While AI exploded into the mainstream in 2023, it has been applied across industries to optimise and automate operations for many years now. In the energy sector, we are already seeing AI transform aspects such as predictive maintenance, grid management, and supply and demand forecasting.

However, there is still a huge amount of value to capture from AI, particularly when it comes to improving the customer experience and reducing carbon emissions. In 2024, we’ll see the use of AI in the sector become much more widespread and intelligent, bringing us closer to unlocking the technology’s full potential. 

Here we take a look at some key ways in which AI is set to transform the energy industry this year.

#1 – Customer service

Bots are already commonplace in energy suppliers’ customer service arsenal. They enable instant help, 24-7, and can help suppliers out of a tight spot when inflow peaks and wait times would otherwise spiral upward. But historically these bots have often fallen short of delivering the level of assistance that consumers rightly expect.

In 2024 bots are upping their game. They’ll be increasingly capable of automatically and intelligently completing tasks rather than creating more work for the customer such as pointing you to an FAQs page which is what we have traditionally seen. The help they offer will be personalised to each customer’s individual situation, rather than relying on one-size-fits-all auto responses and inflexible chatbot scripts. Breakthroughs in large language model (LLM) technology will give them a more accurate understanding of customer intent. No more endless loops of “I’m sorry, I didn’t get that, could you rephrase your question?”.

However, even with increasing levels of sophistication, bots are not the right answer for all situations. Some consumers, and some queries, will always require the human touch. So human agents will still have a critical role.  Soon, we will see the emergence of LLMs that are trained with energy specific concepts and language making them more able to answer complicated energy requests with accuracy and efficiency. These assistants will automatically handle many of the more tedious and robotic workflows (e.g. using generative AI to quickly draft email responses), allowing agents to concentrate on the customer and that all-important human interaction.

#2 – Home energy management

In order to reach net zero, we will need to transition to smart, electrified homes.  That’s why we’re excited to see an accelerating adoption of solar batteries, home electric vehicles (EVs) chargers, heat pumps, smart thermostats and more. This technology has the potential to dramatically reduce our domestic energy usage, to shift it to greener times of the day, as well as interacting with flexibility markets to dynamically buy and sell energy back to the grid yielding even further savings on behalf of the supplier and the customer.

This does come with a challenge, though. Each smart device runs independently. It doesn’t know what the rest of the house is doing. Sometimes devices work against each other, cancelling out the benefits of balancing energy usage within the home. Furthermore, understanding what they’re doing is a headache for the consumer, with the information split across multiple apps.

This year, we expect a smart home to be a single coherent system not a collection of disparate, disconnected devices all doing their own thing. We want things to work together without us thinking about it. We want to look in one place to understand what our devices are doing, and how that’s saving both money and carbon emissions.  

Enter AI. The coordination of smart energy devices isn’t a trivial problem. Even for a simple home setup with an EV charger and a solar battery, getting these devices to work together optimally requires an AI system that can predict solar generation, home usage, and EV driving habits at the individual property level, and understand how these interact with the customer’s tariff.

In 2024 we’ll see the clunky experience of setting up, monitoring, and controlling separate energy devices replaced with AI-driven, whole-home energy management solutions that will increase consumer savings and decrease emissions. 

#3 – Grid management and the rise of the virtual power plant

The proliferation of EVs together with the need to introduce more (intermittent) renewable energy to the grid poses challenges for our infrastructure. Unmanaged, there will be increasingly large and frequent mismatches between the amount of energy being generated and the amount consumed.

Acting in a coordinated way, our connected smart homes will be able to respond to these imbalances, forming a ‘virtual power plant’ (VPP).

Demand will be scheduled, at both a national and local street level, in order to keep our increasingly complex energy ecosystem balanced, protect our infrastructure and achieve a greener energy mix.

Early trials have been promising but have often relied on consumers manually adjusting their schedules when energy companies inform them of impending spikes in supply – this requires participating consumers to be at home at the right time in order to respond, and for them to figure out how best to make use of this cheap green energy. 

In 2024, as consumer trust in AI and smart devices grows, we’ll see more suppliers with AI-driven VPP management software that can respond to imbalance events, automatically scheduling each home’s consumption so that consumers are not inconvenienced or out of pocket.

The same AI software will help suppliers design innovative new tariffs to allow consumers to benefit financially from participating in a VPP.

The continued application of AI in the energy sector will lead to greater efficiencies, automation and improved services, benefiting consumers and providers alike. Perhaps most importantly, the technology will help us transition more quickly to electrified homes and renewable energy, accelerating the shift towards net zero and a cleaner, greener future for the next generation.  

 Crystal Hirschorn is chief technology officer at Zoa.

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