Smart devices are no longer a luxury or reserved for tech enthusiasts: 45% of US internet-connected households have at least one smart device as of 2024, including energy-savers like smart lighting or thermostats. The growing comfort with smart technology would suggest an openness to AI-enabled devices, which can further increase comfort or optimize energy usage on a more personal level. Yet, despite this familiarity, skepticism remains.
In the most recent consumer report from Schneider Electric, “Evolving home energy consumption: Intentions, actions and hurdles to greater home energy efficiency,” almost half of consumers (44%) globally agreed that they would “never rely on AI to manage household tasks automatically,” and 41% said that they wanted “to avoid AI as much as possible.”
This disconnect highlights an important challenge: while AI has the potential to revolutionize home energy management, many consumers remain hesitant to adopt it. What’s driving this reluctance, and how can we bridge the gap to foster greater trust and adoption to reduce our residential carbon footprint?
The Knowledge Gap
Zooming out, we see that the knowledge gap encompasses more than just AI. For the past three years, EY has tracked consumers’ understanding of terms like renewable energy and sustainability. As of 2024, 26% of consumers have a good understanding of what these words mean—a figure that has not changed over three years of tracking.
There are similar tensions between consumers’ stated knowledge of how to conserve energy and what they actually do. In the Schneider Electric report, consumers’ most used method for saving energy was turning off lights; with 58% of respondents doing so. However, lighting only represents 5-7% of energy consumption in the US, so shutting lights is helpful and important, but does not save a significant amount of energy. However, knowing that these kinds of fundamentals are still poorly understood makes AI skepticism less surprising.
With this in mind, there is still a lot of education to be done when trying to close the knowledge gap. SE’s data about mistrust in AI joins a large pool of similar findings. The Journal of Hospitality Marketing & Management recently published a study which found that explicitly mentioning AI in a product description decreased a consumer’s willingness to purchase that product. That reluctance increases for purchases or products deemed “high-risk,” like “AI-powered cars” or “AI-powered illness diagnosis.” We can conclude that energy falls into that category based on Schneider Electric research: not many customers are willing to trust AI with tasks like EV charging (31%), managing energy use (32%), or managing heating and cooling (33%).
Understanding Priorities
With such a deep knowledge gap, figuring out where to start can be difficult. Focusing on global consumer priorities can help guide energy and AI companies to the best strategies.
First and foremost are efficiency and affordability, which are inherently linked. SE data found that 82% of consumers believe efficiency is either somewhat or very important at home. When taken with the fact that 37% of global households struggle to pay current energy bills, efficiency can mean doing right by their pocketbooks rather than the planet. This is underscored by the same research finding that 54% of respondents cannot or will not pay extra for clean energy, and 48% of that population cited affordability as the reason.
Energy price concerns also mean electrification may not have much appeal, despite its role in reducing emissions. Using more electricity inherently means paying more, but as we know, consumers already struggle to pay their bills. Even those who can afford electricity bills now may not be able to in the near future: 67% of consumers would not be able to cover just a 10% increase in their bill.
However, two consumer priorities naturally suggest AI as a solution: personalization and simplification. 67% of consumers have expressed a desire for “personalized energy solutions.” The same report also found that 65% of respondents “know how to start making sustainable energy choices, but 70% say they will not spend more time or money doing so.” By focusing messaging on ease of use and personalization capabilities rather than on AI as a technology, energy companies are better able to meet consumer needs.
The Next Steps
With these factors in mind, energy technology companies can devise clearer strategies to encourage the AI transition while maintaining a strong customer relationship.
First, consumers have shown their desire for easy-to-understand terms. Rather than promising huge changes or hard-to-conceptualize gains, convey what the technology can do for people now and what’s in it for them to switch now, not in the future. For example, current AI technology can already optimize usage based on consumer behavior and energy prices. Instead of expressing the benefits as a 5x increase in efficiency, for example, translate that same idea into currency: how much does it save a user on average?
Furthermore, it’s critical to tailor messages to different audiences. For example, 35% of consumers signaled a willingness to have AI help them manage their homes; they will be more open to tech-forward messaging. Another population is skeptical about AI for concerns about data privacy, for example. In this case, it’s important to address rather than dismiss these issues, both to deepen consumer understanding and establish trust. Emphasize that control always rests in the consumer’s hands.
Ultimately, the most successful strategies will focus on the tangible benefits to demonstrated priorities. With affordability as a concern, providing a range of adoption methods at different price points, rather than requiring a complete overhaul, will likely attract more consumers. Partnerships between energy and tech companies can also reduce adoption costs; for example, some energy companies have begun offering free smart technology to customers. Reducing the mental load of affordability in these ways can help increase the likelihood of purchase.
The Future
While current technology can realize great benefits, AI has not reached its full potential to change how we consume and manage energy.
We are seeing the rise of Home Energy Management Systems (HEMS) designed to work with current infrastructure or which require only a few pieces of technology to get started. Some of these systems have begun integrating models with natural-language processing (NLP). With these systems, consumers can ask a question in their own words and get a comprehensible response instead of trying to discern the magic phrase that will give them the information they actually want.
By making AI understandable and adoptable, energy companies can provide consumers with greater control over their energy usage. Whether or not they embrace AI for lower energy bills or from a desire to live more sustainably, the gains in efficiency are the same. These gains may be small on an individual level, but consider this: over 90% of the world now has access to electricity, meaning individual gains can add up to very big impacts on global energy usage.
In short, AI adoption for energy management isn’t just a win for consumers or energy providers. It’s a win for reducing emissions in the fight against climate change, too.
