Monetising Artificial Intelligence in the utility sector
This growth places AI investments in utilities on a trajectory comparable to distributed energy resource rollouts, or digital grid modernization initiatives. For example, the European grid modernisation market size was valued at USD 11.24 million in 2024, and is anticipated to reach USD 39.39 billion by 2032, at a CAGR of 16.99%.
Yet for many utility companies, AI remains behind the scenes, being used as a tool to reduce maintenance or operational costs, rather than to transform business strategy. However, this is starting to change. An increasing number of utilities have begun to explore how AI can open new revenue streams, offer dynamic, customer-centric products, and support faster integration of renewables.
In a market where differentiation increasingly depends on digital capability, AI is becoming a foundation for commercial innovation and agility. As the energy transition accelerates, AI’s true value will be measured in monetised insights, customer empowerment, and sustained competitive advantage, not just in kilowatt-hour savings.
The market opportunity in Europe
Across the energy sector, AI is becoming a core infrastructure, in the same vein as smart grid rollouts and widespread distributed energy resource (DER) adoption. This mirrors the patterns we’ve seen at triPica, where markets are being driven by digitisation, risk, and opportunity.
According to Grand View Research, the European market for AI in energy reached around USD 2.6 million in 2024, and is expected to grow to USD 12 million by 2030 at a 29.3% CAGR. As such, Europe’s AI in energy market is growing steadily, although at a more measured pace than global averages of 36.9% CAGR.
This relative difference reflects Europe’s more established grid infrastructure and regulatory environment. Utilities are investing in targeted AI applications like flexibility optimisation and customer experience, rather than in foundational ‘‘greenfield’’ digitisation projects that require implementation from scratch – like those that are still driving growth in regions like Asia-Pacific.
But while Europe’s market growth may be more measured, the strategic opportunity is arguably stronger. European utilities face unique pressures to decarbonise, innovate customer offers, and navigate complex regulatory frameworks - all areas where AI can deliver disproportionate value.
From efficiency to revenue
Many European utility companies have already begun transforming AI from a cost-saving tool into a profit-driving business model. We’ve noticed this shift happening most notably in two areas - predictive maintenance and dynamic pricing.
Predictive maintenance for asset resilience
AI-driven predictive maintenance is no longer a niche initiative. Across Europe, utilities are deploying machine learning algorithms and sensor networks to detect equipment deterioration long before failures occur - often weeks in advance.
Indeed, according to Deloitte’s recent Predictive Maintenance report, the benefits of predictive maintenance include a 5%–20% reduction in carrying costs, a 5-15% reduction in facility downtime, and a 5-20% increase in labour productivity.
As such, predictive maintenance is a gateway to new service models. Utility companies can offer asset reliability guarantees, condition-based maintenance contracts, or even cross-border performance consultancy - revenue streams that were previously unreachable.
Dynamic pricing and improved forecast accuracy
The global energy market’s volatility presents a challenge and an opportunity for utilities. By using AI to forecast demand, renewables output, and price movements, utilities can implement dynamic pricing models that benefit from shifts in supply and demand.
For example, in Europe, data-driven demand response programs are already aligning with charging schedules for electric vehicles with periods of cheap renewable generation providing utility companies and customers with more flexibility value.
One study (albeit from 2018) found that a 1% saving in the MAPE (Mean Absolute Percentage Error) accuracy of a Short-term Price Forecast (STPF) is approximately equal to USD 300,000 in savings per year per GW peak-load.
Multiply that across Europe’s aggregated utility fleets, and the potential of dynamic pricing becomes strategically significant.
Optimising energy flow for profit
AI-powered demand forecasting creates material value in flexibility.
For example, a 2025 report from the European Space Agency found that using AI-enabled forecasting and localised congestion management allows Distribution System Operators (DSOs) to optimise flexibility deployment where it’s most needed.
By forecasting where, when, and at what price demand-side flexibility is available, utilities can charge for flexibility services, and even offer subscription-style products that let customers opt-in to grid-friendly energy deals.
Building the AI monetisation layer
As more European energy companies embrace AI for monetisation, the key enabler will be the platform that transforms analytics into customer value and revenue. A robust monetisation layer that combines data, AI, billing, and engagement workflows is essential. Without it, insights remain isolated, and opportunities remain hidden.
A 2024 report from IBM shows that 74% of utility companies are currently embarking on AI initiatives, ranging from initial pilots to strategic implementation across the organisation. But what separates market leaders is in how those predictions flow directly into dynamic customer engagement, billing, and pricing.
And this requires several tightly integrated layers:
- Realtime data fusion: Smart meters, IoT sensors, grid telemetry, carbon intensity indices, and customer profiles all feed into a central AI engine.
- Billing and dynamic tariffs: Systems need to apply variable pricing, such as realtime consumption pricing, or flexibility rewards - and bill accordingly, with minimal latency.
- CRM-led engagement: AI-informed campaigns, notifications, nudges, and opt-in offers need to reach customers at the right time to drive proactive behaviour and retention.
Trust, transparency, and governance
Advanced AI systems (particularly generative models) can sometimes suffer from a lack of transparency. For example, in regulated markets like Europe, utilities have an obligation to maintain:
- Explainability: Where customers need to understand why their tariff changed, or why they were nudged to reduce their usage.
- Governance: Ethical controls, audit trails, and human oversight ensure reliability and safety, especially as AI ties into billing.
Indeed, the U.S. Department of Energy’s AI for Energy report recommends:
‘’To ensure safety, security, and reliability, AI models for grid applications should be rigorously validated, interpretable, ethically implemented with humans-in-the-loop’’
Lowering the barrier
While the potential of AI is well understood, deploying AI platforms at scale still presents practical hurdles. Many European utilities face legacy system constraints, fragmented data landscapes, and regulatory uncertainty around how AI-driven offers and billing will be governed.
Bridging these gaps requires more than standalone AI pilots. It calls for platforms like triPica that can integrate predictive insights with billing, CRM, and customer-facing workflows in real time.
The ability to integrate AI into operations is where true commercial value is created. As a result, utilities can move faster, without waiting on multi-year IT overhauls, and begin monetising AI insights through tangible customer offers and service models.
AI monetisation in action
Energy companies are starting to use AI to deliver market-ready products. Two triPica-enabled projects stand out as early examples of monetisation in motion.
Europe’s first commercial V2G service
In September 2024, triPica partnered with The Mobility House to launch Europe’s first commercial Vehicle-to-Grid service in France, integrated with Renault 5 customers.
The platform empowers EV owners to sell energy back to the grid during peak times, boosting grid flexibility and reducing costs for consumers. triPica’s real-time billing ensures every kilowatt-hour outflow is monetised, enabling dynamic pricing and transparent, customer-facing insights.
Raphael Hollinger, Energy Lead at The Mobility House, said:
“V2G is a game-changing innovation for both energy suppliers and customers. With our technology and triPica’s adaptable billing platform, EV owners can contribute to the energy transition and save on energy costs”.
This example demonstrates how AI can be used as the foundation of an entirely new offering, turning idle EV batteries into interactive market assets.
Rapid B2C market entry with loyalty offers
In July 2023, Primeo Energie, an energy retailer with Swiss heritage, used triPica’s modular SaaS platform to launch its French B2C business in record time, riding the tailwind of rising energy prices.
Thanks to triPica’s flexibility, Primeo implemented loyalty reward structures and tailored tariffs without lengthy IT roll-outs. Antoine d’Ornellas, Retail Market Director at Primeo Energie France, said:
“triPica adapts to your specific requirements instead of imposing a standard operating model.”
As well as reducing costs, this market entry created a competitive edge through customer-centric rewards and rapid product agility.
New revenue models enabled by AI
AI is no longer confined to back-end operations. In Europe’s energy sector, it’s beginning to underpin entirely new business models, transforming how utilities package and deliver value. From subscription-based energy services to AI-enabled optimisation contracts, these models are turning digital capability into recurring, customer-facing revenue.
AI-as-a-Service, and Energy-as-a-Service (EaaS)
The global Energy as a Service (EaaS) market was valued at USD 85.62 million in 2024, and is projected to grow to USD 208.20 million by 2032, at a CAGR of 11.75%. This growth indicates a clear shift in how energy services are being packaged and delivered.
For utility companies, it highlights an opportunity to expand beyond commodity sales, and to offer value-added services that customers are increasingly willing to pay for.
For example, grid optimisation contracts that leverage AI can deliver guaranteed cost savings or carbon reductions.
Subscription and performance-based models
AI allows utility companies to reinterpret what “energy service” means.
Instead of charging for kilowatt-hours consumed, utilities can offer outcome-based, subscription-style packages like guaranteed greenhouse gas reduction, EV charging bundles synced to green energy periods, and Energy Efficiency-as-a-service.
These models offer recurring revenue streams that perform independently of wholesale energy prices.
Generative AI for innovative products
Generative AI is also enabling the development of new energy products.
European utilities that build generative-AI-based offerings like real-time grid planning tools, or interactive outage simulators can license these tools to other utilities or network operators.
Consequently, they can start to generate Software-as-a-Service (SaaS) income.
How generative AI is driving innovation across European utilities
In the energy sector, AI innovation is expanding well beyond grid management and customer billing, it’s extending into research and development (R&D), materials design, and faster product development cycles.
Generative AI in grid operations and research
At a 2024 European Commission workshop, grid operators highlighted how generative AI can improve renewables integration, grid resilience, shorten grid connection times, and reduce household bills.
Similarly, a 2024 report published by The National Renewable Energy Laboratory (NREL) showcased how generative AI is being applied to automate network decisionmaking.
The report also highlights how AI is being used in processing timeseries data, naturallanguage operator queries, and system simulations to support better realtime operations.
AI-Driven materials discovery and battery design
Generative AI is transforming materials science, with European research groups using it to design novel battery electrolytes in weeks instead of years.
A recent study by Cornell University demonstrated how Gen AI accelerated candidate generation and screening for nextgeneration solidelectrolyte materials. These breakthroughs - which are helping develop more stable, efficient energy storage - have direct implications for utilities managing distributed energy resources and driving cleanenergy innovation.
As such, AI-led research and development accelerates speed to market, helping utilities reduce the time to prototype new products from years to months. It also encourages product innovation, where high-value tools such as digital twins, or outage simulators can be made commercial and offered to other grid operators or energy companies.
And for first-movers, generative AI-enabled tools provide a clear competitive edge, opening up opportunities for licensing and SaaS-based revenue models that can differentiate offerings in an increasingly dynamic market.
AI as a growth lever for utility companies
Artificial Intelligence is fast-becoming a strategic force across European utilities. In 2024, investments in European tech were on track to reach around USD 45 billion - three times as much as the USD 15 billion recorded in 2015.
Indeed, Europe is emerging as a global powerhouse in generative and industrial AI. As such, utilities that embed AI deeply, from grid operations to customer billing, will be able to tap into new markets, outpace competitors, and deliver services that genuinely stand apart.
The potential is already visible across the value chain. Predictive maintenance is reshaping how assets are managed and monetised. Dynamic pricing and flexibility programs are turning grid responsiveness into new sources of margin. And AI-driven platforms are enabling subscription-based models. Meanwhile, generative AI is opening entirely new frontiers - from product innovation to grid optimisation and materials discovery.
Utilities that treat AI as a driver of growth, not just efficiency, will be best placed to thrive in this new environment. The AI tools are proven, customers are receptive to personalised energy experiences, and regulatory frameworks are evolving to support flexibility and innovation.
What matters now is execution. Energy companies that develop the right digital architecture, adopt AI internally, and design commercial models that turn insight into customer value will be best positioned to lead the market
This is where triPica’s AIready SaaS platform can help utilities move faster. If your company is ready to turn AI intelligence into commercial value, we’d be happy to explore the opportunities in more detail.
Get in touch with us today to learn more.
