AI is redefining energy management, cutting costs, and boosting sustainability. Experts call the shift essential for staying competitive.
AI is fundamentally reshaping energy management, replacing outdated static models and manual processes with dynamic, data-driven solutions. Traditional methods frequently left businesses faced with inefficiencies and untapped savings. Today, AI offers a smarter approach—leveraging real-time data and predictive analytics to optimise energy consumption while lowering costs.
Sustainability News spoke with Dr. Zohar Bronfman, CEO of Pecan AI, who described how AI is changing the game. “With AI, businesses can forecast energy demand based on a wide range of variables—weather patterns, occupancy levels, and even market trends,” he says. “This means minimising waste, improving efficiency, and slashing costs, all while enhancing sustainability. Companies sticking to traditional methods risk falling behind as AI-driven solutions become the norm.”
By integrating AI with IoT devices, energy management becomes simpler. Real-time monitoring and adjustments ensure businesses use only what they need, when they need it, without manual intervention.
Real-world success stories
One notable example is Google’s DeepMind, which used AI to optimise cooling systems in its data centres. The company reduced cooling systems’ energy consumption by 40% using machine learning, resulting in cost savings. Similarly Verdigris Technologies uses predictive AI to analyse commercial building systems to maximise energy efficiency, which led to 30% savings on power bills.
Bronfman envisions similar breakthroughs for mid-sized businesses. “Imagine leveraging AI to forecast energy consumption based on seasonal demand or adjusting operations in real time to maximise energy efficiency,” he explains. “These solutions are no longer futuristic; they’re the new standard for companies looking to balance cost efficiency and sustainability.”
Overcoming challenges to AI adoption
One of the most significant barriers is data quality. AI thrives on accurate, clean data, but many businesses have fragmented systems and legacy infrastructure that hinder effective integration. “The solution lies in investing upfront in robust data infrastructure, ensuring that systems – from HVAC to lighting – are interconnected, and that the data collected is reliable,” says Bronfman.
Employee readiness is equally important. AI isn’t a plug-and-play solution; it requires teams to adapt and collaborate alongside the technology. “Companies must prioritise education and change management to fully capitalise on AI’s potential,” Bronfman says.
The future of AI in energy management
In the future, AI will play an important role in integrating renewable energy into mainstream systems. As solar and wind power become more common, AI can forecast energy generation based on weather patterns, enabling businesses to store surplus energy during peak production and use stored power when generation dips.
Bronfman also highlighted the emergence of smart grids – autonomous systems that balance supply and demand. Such advancements promise to improve grid resilience, boost energy efficiency, and enhance sustainability.
Navigating regulations and sustainability goals
AI’s ability to streamline regulatory compliance is a potential advantage. By automating the tracking and reporting of energy usage, greenhouse gas emissions, and other key metrics, businesses are aided with compliance under changing environmental rules. Bronfman explains: “AI can automate the tracking and reporting of energy usage, greenhouse gas emissions, and other metrics.”
AI might dispel the notion that sustainability and efficiency are at odds. “AI demonstrates that businesses can meet and exceed environmental standards while driving profitability and innovation,” Bronfman says.
The human element: AI and behaviour
Energy management is as much about people as it is about technology. With his background in computational psychology and data science, Bronfman highlights how AI can influence human behaviour. “AI solutions that understand human behaviour can nudge individuals toward better energy use habits,” he explains. Personalised notifications and gamified feedback, for example, can motivate teams to adopt energy-saving practices.
By bridging technology and behaviour, businesses can ensure that AI solutions are effective, accepted, and implemented. “It’s this synergy between technology and human behaviour that will drive the future of energy management,” Bronfman concludes.
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