By Dbrav Dunkley, Partner, Credera
In the energy sector, CMOs face a growing challenge: how to engage customers in a historically low-touch industry while navigating market volatility and regulatory complexity. Traditional marketing efforts have often been reactive — responding to price fluctuations, policy shifts, and customer complaints rather than proactively shaping demand and engagement.
Now, AI is changing that. A recent Grand View Research report valued the global AI in energy market at $8.75 billion in 2023, with an anticipated 30.1% compound annual growth rate through 2030. Meanwhile, a 2024 IBM study found that 74% of energy and utility companies are embracing AI. This surge in adoption signals a shift: AI is no longer a future investment; it’s a competitive necessity.
AI is already transforming other industries. In marketing, for example, AI is streamlining strategies and operations. Salesforce reports that 71% of marketers expect generative AI to eliminate busy work, allowing them to focus on strategic initiatives.
For energy CMOs, the opportunity is clear: AI can revolutionize customer engagement, predictive analytics, and sustainability messaging, helping organizations stay ahead in a rapidly shifting landscape.
How AI Is Reshaping Energy Marketing
For years, energy marketing was centered around brand positioning and regulatory communication. But with AI, CMOs can move beyond storytelling to real-time customer engagement, behavioral insights, and data-driven sustainability messaging.
AI isn’t simply just another tool; it’s redefining how energy marketers influence consumer behavior, optimize pricing, and drive the clean energy transition. Here’s how:
1. AI is moving energy marketing from static to dynamic.
Traditional energy marketing has long been reactive — responding to price fluctuations, policy shifts, and customer complaints. AI changes that dynamic by allowing CMOs to predict demand trends, personalize offerings in real time, and automate responses to customer behavior.
For example, global energy provider Engie leveraged Atlas AI’s predictive analytics to target high-opportunity regions for off-grid solar expansion in Kenya. By analyzing socioeconomic indicators, electrification gaps, and population density, Atlas AI’s machine learning models helped Engie pinpoint areas with high demand and repayment potential for solar appliances, leading to a 48% increase in monthly sales in the Coast region.
AI isn’t just for ad targeting; it’s a powerful tool for market expansion, predictive customer segmentation, and demand forecasting.
2. Personalization at scale: From generic messaging to customer-specific insights.
Most energy customers only think about their provider when they receive a bill or experience an outage. AI can change that dynamic by delivering hyper-personalized energy insights, sustainability updates, and incentive-driven behavioral nudges.
AI-driven platforms, for instance, could provide personalized clean energy recommendations to customers, identifying relevant programs based on criteria such as customer type, building type, and usage levels. This, in turn, could help optimize customers’ bills, energy use, and carbon footprint.
AI should do more than automate marketing; it should build trust by delivering personalized, data-driven insights.
3. AI-powered content creation: Automating the right message at the right time.
With generative AI, CMOs can scale content production while maintaining relevance. Instead of manually crafting sustainability reports, blog posts, or regulatory updates, AI can generate personalized content that adapts to individual customer concerns and interests.
Of course, AI-driven content should be used strategically. It should support, not replace, human messaging, helping teams deliver relevant, timely, and personalized energy insights at scale.
4. AI in crisis communications: Managing consumer trust during volatility.
Energy markets are inherently volatile, whether due to weather events, geopolitical shifts, or unexpected demand surges. AI can help CMOs proactively manage crises by detecting sentiment shifts, automating rapid-response messaging, and keeping customers informed.
During a heatwave-induced power shortage, for example, AI-driven analytics could detect the risk of rolling blackouts before traditional monitoring systems. AI-powered sentiment tracking would identify rising frustration on social media, triggering automated, real-time crisis messaging via SMS, email, and chatbots — alerting customers, providing energy-saving tips, and prioritizing alerts for at-risk individuals. This proactive approach not only mitigates consumer frustration, but also strengthens brand loyalty.
5. Ethical AI: The next challenge for energy marketers.
As AI adoption grows, so do concerns about data privacy, algorithmic bias, and regulatory scrutiny. In a sector already under intense regulatory oversight, CMOs must take the lead in making sure AI-powered marketing remains ethical, compliant, and transparent. Security is top of mind: 77% of AI users believe companies need to do more to address AI-related data privacy issues.
AI governance isn’t a tech or compliance issue, but a brand trust issue. CMOs must advocate for transparent AI policies and ensure that personalization doesn’t come at the cost of privacy or fairness.
AI: The Future of Energy Marketing
Energy CMOs who embrace AI today will redefine customer relationships, optimize marketing efficiency, and build trust in an increasingly complex landscape. The ones who lead this shift won’t just see better marketing results — they’ll help shape the future of the energy industry itself.
About the Author
Dbrav Dunkley is a Partner at Credera, a global consulting firm that partners with businesses to deliver transformative digital, technology, and data-driven solutions, helping organizations innovate and achieve long-term success.
