Closing The Workforce Skills Gap On Artificial Intelligence And Machine Learning At Water Utilities

By Kevin Westerling,
@KevinOnWater

A Q&A on embracing AI

Although artificial intelligence (AI) and machine learning (ML) have been under development and talked about for years, the practical implementation of these technologies came fast and furious. Now, with their rapid growth across all industries, many are feeling overwhelmed. This is especially true in the water/wastewater sector, where the median worker age is 48, according to the U.S. EPA, with up to 50% expected to retire over the next 10 years.

This offers good and bad news for AI/ML implementation. On the downside, older workers are less inclined to embrace digital technology; the silver lining, though, is that most incoming workers are “digital natives” who welcome it with open arms.

Despite these generational differences, no one should opt out altogether. The benefits of AI and ML for utility operations, the public, and the environment are so profound that the entire industry should do their best to wrap their heads around its functionality and implications.

To that end, I consulted Marina Donovan, Vice President of Global Marketing, ESG and Public Affairs for Itron, to understand where utilities stand with regard to AI/ML adoption, what’s holding them back, how to overcome the challenges, and why it’s important for water and wastewater management.

In what ways can water and wastewater utilities benefit from AI and ML?

Water and wastewater utilities stand to see numerous benefits from adopting and integrating AI and ML, but the primary benefits will be the optimization of operations and improvements surrounding the reliability of service delivery. This year’s Itron Resourcefulness Insight Report explored current trends and future expectations of AI and ML on utility operations and strategies. While we surveyed electricity and gas utility executives, what we learned could apply to water utilities as they navigate their AI and ML adoption journey. The research found that 43% of utilities surveyed believe AI and ML-based tools would impact the ability to detect and manage dangerous situations. In a tie for second, 29% of respondents stated that benefits would be seen in business productivity as well as customer engagement. For water utilities, AI/ML-driven tools offer opportunities to integrate automation into routine processes such as equipment maintenance and data management. Automation not only unlocks new efficiencies but also reduces reliance on manual or time-consuming processes — both critical for ensuring reliability and optimizing water distribution.

Using AI and ML, water utilities can gain fresh and advanced insights that enable them to conduct predictive maintenance through real-time system data analysis. This stream of data is what allows utilities to identify potential equipment failures before they occur, preventing costly downtime. Additionally, AI can enhance water distribution and treatment processes, which is crucial for reducing operational costs.

From a customer perspective, AI and ML can support water utilities in improving customer service and promoting sustainability efforts. The flow of information between both utilities and customers plays a vital role in predicting demand, tracking consumption patterns, and improving billing by detecting potential leaks. As severe weather patterns become more frequent, water utilities must manage critical resources and ensure that operations are minimally impacted.

Are these technologies being widely implemented? What are the factors or barriers impeding implementation?

One example of AI implementation in the water sector is with VODA.ai, which helps utilities by performing AI-based analyses. According to a study by Utah State University, approximately 20%, or 425,000 miles of water pipes in the U.S. and Canada, need to be replaced. Together, VODA.ai and Itron are simplifying how water utilities identify and predict which pipe assets need to be replaced, rehabilitated, or contain lead with the introduction of Pipe Asset Management. This solution proactively mines public data, which feeds into VODA.ai’s AI engine and is presented in an interactive tool to identify pipes that need replacing or rehabilitating.

While many utility managers and operators recognize the importance of adopting advanced technologies to meet increasing demands from customers and unlock the benefits of AI and ML, widespread implementation among water utilities comes with challenges. One of the most significant barriers is the lack of technical expertise, a concern highlighted in the Itron Resourcefulness Insight Report, where 43% of surveyed electricity and gas utility executives cited a skills gap among their workforces. This challenge is also relevant to water utilities, as successfully integrating AI and ML systems requires staff proficiency in both traditional operations and advanced data analysis.

Another key challenge highlighted in the report is the cost of implementing AI and ML technologies. These expenses can be particularly challenging for utilities operating on limited budgets, given the initial investments and ongoing maintenance costs involved. Additionally, 39% of surveyed utilities cited the ongoing reliance on legacy systems as a barrier to AI and ML adoption. Many older systems lack the infrastructure needed to support the data-intensive nature of these technologies, creating challenges in integration and performance. Water utilities face similar issues with aging infrastructure and will need to make strategic investments to fully leverage the benefits that AI and ML can offer.

What would be the impact of NOT addressing the workforce readiness issue in terms of AI and ML?

A skilled workforce is an essential component of operating AI and ML technologies. Without it, operational inefficiencies that already exist could continue to grow while diminishing any future opportunities for optimization. Unprepared workforces could also stall any forward movement or progress from being made in areas such as predictive maintenance, real-time decision-making, and resource conservation. Furthermore, not tapping into the power of AI could hinder progress in improving operational costs, delays in addressing critical infrastructure challenges, and decreasing service delivery interruptions.

For water utilities, a skilled workforce equipped with AI and ML technologies can significantly enhance operations and customer relationships and satisfaction. As population growth continues to drive higher demands for water, AI-powered solutions not only streamline service delivery but also reduce disruptions. Furthermore, with the increase in severe weather events such as prolonged droughts and hurricanes, the importance of AI and ML solutions to manage resources, predict service interruptions, and adapt to changing conditions become more evident. Integrating these technologies can increase efficiency in water utilities, strengthening both the workforce and critical infrastructure.

What are some proactive steps utilities can take to bridge the workforce skills gap?

There are several ways for water utilities to bridge the skills gap within their workforce. The first proactive step is to invest in education and training programs to upskill current employees. A range of training options is available, such as specialized AI training programs tailored to water utilities, with a focus on practical implementation. Additionally, industry associations like the American Water Works Association and International Water Association provide workshops, webinars, and resources on AI applications for water management. This investment will equip employees with the tools and knowledge needed to manage both traditional utility operations and advanced technologies such as AI and ML. A second approach is to leverage partnerships with trade organizations and educational institutions. These collaborations can create effective pipelines for recruiting and training the next generation of water utility operators, ensuring they possess the digital skills necessary for AI/ML integration.

Additionally, water utilities can focus on local workforce development by tailoring training programs to address regional requirements. Highlighting local challenges helps utilities prepare employees for the unique operational demands and infrastructure upgrades in their area. By implementing these proactive measures and adopting modern solutions that leverage AI and ML technologies, water and wastewater utilities will be more prepared to take full advantage of future advancements in AI and ML. This approach not only addresses current skills gaps but also positions utilities for growth as technology continues to advance.

Itron supports these efforts through our STEM education initiatives and community partnerships to equip future generations with the skills needed for careers in energy and technology. For more details on these initiatives, see Itron’s Corporate Sustainability Report.