The Impact of Artificial Intelligence in the Utilities Industry: Innovations and Strategies 

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The rise of generative AI is revolutionizing numerous industries with algorithms capable of generating text, images, computer code, and innovative data models. This technology is becoming a focal point even in the boardrooms of the Utilities Industry, proving its cross-sector value. 

According to a survey conducted by the Capgemini Research Institute, 95% of public and energy service companies interviewed globally have discussed Generative Artificial Intelligence in the past 12 months. Of these, 33% have already initiated pilot programs to explore various use cases. While nearly 40% of companies have established dedicated teams and budgets for generative AI, 41% adopt a cautious “wait and see” strategy. 

This article examines how the use of Artificial Intelligence in the Utilities industry enhances customer experience, asset management, and the optimization of staff and resources. 

Revolutionizing Customer Service in the Utilities Industry with AI

Energy service companies face challenges in improving their service offerings and meeting the rising expectations of customers. While traditional communication methods like telephone and email are still prevalent, they lack the agility required by modern demands. 

The adoption of Artificial Intelligence in the Utilities Industry, especially through the use of AI chatbots and machine learning, offers organizations the opportunity to excel in customer service. 

AI automation allows for: 

  • Efficient management of routine inquiries; 
  • The provision of self-service options for scheduling and managing appointments; 
  • Streamlining of customer transactions without the need for additional human resources. 

Moreover, data analysis helps providers to understand consumption patterns, enabling them to offer advice on energy and water conservation and value-added services such as energy audits. 

IFS Cloud is already at the forefront, providing utilities and other sectors with cost-effective means to exploit AI-powered bots, natural language processing (NLP), and technical capabilities for remote support. 

By automating routine activities and using learning algorithms to anticipate user needs, the experience is transformed for both customers and staff. 

Modernizing Energy Infrastructure with AI 

Global utility networks are facing the significant challenge of aging infrastructure, with about 70% of the U.S. energy grid having surpassed the 50-year mark, as revealed by a recent report from the United States Department of Energy

In the context of climate change, energy providers are working to modernize the grid to support the electrification of renewable energies, ensure resilience, and facilitate a bidirectional network that supports self-generation from microgrids. 

Faced with limited resources such as transformers, turbines, and photovoltaic solar panels, companies must extend the operational life of existing assets through efficient maintenance and monitoring to ensure reliability and safety. 

Organizations are therefore turning to advanced digital solutions like IFS Cloud, which uses Artificial Intelligence for optimized and simplified asset management throughout their lifecycle. 

IFS Cloud leverages big data analytics and machine learning to prioritize assets at risk of issues or premature failure. This AI-driven predictive asset performance management approach improves both financial management and supply chain management

With the use of predictive algorithms, IFS Cloud helps to solve critical questions such as “Do we have the right inventory in the right places to meet the forecasted demand?” and “Can we implement just-in-time strategic sourcing to ensure the best price in a competitive market?”. 

Using AI to Address the Damage from Climate Change 

The impacts of global warming are becoming increasingly apparent, with a growing frequency of extreme weather events causing significant faults and disruptions in infrastructure. 

Events such as heatwaves triggering wildfires, freezing temperatures leading to power outages, and unprecedented rainfall causing floods pose crucial challenges for infrastructure resilience. 

The use of AI-driven Enterprise Asset Management (EAM) software enables the modeling of future scenarios through “what-if” analyses based on current and historical sensor data. 

This approach encompasses: 

  • The projection of environmental risks; 
  • The forecasting of load and population growth; 
  • The assessment of potential consequences of field failures. 

In the context of the transition towards decarbonization and electrification, Artificial Intelligence in the Utilities Industry plays a pivotal role in estimating the additional capacity needed to meet increasing demand, significantly influencing infrastructure planning decisions. 

Organizations can evaluate whether to maintain, replace, transfer, or adapt existing assets, considering critical factors such as the risk of fires during extreme heat or ice accumulation in harsh winters. 

Finally, financial modeling is essential to estimate the total cost of ownership, supporting informed decisions about maintaining or replacing infrastructure in high-risk areas. 

AI’s Contribution to Workforce Management 

Effective management of the workforce, skills, and resources is a critical challenge for public service companies. It’s vital to maintain operational stability by ensuring a suitable labor force, while also avoiding overstaffing. 

Given the global shortage of specific skills, it becomes crucial to balance effectively the use of contractors and internal resources. 

Artificial Intelligence and Automation in the Utilities Industry are emerging as vital tools to support workforce planning and skill development across the sector. 

According to insights from the IFS Customer Advisory Committee, utilities are facing a dual challenge: maintaining staff and skills for the existing network while acquiring the new technological skills required for the evolving network. 

With limited resources available, the use of AI and automation can transform resource management and provide essential support in recruitment, training, and upskilling initiatives during this phase of the industry’s transition. 


In a heavily regulated industry with clear responsibilities for ensuring energy continuity and meeting demand, it’s unsurprising that the adoption of AI has been cautious so far.  

However, with the projected global use of AI in the energy sector reaching $7.78 billion by 2024, utilities must recognize and seize this opportunity. While caution is wise, it is crucial for utilities to educate themselves on how AI can be beneficial and the necessary measures for its effective management. 

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