AI’s Misunderstood Role in Wastewater
As the new year begins, the focus turns to the challenges and opportunities ahead for wastewater infrastructure. With artificial intelligence (AI) now a tangible component of inspection workflows, the conversation is shifting not only toward the technology itself but toward how it is reshaping the way teams work, collaborate and support their communities. The industry faces rising inspection volumes, expanding and aging networks and shrinking review capacity; conditions that demand tools that help professionals work smarter, not harder.
No one digs a trench with shovels when an excavator exists. The machine does not replace the crew; it enables more efficient work. Likewise, AI can handle the heavy lift while wastewater professionals remain focused on decision-making.
AI’s emergence in wastewater inspection reflects how far the industry has progressed from the fully manual workflows many practitioners began with. Twenty-five years ago, inspections relied on limited technology. As software advanced, NASSCO’s PACP™, LACP™ and MACP™ standards were developed to support consistent data collection and analysis. Technology has improved significantly and NASSCO standards continue to guide the industry. However, staffing models and review workflows have not scaled at the pace needed to meet today’s demands. High-fidelity inspections remain essential to reliable analysis, yet even the most skilled manual workflows struggle to keep up with growing volume. Bottlenecks routinely stem from the imbalance between inspection needs and reviewer capacity.
AI-generated coding does not replace the need for skilled operators and analysts. Conversely, it reduces baseline workload so expertise can be applied where it matters most. By handling portions of coding and review that are prone to fatigue, such as joints, service connections and densely clustered defects. AI provides a consistent first interpretation and allows human attention to shift to context and nuance.
Early improvements seen when AI is introduced into CCTV workflows commonly include better data consistency and reduced pressure on field operators. Even among experienced, NASSCO-certified operators, interpretation varies; human judgment is not perfectly uniform. Three operators reviewing the same pipe may identify the same condition yet assign three different defensible codes. These variances ripple into planning, rehabilitation prioritization and budget decisions. With AI in the workflow, baseline coding becomes more consistent, allowing operators to focus on capturing high-quality video and coordinating field work. Human expertise supplies nuance and situational understanding, while AI manages repetitive tasks.
AI’s role is often misunderstood in the wastewater workflow. It is not an all-knowing system; it is a human-designed tool built to mirror analytical tasks within the limits of its training. AI shines when used as a decision-support tool rather than a decision-maker. It identifies patterns confidently but can also be confidently inaccurate. Its strength lies in delivering a dramatically accelerated and consistent baseline that reviewers can refine. In wastewater inspection workflows, trust is earned through validation whether confirming human or machine outputs. Even so, combining AI’s consistency with human skill yields speed and reliability neither can achieve alone.
The goal is to improve final data acceptance faster than traditional workflows allow. Many municipalities rely on multilevel review: the operator codes the inspection, a senior reviewer audits accuracy and in some cases, a third layer verifies the data before use. Each step adds value but consumes capacity. With AI helping to establish baseline consistency, reviewers can maximize efficiency by concentrating on cases requiring deeper analysis rather than rechecking for uniformity. Conversations naturally shift from “How do we meet service goals with this backlog?” to “Let’s deploy people where they create the most value.”
With a decline in experienced personnel across the industry, teams are being left with rising workloads and fewer senior reviewers. The need is not only for more inspections but for balancing sound, budget-responsible decisions while maintaining capacity for mentoring new talent; AI helps to create that bandwidth. Contractors can scale without overburdening staff and engineers can maintain confidence in growing datasets. Applied thoughtfully, AI supports organizational growth without compromising quality or eliminating human involvement.
Ultimately, the partnership between human expertise and AI is the true advancement not the technology alone. The industry still requires the nuance and judgment only people can provide, while AI alleviates the backlog and repetition that have weighed on teams for years. Using tools does not diminish human roles; it strengthens them, enabling professionals to shift from constant reaction to thoughtful strategy. Municipalities gain a clearer, more reliable understanding of their networks. AI can elevate underground infrastructure management when industry professionals use it to amplify their work. This partnership is not flashy or magical, it is a logical, responsible evolution of workflows designed to meet today’s growing demand.
Jax Vollmer is the Chair for the ADR Workgroup, Co-Chair for the Software Committee at NASSCO and Technical Manager for AI Product Delivery at ITpipes. She can be reached at jax.vollmer@itpipes.com.
This column is featured in our January issue of American Infrastructure, read the print version here.
