Expanding the power of agentic AI in the energy industry
What if the solution to energy sector challenges lay not solely in new infrastructure or regulatory adjustments, but in the intelligence of systems capable of adapting, learning, and evolving? Agentic AI - the next frontier in artificial intelligence - holds that promise and is proving to be a transformative force across energy providers globally.
For an industry grappling with mounting financial pressures, the push for decarbonization, and increasing cybersecurity threats, agentic AI offers not just a lifeline but a launchpad towards innovation, efficiency, and long-term viability.
The energy sector's complex landscape
The energy industry is facing unprecedented disruption. Escalating customer churn rates, aging infrastructure, and decarbonization mandates are only the beginning; add workforce skill gaps, mounting regulatory demands, and threats to grid cybersecurity into the mix, and you have an intricate puzzle to solve.
For UK energy companies especially, several challenges often converge:
Cost and operational inefficiencies
in legacy systems that undermine profitability.
Grid modernization efforts
struggling under the weight of regulatory costs.
Customer expectations
moving rapidly towards sustainable and seamless energy solutions.
The question for sector leaders, then, isn't whether to innovate—but how to innovate. This is where agentic AI is stepping into focus as a catalyst for change.
Agentic AI – a strategic imperative
Unlike traditional AI models that focus on single-task automation, agentic AI can adapt dynamically to complex, multi-layered workflows. By merging machine intelligence with human judgment, agent systems open the door to advanced decision-making and process optimization on a scale previously unthinkable.
For those unfamiliar, agentic AI operates with autonomy, proactively learning from data, identifying patterns, and even making decisions within set parameters while staying in constant collaboration with human oversight.
Agentic AI is already gaining momentum across industries. The global AI market is projected to grow from $5.2B in 2024 to over $196B by 2034. Gartner estimates that by 2028 we will see 33% of enterprise applications incorporating agentic AI and AI making 15% of day-to-day decisions autonomously.
It's no mere hypothesis; agentic AI is being operationalized today, and in the energy sector, it’s delivering measurable outcomes.
Real-world applications of agentic AI in energy
Customer experience transformation
Customer preferences are rapidly shifting towards sustainable and hyper-personalized energy solutions. With agentic AI, energy providers can deploy AI agents capable of offering tailored interactions across channels such as email, chat, and voice. By analyzing historical and real-time customer behavior, these systems create deeply personalized interactions while minimizing customer effort. Our estimates show that UK energy providers who integrate AI-based systems into their customer operations could potentially see 15%-20% higher customer satisfaction rates, with expedited resolution times for billing disputes and seamless onboarding processes that reduce churn.
Operational efficiency at scale
Aging infrastructure and manual workflows have placed constraints on resource efficiency. Through agent observability dashboards and predictive analyses, agentic AI is making energy operations smarter and leaner. For instance, in billing exception management—a painstakingly manual process—AI-driven workflows could potentially boost operational efficiency by up to 45%. The result? Faster and accurate billing resolution, expedited appointment scheduling, and faster energy settlements.
Workforce enablement via AI assistance
The skill gap in the energy sector presents a pressing need for organizations to upskill and enhance workforce productivity. Agentic AI supports engineers and customer service representatives alike through dynamic procedural guidance and decision support. Imagine an AI agent aligned with grid maintenance procedures, assisting engineers by predicting faults and optimizing maintenance schedules. This not only reduces downtime but also ensures compliance with safety regulations.
Grid modernization and cybersecurity
Modernization of the energy grid is imperative, but it comes with security risks. Agentic AI's embedded governance models address these risks proactively by identifying vulnerabilities in real-time and autonomously prioritizing threat responses. These systems constantly learn from evolving threats, creating a dynamic security framework that protects critical infrastructure.
Why agentic AI is a natural fit for the energy sector
Agentic AI isn't just another software system—it represents a new paradigm in energy-sector operations. Here are the core reasons why energy leaders must consider its adoption:
Scalability
AI models can adjust to geographic expansions, seasonal demand surges, and new market requirements, ensuring that solutions grow with your business needs.
Data-driven intelligence
Leveraging vast customer histories and real-time grid data, AI systems optimize decisions with pinpoint accuracy.
Regulatory compliance
With transparent, explainable AI and built-in governance, organizations are better equipped to meet and exceed compliance requirements.
Sustainability
AI-driven operational efficiencies contribute directly to decarbonization by streamlining energy usage, reducing waste, and enabling more accurate resource distribution.
By addressing such critical challenges, agentic AI creates a compelling value proposition, empowering energy leaders to transition into a future-ready, sustainable business model.
Actioning the change
Change isn’t easy, especially in a heavily regulated and intricate industry like energy. But it's achievable, particularly when organizations approach transformation with a clear strategy.
The adoption of agentic AI must prioritize scalability and long-term stability while focusing on human-AI collaboration. By entrusting AI with repetitive, high-volume tasks, organizations can free up human resources to focus on innovation and strategy.
Three steps to success with agentic AI:
1
Identify impactful use cases – Target complex, high-volume processes where meaningful efficiencies or improvements can be realized.
2
Implement governance structures – Build a clear AI governance framework that addresses ethical, security, and compliance concerns.
3
Invest in skills and integration – Ensure your workforce is equipped to leverage AI solutions effectively through comprehensive training and implementation support.
Stepping forward with agentic intelligence
The energy sector’s challenges aren't just obstacles-they're opportunities. Opportunities to radically transform the way the industry delivers services, addresses sustainability, and serves its customers.
Agentic AI isn't a tool for tomorrow; it's a solution for today. Its capacity to drive innovation, streamline operations, and meet the dual demands of profitability and sustainability makes it a crucial element of any future-leading energy organization. Agentic AI can reshape energy operations. At EXL, we’ve considered the various challenges the energy industry faces in designing our new AI platform. Read our press release on EXLerate.AI™ to learn how we’re helping organizations scale their AI programs and take the next step towards innovation, efficiency, and sustainability.