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The utility industry is facing a lot of challenges and opportunities in the digital age. Renewable energy sources, changing customer expectations and stricter regulations are reshaping the way utilities operate and deliver value.

Utility companies know that staying ahead of the curve means embracing innovation and leveraging the power of artificial intelligence (AI), notably generative AI (gen AI) and the promise it holds for the sector.

Gen AI can create new data, content or scenarios from existing data, using techniques such as generative adversarial networks (GANs) and variational autoencoders (VAEs). These techniques use deep learning methods to train neural networks that then generate realistic and diverse outputs, such as images, texts, sounds or videos.

Gen AI can help utilities to simulate new situations, optimise processes and enhance customer experience across the entire value chain. 

We have identified eight potential scenarios across the value chain where gen AI can be applied to improve efficiency, reliability and customer satisfaction:

  • Asset management – Preventive maintenance & optimisation

  • Network grid resilience & optimisation

  • Energy mix: Renewables & storage

  • Field services optimisation

  • Energy trading optimisation

  • Demand response management & efficiency programmes

  • Customer services: Omni-channel digital assistants & customer communication

  • Sales & marketing: Personalised product offerings, pricing strategies and campaign content

Asset Management

For utilities, the uptime and performance of their assets are critical for delivering reliable and cost-effective service. Utility companies regularly monitor and maintain their assets using data from sensors, inspections and historical records. However, this can be time-consuming and costly., especially for remote or hard-to-access assets.

Gen AI can help utilities enhance their asset predictive maintenance by creating new data sets from existing data, such as images, texts and weather data. This can help utilities detect potential issues early and dispatch unmanned monitoring vehicles, such as drones or rovers, to address them. Gen AI can also help utilities automate their asset documentation by ingesting records in large language models that can provide relevant and consistent data in a conversational and interactive way.

Network Grids

The integration of renewable energy sources into the grid poses challenges for utilities, such as grid stability, load balancing and outage recovery. Renewable energy sources are often dependent on variable and unpredictable weather conditions. To manage these challenges, utilities need to plan and operate their grids in a smart and flexible way, using data from various sources, such as demand patterns, weather forecasts and grid status.

Gen AI can help utilities to improve their grid resilience and optimisation by:

  • creating synthetic data sets and simulating scenarios that can test the grid's vulnerabilities and performance under different conditions, such as equipment failures or natural disasters

  • analysing geographical data, load patterns and historical outage data, and generating alternative grid configurations for improved redundancy, load balancing and rapid recovery.

Energy mix

Utilities need to use more renewable energy sources in their energy mix to move towards a low-carbon economy while keeping the supply safe and affordable. Renewable energy sources, such as solar and wind power, can have environmental and economic advantages, but they need sophisticated management systems and storage solutions to deal with their variation and unpredictability.

Gen AI can help utilities use renewable energy and storage better by simulating scenarios that maximise utilisation and efficiency, whilst considering factors such as weather and demand changes. By generating synthetic data that mimics characteristics and behaviours, gen AI tests the feasibility of new or uncommon energy generation technologies or sources, like geothermal energy or hydrogen, and supports integration challenges of these new sources by simulating different scenarios and outcomes, such as grid stability, energy storage and system constraints. 

Field services

Field services are an essential part of the utility industry, involving the installation, maintenance and repair of assets and equipment, as well as the interaction with customers and stakeholders. Customer satisfaction, as well as utilities' operational effectiveness and earnings, can be influenced by field services. However, field service delivery may be impacted by skills shortages, high turnover, complex tasks and customer expectations.

Gen AI can optimise field services by providing self-service tools that can identify knowledge articles and generate step-by-step guides to address technical issues and improve the customer experience. It can also help speed up employee onboarding by capturing and organising the unstructured knowledge and experience of the existing workforce and making it accessible to the next generation of workers.

Energy trading

Energy trading is a vital activity for utilities, as it involves the buying and selling of electricity and gas in the energy market, as well as the management of risks and opportunities. Energy trading can affect the competitiveness and profitability of utilities, as well as their ability to meet the demand and supply needs of their customers. However, energy trading can be a complex and dynamic process, as it involves multiple variables and factors, such as price, demand, supply, regulations and weather.

Gen AI can help utilities trade energy more efficiently by quickly finding the best strategies and prices while considering the environmental impact of energy sources. It’s also a powerful tool for the trading market by simulating real-world conditions to create new trading algorithms, strategies and policies, and enable traders to assess their decisions and refine trading approaches before going to the actual market.

Demand response

Demand response management and efficiency programmes are initiatives that aim to reduce the energy consumption and demand of customers, especially during peak periods, by offering incentives, such as discounts, rewards or dynamic pricing. Demand response management and efficiency programmes are usually manual and lack personalisation but have the potential to balance the grid, reduce costs, and improve customer satisfaction and loyalty. 

Gen AI can help utilities to create targeted, personalised demand response and efficiency programmes by analysing real-time data from smart meters and IoT devices, and generating new data points from deep learning. It can help utility companies understand energy usage patterns, preferences and customer needs, and provide customised recommendations and incentives based on segments and profiles – it can also measure the effectiveness and impact of these programmes, and adjust them accordingly.

Customer services

In the utility industry, customer service can be challenging and costly involving a large skilled workforce, multiple channels and complex systems to manage communications with customers and stakeholders on issues such as billing, outages and complaints. But getting this right can influence customer satisfaction, retention and loyalty, as well as brand image and reputation.

Gen AI can improve customer service by providing omni-channel digital assistants that can mimic human-like, interactive conversational agents. These digital assistants can be trained centrally and used across channels, such as webchat, WhatsApp, messaging, social, voice, etc. Once trained with the right sources of domain data (FAQs, regulations, knowledge bases, datasets, etc), gen AI can respond to natural language questions with contextual and relevant responses that are not pre-defined. This can significantly improve digital deflection and reduce the cost-to-serve. Gen AI can enhance customer communication more widely by dynamically generating personalised content for billing reminders, service updates or new offers/discounts.

Sales & marketing

The development and promotion of new products, services and packages, as well as the acquisition and retention of customers and stakeholders are essential for utility companies. Whilst it can be expensive and difficult, sales and marketing can help utilities to differentiate themselves from the competition, increase their market share and revenue and build long-term relationships with their customers.

Gen AI can help utilities:

  • boost their sales and marketing by creating personalised product offerings, pricing strategies and campaign content

  • identify patterns and produce curated, bespoke content for users that match their interests, needs and preferences

  • create targeted ad campaigns and hyper-intuitive themes that can improve sales conversions

  • generate new marketing channel content by learning from previously successful campaigns

Overcoming the obstacles of gen AI adoption

Before utilities can benefit from gen AI opportunities, they need to make sure they have the data and expertise to meet the challenge. Data problems, such as low availability, quality or privacy, and a shortage of skilled resources can hamper adoption, and there are ethical, social and environmental considerations for ensuring responsible and transparent use of AI.

Partnerships are the quickest way of overcoming and navigating these adoption obstacles, drawing on the experience and capabilities from outside of the utility industry to apply and use gen AI across the value chain and align with business goals, customer demands and changing regulatory requirements.

Gen AI is a game-changer. It will reduce risks and improve efficiencies, and enhance customer satisfaction and sustainability. However, it requires the right data, expertise and transparency to ensure the full potential is achieved.


Vinitesh Gaurav

Director, Consulting, Manufacturing, Logistics, Energy & Utilities, UK&I, Cognizant

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Dr. Nitish Khetavath

Senior Manager, Consulting, Manufacturing, Logistics, Energy & Utilities, UK&I, Cognizant

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