How Energy and Utilities Companies Can Get AI Ready

For years, experts have been discussing the advancement of artificial intelligence (AI), including its significant role in utilities and the development of utility-based agents. Machine learning and automation, once emerging technologies, have now reached a pivotal moment where they have become mainstream and are being widely implemented in businesses, particularly in the utility sector. This integration of AI in utilities and the deployment of utility-based agents marks a transformative phase in how businesses leverage technology for operational efficiency and customer service.

The turning point for the industry was the release of tools like ChatGPT that put AI in the hands of almost anyone. Companies like OpenAI, thanks to the use of ChatGPT, are gaining access to a proliferation of training data. AI is getting smarter and faster simply because more people are training it. That’s why you’re hearing about AI so much in the news.

For energy and utility companies in particular, AI has the potential to help businesses run better.

“AI has the potential to cut energy waste, lower energy costs, and facilitate and accelerate the use of clean renewable energy sources in power grids worldwide,” explains a report from Deloitte. “It can also improve the planning, operation, and control of power systems and can be used to improve interactions with customers and field workers.”

To reach its potential, the humans behind AI implementation in an energy company need to be smart about executing. This process begins with an organization’s digital transformation strategy, which should specifically enable utilities to adapt to new technologies efficiently.

Why digital transformation is a necessity

“By 2025, 40% of energy and utilities companies will face a 50% increase in capital demands triggered by resource scarcity and soaring demands,” explains a Gartner article.

Meanwhile, the energy and utilities sector is experiencing the combination of heightened customer demands in addition to talent turnover. Gartner analyst Rich McAvey elaborates:

“Energy companies are expanding the scale and scope of digital innovations to drive efficiency, transform operations, and diversify revenue. CIOs and digital leaders need to understand how to align technology investments with strategic business goals.

Informed and intelligent decisions, particularly in the energy sector, are critical for every step in the digital transformation journey. In today’s resource-constrained economy, with the utility of AI becoming increasingly evident, there’s simply no wiggle room for error.

Every organization will need its own unique strategy for digital transformation and getting AI ready. Consider AI in the utility industry, as an example. Here are some recommendations to follow.

Practical tips for getting AI ready in the energy and utilities sector

1. Ensure that your customers are the focal point of your strategy 

With customers at the core of your strategy, integrating AI for utilities positions you well for business growth. Optimizing energy management through AI helps in gaining a deeper understanding of your customers’ needs and behaviors. This customer-centric approach, enhanced by AI, enables you to identify pain points, discover patterns in energy usage, respond effectively during emergencies, and recognize problems in energy distribution that require immediate attention.

Your software can help with ensuring that your field service organization is taking a customer centric approach. Consider the case of CHEMET GLI, a European company that specializes in installing, removing, and exchanging liquefied petroleum gas (LPG) tanks, in addition to providing emergency services.

“There came a point where we needed to improve our operations,” explains Adrien Wicker from the IT services team at CHEMET GLI. “We decided to look for a field service management software that would allow us to optimize our technicians’ routes and track our customer contacts, including work order history and comments.”

“Our previous process was way too cumbersome and hindered our ability to develop our business and grow. We had little to no visibility into our short and long term operations. The catalyst came when 2 large customers of ours wanted us to interface with their data exchange system.”

Before choosing software to begin automating your own operations, it may be helpful to research your customers’ roadmap for data infrastructure.

2. Know exactly how and where it makes sense to implement AI

Leading field service companies turn to AI because they understand that it’s the only way to efficiently utilize the data being collected by their customers’ equipment, and to optimize their technicians’ travel schedules. Incorporating a utility-based agent in AI enhances this process by evaluating and acting upon data in a way that maximizes utility or performance. This data is only as valuable to the extent to which it gets put to work. In the realm of asset management, the effective use of AI-driven insights is crucial for managing assets more efficiently, predicting maintenance needs, and optimizing resource allocation.

When leveraging data, it’s important to focus on precise use cases. As an example, you can use artificial intelligence to optimize your field service management practices in real time. AI makes it possible to consider a range of parameters when planning service calls, including the type of service needed, predictive maintenance, and technician locations/skills.

With artificial intelligence in utilities industry, you have the information needed to get the right technician to the right location at the right time to maximize the chances of resolving the customer issue on the first visit. The software itself uses machine learning to adapt based on work order histories, previous technician scheduling strategies, and information that systems continue to harness.

3. Be prepared to leverage 5G

In the energy and utility space, real-time communication networks are crucial. Especially in the event of an outage, natural disaster, or stressful situation, instantaneous communication is what helps projects go smoother.

With faster mobile internet speeds, field service providers can deliver more real-time services and improve communications as a result. With this foundational infrastructure, a utility based agent in AI will be especially useful for developing models, accessing data, and supporting human decision making.

Across the United States, funding is becoming increasingly available to support the energy industry, including initiatives for energy efficiency and renewable energy. As energy and utilities companies embrace AI, understanding the utility function in AI example becomes crucial, particularly in the context of 5G rollout plans in your service area. This advancement means potentially partnering with telecommunications companies, enhancing the value and importance of energy and utilities companies in an evolving technological landscape.

5G will be crucial for the future of AI and for energy and utility companies to meet the rising demands of energy consumption.

Final thoughts

The best implementations of AI technologies and goal based agents will focus on helping empower people rather than replacing jobs. Automation is valuable for systematizing difficult tasks so that human minds can work more efficiently. The key is to focus on relieving business bottlenecks and to help people work smarter rather than harder throughout the organization. As jobs get harder and more complex, AI can take on more of the lift.

To learn more, download our latest whitepaper “Digital transformation blueprint for Energy & Utilities companies: Bringing operational efficiency to work orders and maintenance”

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