Down And Dirty With Digital: How AI Enhances Water Infrastructure Fieldwork
By Kevin Westerling,
@KevinOnWater
A Q&A with Shelley Copsey, co-founder and CEO of FYLD, on carrying out the rebuild of U.S. water infrastructure with greater efficiency, through AI and machine-learning tools.
Fieldwork is at the heart of infrastructure expansion and rehabilitation, as utilities, engineers, and contractors collaborate to build the systems and structures that treat and move water. The opportunity is great, but so are the challenges. Which is why new, digitally-enhanced tools are needed — to meet modern demands related to labor shortages, regulatory pressures, environmental threats, worker safety, and ever-tighter budgets.
Such technologies are also used to support “boots on the ground” labor, as planning, design, monitoring, and management decision-making are all enhanced by digital technologies.
To better understand this (relatively) new dynamic and its potential, I interviewed industry expert Shelley Copsey, who not only co-founded and runs a leading water-tech firm, but lists MIT and Stanford among her educational bona fides. Here’s her take on workforce optimization in this era of infrastructure renewal — and AI.
2026 marks the final year of the current authorization for the $1.2 trillion Infrastructure Investment and Jobs Act (IIJA). What does that mean for the development of capital improvement projects?
What other factors are driving infrastructure rebuilding, from both a needs standpoint and how projects are executed?
Beyond regulation, three forces are really driving infrastructure rebuilding: extreme weather, aging, and an urgent need to modernize how we deliver projects. Extreme weather conditions are exposing weak points in today’s networks, while decades-old pipes and structures are reaching the end of their life at the same time. That combination means we need long-term, community-focused plans that make systems genuinely more resilient. This is where the role of operational leadership comes into play, to build compelling, evidence-based plans that show how we’ll protect local communities and invest for the future.
On the execution side, projects like the Thames Tideway Tunnel project in the UK prove what’s possible when clients, contractors, and communities align around modern ways of working and transparency. That’s the model we need to replicate at scale. FYLD is excited to be part of that next phase, helping water companies use digital tools to plan better, execute more predictably, and deliver the scale, safety, and visibility these rebuilding programs now demand.
As AI continues to ramp up and become a bigger part of every project (and society writ large), what does that mean for the water industry, considering the massive amount of water that data centers require?
AI’s growth is as much a water story as it is an energy story. As data centers and “private power islands” scale up to feed AI’s energy appetite, they bring major water demand with them and create new infrastructure bottlenecks. For water utilities, that means they will need to approach these data center customers with long-term partnership and transparency. Early alignment on siting, cooling, reuse, and redundancy planning will determine whether local networks can cope.
As AI accelerates, the utilities that succeed will be those that build strategic partnerships with data center operators, plan for long-term community impact, and adopt modern, scalable ways of working.
The water industry has been accused of being late adopters of digital tech, but that is mostly because of the importance of delivering safe water — the “tried and true” typically wins the day. The industry’s relatively higher average age also contributes, being that most are not digital natives. How do you see the pace of adoption moving forward?
I actually believe that starting next year, we are going to see the pace of technology adoption in the water industry accelerate. As the workforce turns over and a new generation of leaders steps in, the “tried and true” won’t go away, but it will be seen in better tools, automation, and AI. Those who are known to be late adopters or resistant to tech are beginning to retire, and the new demographic of workers entering the field will lower barriers to deploying digital transformation across teams.
This shift aligns with a broader move toward outcome- and value-based leadership where success is defined by measurable improvements in safety, compliance, community impact, and cost. By 2026, the defining mindset will be “permit-to-operate as a product,” with those outcomes delivered through dashboards and service-level agreements (SLAs) rather than spreadsheets and back-office files.
What are some operational tasks that can be simplified and/or improved by implementing digital technologies at the utility level?
Digital tools are becoming more essential as utilities face the perfect storm created by lead line and PFAS mandates. These regulations demand an unprecedented scale-up in workforce, capital deployment, and program management, which is proving to be more than what traditional processes can handle. Technology helps these teams avoid the chaos of crews being dispatched inefficiently, materials being mislocated, rising costs, or escalating compliance risk.
Platforms like FYLD give leaders real-time visibility into where crews are, what they’re accomplishing, and what’s slowing them down — making room for quick adjustments that keep tasks like large-scale lead line replacement and water treatment programs on track. They also help standardize workflows across hundreds of sites, making it safer and easier to train new workers as utilities rapidly expand their teams.