Key takeaways:
- European utilities are shifting toward flexibility-driven energy systems but lack clear monetization pathways
- AI adoption is accelerating, but most deployments remain siloed and disconnected from core operations
- Utilities face growing uncertainty in financing firm power vs. intermittent renewables
- Grid resilience and digital infrastructure are emerging as top priorities amid rising volatility
- Data integration, not new tools, will determine the real value of AI in utility operations
The Lux Take: The shift to flexibility-driven utilities
European utilities are moving toward flexibility-driven systems shaped by regulatory alignment with system operators. Value creation will depend on improving data quality and integration to enable AI in real-time operations, rather than isolated applications. Capital-intensive assets such as nuclear and geothermal will remain viable where premium offtake supports financing, as grids become more dynamic and dominated by intermittent renewables.
Event overview: Utilities confront uncertainty in the energy transition
Lux attended the Future of Utilities Energy Transition Summit in Amsterdam on March 18–19, 2026. The event’s theme was tied to recent geopolitical events and the growing prevalence of AI and its impact on European utilities. The panels and attendees discussed flexibility, grid infrastructure, financing, power generation, and strategies to transition to the grid of the future, with uncertainty the prevailing sentiment among attendees. In this research brief, Lux Research highlights three key takeaways for utilities from the event.
Takeaway #1: Flexibility is critical — but monetization remains unclear
Flexibility is widely recognized as essential to the power system, but utilities still lack a clear pathway to build and monetize it at scale. Resilience dominated the conference, with utilities and energy companies focused on building power systems that can withstand growing volatility and constraints. Flexibility emerged as a key enabler, allowing systems to respond to intermittency, congestion, and shifting demand as electrification accelerates, yet utilities still struggle to define what to build and how to capture value. Stakeholders identified distributed, fast-to-deploy solutions, such as demand response, behind-the-meter (BTM) storage, and flexible loads, as the most practical near-term options given long interconnection timelines and permitting delays, but these approaches rely on digital infrastructure that many utilities lack at scale due to fragmented data, legacy systems, and limited integration between IT and operational systems. Although machine learning(ML)/AI and digital tools are widely cited as critical for forecasting, dispatch, and asset optimization, most deployments remain at pilot stage and are not embedded in core operations. At the same time, evolving market structures distribute value across multiple services with different participation rules and technical requirements, complicating coordination and creating uncertain revenue streams, making flexibility essential for managing renewables and electrification but difficult to finance as a stand-alone investment.
Takeaway #2: Utilities face a strategic crossroads in asset investment
Utilities are at a crossroads in their asset transition and portfolio management strategies, seeking clear use-cases to justify financing new-build assets. Utilities and energy companies at the conference highlighted a strong ambition to lead regional grid resilience but provided limited clarity on execution. Stakeholders broadly expect intermittent renewables, particularly microgrids and BTM systems, to meet near-term demand, given grid congestion and interconnection delays in Europe, especially as data center demand rises. This assumption complicates the case for clean, firm power sources like advanced geothermal or nuclear, which face financing barriers due to high capital costs and long lead times. High penetration of intermittent renewables may further reduce capacity factors, weakening the economic case for these assets. While declining grid inertia increases the need for sources that complement and stabilize the grid, firm power is not the only solution; grid-stabilization technologies, advanced power electronics, and energy storage can also provide these services. This dynamic raises a central question: Will future grids require firm power to deliver reliable, low-cost electricity, or will capital constraints limit deployment? Outcomes will vary by geography, but firm power will likely serve premium offtakers like data centers, while conventional grids become more dynamic and flexibility driven.
Takeaway #3: AI adoption is growing — but integration is the bottleneck
AI use-cases are becoming clearer, but integration into core utility operations remains limited. Conference discussions focused on practical applications rather than transformational narratives, including AI-assisted engineering validation, automated asset and work order management, renewable siting optimization using digital twins, and real-time orchestration of distributed resources through virtual power plants. These applications position AI as a tool to improve efficiency, reduce manual effort, and accelerate decision-making across grid and asset operations. However, utilities continue to deploy AI as isolated point solutions with limited integration into core systems and workflows. Fragmented data across IT and operational systems, weak linkage to operational KPIs, and limited trust in model outputs constrain broader adoption. European utilities also highlighted challenges related to General Data Protection Regulation compliance, data collection, and extensive preprocessing requirements, which hinder the extraction of useful data with which to train and develop models. As a result, utilities are prioritizing edge computing and in-house model development to support near-term applications in customer service (including agentic workflows), energy trading optimization, and internal operations — areas that offer the most immediate value.
Outlook: Data integration will define competitive advantage
AI is now a top priority for utilities as they seek differentiation beyond established applications like forecasting, trading, and asset monitoring. However, siloed data and limited real-time access constrain broader impact. Improving data integration will allow utilities to scale existing models more effectively and support real-time decision-making — capabilities that directly underpin flexibility. As a result, AI’s value will depend less on new use-cases and more on how well utilities operationalize existing data.
At the system level, rising demand and higher oil and gas costs will push Europe to accelerate intermittent renewables, storage, and electrification to reduce fossil fuel dependence. This shift will require grid-stabilizing technologies and market models that reduce curtailment. In this context, capital-intensive firm power solutions like nuclear and geothermal will remain viable primarily for premium offtakers (e.g., data centers), as grids become more dynamic and dominated by low-cost intermittent renewables.
Navigate the next era of utilities innovation
Utilities are entering a period of rapid transformation, where flexibility, AI integration, and smarter asset strategies will define competitive advantage. But turning these signals into actionable strategy requires more than observation.
Want to understand where utilities innovation is headed next and how to position your organization to lead?
Explore Lux Research’s latest report, “The Next Era of Utilities Innovation,” for deeper insights into emerging technologies, business models, and strategic priorities shaping the future of energy.
