doesn't have the correct tickets to even walk on a construction site safely, nevermind when there's actually stuff kind of going on."

This lack of practical understanding extends to the physical constraints of construction work. "You've got five points of PPE typical on a project. You've got big heavy boots on, you've got Hi-vis trousers, jacket, everything else, hard hat, gloves, glasses. You're already loaded up with a lot of stuff on top of if you're actually doing some work, you've got tools and bits and pieces doing that. The last thing you need is extra tech and extra solutions."

The result? Solutions that look impressive in boardroom presentations but fail to deliver value in the muddy, complex reality of construction sites.

The Adoption Challenge

When asked why site teams often resist new technology, John's answer was refreshingly straightforward: it's about time and money.

"Once you press go on delivery, you are burning cash," he explained. "So you're burning time for people to sit around. If you've got modular construction, those units have been booked off the production line and you're going to end up on site with 300 bathroom pods in the rain, sat there because you're sat in a computer trying to learn whatever it is you've been given."

This economic reality creates a fundamental barrier to adoption that many tech companies fail to appreciate. Even if a company decides to invest in training before a project begins, adoption isn't guaranteed because, as John puts it, "it's solutions are different from problems."

His challenge to major tech companies like Autodesk was particularly pointed: "I would love to see Autodesk actually go off and deliver a multi-tenanted building all by themselves, become the principal contractor and manage all the works through it and get their coders in to understand this is how they're to get them on the tools, get them to bricklaying, plastering, pulling cables and then see how that kind of comes about."

Symterra's Approach

John's experiences led him to create Symterra, a solution built from the ground up with site realities in mind. "We very much kind of have a bottom up solution for site communication. It's a data pipeline. It allows you to connect your workforce to whatever you need it to go into."

The approach prioritises simplicity and practicality: "We designed our system to add subbies for free. It doesn't cost the subbies any money. It doesn't cost the company any money in the subscription." This zero-friction approach stands in stark contrast to systems that require weeks of paperwork to onboard new subcontractors.

When asked about Symterra's relationship to tools like WhatsApp—which remain popular on sites despite their limitations—John acknowledged the comparison: "We do kind of say we're like WhatsApp for construction, replacing that." But unlike companies that simply replicate WhatsApp's chat functionality, Symterra adds structured data capture that makes the information usable long-term.

This balance between ease of use and data value represents the sweet spot that construction tech needs to hit—something that's only possible when solutions are designed with genuine understanding of site conditions and workflows.

The Future of Construction Tech

Looking to the future, John sees potential in robotics but remains grounded in practical considerations. For tasks like cable pulling in underground environments—"It's not nice. It's hard work"—robots could provide genuine value by reducing physical strain and injury risk.

However, he's sceptical about more ambitious visions of fully automated construction: "By the time you set the whole system up and the conveyor belt and so on, the capital cost involved, that machinery is massive compared to, you know, let's say a 200, 300 day rate for somebody coming on site to do the work."

The most promising approach may be modular robotics that can be adapted to different tasks—"It's just changing out the arms, the hands, the appendages and off it goes. It does a different task." This flexibility could allow for gradual adoption without requiring massive upfront investment.

Conclusion: Bridging the Reality Gap

The conversation with John Ryan highlights a critical challenge for the construction industry: bridging the gap between technological possibility and on-site reality. While AI, robotics, and other advanced technologies offer tremendous potential, their value can only be realised when they're designed with genuine understanding of construction's unique constraints and requirements.

The path forward isn't about forcing construction to adapt to technology, but rather developing technology that genuinely serves construction's needs—built from the ground up, not the boardroom down. As John's experience with Symterra demonstrates, this approach requires deep industry knowledge, practical understanding of site conditions, and a focus on solving real problems rather than chasing technological novelty.

For technology to truly transform construction, it must first acknowledge the reality of how construction actually works—with all its complexity, constraints, and human factors. Only then can we bridge the reality gap and deliver solutions that make a meaningful difference to those doing the actual work of building our world.

Listen to the full episode

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