Artificial Intelligence will transform the energy industry in three ways

In 2024, artificial intelligence will play a role in improving customer experience and reducing carbon emissions. Although artificial intelligence has only started to become mainstream in 2023, it has been used in various industries for years to optimize and automate operations. 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 huge value to be found in artificial intelligence, especially in improving customer experience and reducing carbon emissions. By 2024, we will see the application of artificial intelligence in this field become more widespread and intelligent, bringing us closer to unlocking the full potential of this technology.

Here’s a look at some of the key ways artificial intelligence will transform the energy industry this year.

1. Customer Service

Bots have become a common tool in the customer service arsenal of energy providers. They provide immediate assistance around the clock and can help providers out during times of traffic spikes and increasing wait times. But historically, these robots have often failed to provide the level of assistance consumers expect.

In 2024, robots will play a greater role. They will increasingly be able to complete tasks automatically and intelligently, rather than adding more work to customers like we have traditionally seen, such as pointing to FAQ pages. The help they provide will be personalized to each customer's specific situation, rather than relying on cookie-cutter automated responses and inflexible chatbot scripts. Breakthroughs in large language model (LLM) technology will allow them to more accurately understand customer intent.

Although, even with increasing levels of sophistication, robots are not the right answer for every situation. Some consumers and some queries will always require human intervention. Therefore, human agents will still play a key role. Soon, we will see the emergence of LLMs trained in energy-specific concepts and language, allowing them to answer complex energy requests more accurately and efficiently. These assistants will automate many of the more tedious and mechanical workflows, allowing agents to focus on the customer and the human interactions that matter most.

2. Home Energy Management

To achieve net-zero emissions, we need to transition to smart electrified homes. That's why we're excited to see the accelerated adoption of solar cells, home electric vehicle (EV) chargers, heat pumps, smart thermostats and more. This technology has the potential to drastically reduce our household energy use, shifting it to greener times of day, and interact with flexibility markets to dynamically buy and sell energy back to the grid, resulting in greater savings for suppliers and customers. Save more.

This does bring challenges, however. Each smart device operates independently. It has no idea what other devices in the home are doing. Sometimes devices interfere with each other and take advantage of the same household's energy use. Additionally, understanding what they are doing is a headache for consumers because the information is scattered across multiple applications.

With the emergence of artificial intelligence, the coordination of smart energy equipment is no small problem. Even a simple home setup with an EV charger and solar cells, making these devices work optimally together requires an AI system that can predict solar generation, home usage and electric power at an individual property level. car driving habits, and address how these interact with customer electricity bills.

By 2024, we will see the cumbersome experience of setting up, monitoring and controlling individual energy devices replaced by AI-driven whole-home energy management solutions that will increase consumer savings and reduce emission.

3. Grid Management and the Rise of Virtual Power Plants

The proliferation of electric vehicles and the need to introduce more (intermittent) renewable energy to the grid pose challenges to our infrastructure . If left unmanaged, the mismatch between power generation and consumption will become larger and more frequent.

Through a coordinated approach, our connected smart homes will be able to respond to these imbalances, forming a “virtual power plant” (VPP). Demand will be orchestrated at the national and local street level to keep our increasingly complex energy ecosystem in balance, protect our infrastructure and enable a greener energy mix.

Early trials are promising but often rely on consumers manually adjusting their schedules when energy companies notify them of an impending supply peak, which requires participating consumers to be home at the right time in order to respond , and let them figure out how to best use this cheap green energy.

In 2024, as consumer trust in AI and smart devices continues to grow, we will see more vendors have AI-driven VPP management software that can respond to imbalance events, Automatically schedule consumption for each household to avoid inconvenience or out-of-pocket expenses for consumers.

The same artificial intelligence software will help suppliers design innovative new tariffs so that consumers gain financial benefits from participating in the VPP.

The continued application of artificial intelligence in the energy sector will increase efficiency, automate and improve services, benefiting both consumers and suppliers. Perhaps most importantly, this technology will help us transition more quickly to electrified homes and renewable energy, accelerating the shift to net-zero emissions and the next generation of cleaner, greener futures.

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