Turning Buildings Into Competitive Assets: How Energy as a Service Is Rewiring Industrial Advantage

As energy systems become digital, connected, and intelligent, buildings are evolving from static infrastructure into dynamic, data-driven platforms. Energy efficiency, service models, and AI-powered building intelligence are turning sustainability from a compliance exercise into a lever for competitiveness.

At Sustainability in Service 2025 – Power of 50, Kim Enevoldsen with Siemens, revealed that scalable decarbonization is achievable when organisations connect their physical assets with digital capabilities and rethink how they finance, operate, and optimise their technical infrastructure.

Technology, Ecosystems, and Customer Relevance  

The transformation of building operations has shown that technology alone is not enough. Competitiveness increasingly depends on ecosystem positioning and a clear understanding of evolving customer needs.

Many organisations are already showing familiar failure patterns:

• Failure to adapt to new technology: Relying on legacy systems while the market shifts toward connected, software-driven ecosystems;
• Misaligned partnership strategies: Backing the wrong platforms and missing where innovation is actually happening;
• Slow decision-making: Governance models that cannot respond at the pace of technological change;
• Misreading customer demands: Optimising for hardware performance while customers prioritise integrated, service-based outcomes.

These dynamics are now playing out in building intelligence, sustainability, and energy management. Treating digitalisation, AI, and energy-as-a-service as optional add-ons is no longer viable. Organisations that do risk ending up with strong physical assets, but without the connectivity, intelligence, and ecosystem integration required to compete.

It’s critical to keep pace with technology, build the right partnerships, and anchor every investment in a precise understanding of customer and operational needs.

Regulation as Accelerator, Not Just Obligation  

Across Europe, the regulatory environment around energy, carbon, and building performance is intensifying. Over the last few years, a wave of new and updated frameworks has reshaped expectations for how organisations manage and report on their energy use and emissions.

These rules now pull sustainability into day-to-day operations, whether organisations are ready or not. Instead of treating regulation purely as a constraint, leading companies view it as:

• A forcing mechanism to upgrade ageing infrastructure and digital capabilities;  
• A catalyst for internal alignment between sustainability, finance, operations, and IT;  
• A baseline that, once met, can be turned into a genuine market differentiator.

Where some organisations still pursue compliance sustainability, doing the minimum to satisfy regulators, others are actively using regulation to justify investment in intelligent, connected, and flexible buildings that deliver strategic benefits far beyond compliance.

From Automated to Autonomous: Buildings That Speak in Data  

Most industrial and commercial facilities today can be described as traditional or, at best, automated buildings. Systems are often siloed, operated in parallel rather than as a unified whole. Data exists, but in fragmented, difficult-to-use formats.

Buildings and technical infrastructure already generate vast amounts of data. To unlock value, organisations must be able to interpret this data and translate it into decisions, actions, and measurable outcomes.

The evolution follows three steps:

1. Traditional / automated buildings: Systems are locally controlled, with limited integration. Efficiency improvements are largely manual and project-based, relying heavily on local expertise and one-off engineering.
2. Smart buildings: Systems are connected to a common digital layer or platform. Data from across the building, from sensors, equipment, and controls, is consolidated, analysed, and made visible. Performance optimisation becomes continuous rather than episodic.
3. Human-centric autonomous buildings: Buildings start to anticipate and act. AI algorithms process live and historical data to automatically adjust operations, recommend interventions, or execute corrective actions with minimal human involvement. The building becomes an active partner in operations, not just a passive asset.

This progression is enabled by several mutually reinforcing capabilities, such as cloud-based data management, AI and advanced analytics, open platforms and APIs, and cybersecurity architectures bridging IT and OT.

AI-Powered Decarbonization: Where Digital Meets Physical  

AI can be a practical engine for decarbonization and cost reduction. Industrial AI, applied to buildings and infrastructure, is increasingly being used to:

• Analyse massive volumes of time-series data from sensors, meters, and building systems;  
• Identify inefficiencies and anomalies that would be invisible to human operators;  
• Optimise setpoints, schedules, and equipment behaviour in near real-time;  
• Predict and prioritise maintenance interventions;  
• Support scenario planning for energy, carbon, and resilience.

However, significant impact is achieved when the digital layer is combined with targeted interventions in the physical world.

The ideal solution is to bring the two together:

• Digital: A cloud-based platform aggregates data from across the building environment, including HVAC, lighting, e-mobility, fire systems, security cameras, power quality sensors, and more. Data is structured into a single environment, protected by robust cybersecurity, and processed by AI to generate actionable insights.

• Physical: Energy engineers conduct value discovery audits to determine what is technically and economically possible, from retrofitting air handling units and upgrading fans to introducing high-efficiency boilers, heat pumps, or LED lighting.

Connecting these layers enables prioritised, data-backed modernisation programmes where every physical intervention is informed and monitored by digital intelligence.

Energy as a Service: Turning Savings into Investment  

Perhaps the most transformative aspect for industrial decision-makers is not only how buildings can be optimised, but how those optimisations can be financed.

Energy as a Service (EaaS) models are redefining how organisations pay for decarbonization and modernisation. Instead of treating energy efficiency as a pure CAPEX burden, savings generated by projects become the primary funding mechanism.

The typical structure involves:

1. Establishing a baseline: Detailed measurement and analysis of current energy use and building performance to define the starting point.
2. Designing and implementing measures: A combination of technical upgrades (e.g. HVAC modernisation, LED lighting, control system enhancements) and digital services (e.g. analytics, optimisation, predictive maintenance) is deployed.
3. Capturing and guaranteeing savings: The energy savings generated are quantified and used as the source of payment for the solution. In some models, the provider guarantees a specific level of savings, significantly reducing risk for the building owner or operator.
4. Shifting from CAPEX to OPEX: Instead of upfront capital expenditure, the investment is repaid via the operating budget, often from the energy budget itself. Under certain conditions and in specific markets, these arrangements can also be structured off-balance sheet.

This shifts the narrative from “cannot afford to invest” to “cannot afford not to”. When energy savings fund infrastructure modernisation, the barriers to action are dramatically reduced.

Security, Resilience, and the New Definition of Competitiveness  

Over the last few years, geopolitical tensions and market volatility have reshaped how organisations prioritise energy and building investments. Sustainability, while still important, is no longer the only or dominant driver.

The current hierarchy of needs increasingly includes:

• Security of supply: Ensuring that operations are not disrupted by energy shortages or grid constraints;
• Energy resilience: The ability to adapt dynamically to price spikes, load constraints, or system disturbances;  
• Cyber resilience: Protecting interconnected building and energy systems from cyber threats as IT and OT converge; 
• Physical security: Integrating building intelligence with access control, surveillance, and safety systems.

Alongside energy efficiency and decarbonization, these priorities are now part of an integrated competitiveness agenda. Intelligent infrastructure is judged not only on how green it is, but on how robust, secure, and adaptive it can be in a complex operating environment.

Building Platforms and Ecosystems

A critical shift is the growing importance of platforms. Building and energy platforms are becoming the foundation for how data is managed, analysed, and turned into operational value.

The emerging model is characterised by:

• Cloud-based architecture: Data is centralised to enable remote access, cross-site visibility, and scalable analytics. This supports new operating models, where expertise can be applied across multiple locations without being physically present.

• AI-enabled analytics: Data is processed and interpreted at scale, enabling faster identification of anomalies, optimisation opportunities, and forward-looking actions that would be difficult to detect manually.

• Connectivity hub: The platform integrates multiple systems and data sources into a single environment, replacing fragmented data flows with structured, usable information.

• Open, app-based ecosystem: Modern platforms are designed to be open and extensible. Third parties can build applications on top, allowing capabilities to expand over time and reducing dependency on a single vendor.

Within these environments, applications typically span operations (e.g. predictive maintenance), sustainability (e.g. emissions tracking), and energy management (e.g. consumption optimisation). Additional services can combine real-time data, historical patterns, and external inputs such as weather to continuously improve performance, for example, by optimising heating systems with minimal manual intervention.

Platform choice is a strategic decision. Closed or inflexible environments limit integration and future innovation, while open, scalable ecosystems enable continuous improvement and long-term competitiveness.

Bridging IT and OT: Cybersecurity as Enabler, Not Obstacle  

As buildings are brought online and connected to cloud-based platforms, cybersecurity concerns inevitably intensify. Industrial and critical infrastructure operators, particularly in sectors such as healthcare, are understandably cautious about exposing operational technology (OT) to the wider network or the internet.

Several principles are emerging as best practice in managing this challenge:

• Segmentation and selective connectivity: Not all data and not all systems need the same level of exposure. Sensitive or critical systems can remain locally hosted, with tightly controlled remote access. Less sensitive data streams can be securely routed to the cloud for analysis.

• Trusted, secure gateways: Mature, healthcare-grade connection technologies for transferring sensitive data can be repurposed for building and energy applications, ensuring end-to-end encryption and compliance with sectoral regulations.

• Clear governance between IT and OT: Cross-functional alignment is essential. Energy, facility management, IT, cybersecurity, and operations must jointly define architectures, responsibilities, and escalation paths.

Cybersecurity, when addressed proactively, is not a blocker to digitalisation but rather a foundational enabler. Without it, the benefits of intelligent, connected, and remotely managed facilities cannot be fully realised.

Human Capital Constraints: Why Autonomy Matters  

A key driver of autonomous and AI-enabled buildings is the growing shortage of skilled operational staff. As building systems become more complex, many organisations simply do not have enough qualified people to manage them effectively.

In this context, automation is necessary to maintain stable, safe, and efficient operations.

Autonomous and semi-autonomous capabilities can:

• Reduce manual workload: Routine monitoring, adjustments, and issue detection are handled automatically, freeing up limited staff capacity.

• Standardise operations: Best practices can be embedded into systems and applied consistently across sites, reducing variability and dependency on individual expertise.

• Enable remote management: Experts can oversee multiple facilities from a central location, rather than being tied to a single site.

• Ensure continuity: Optimisation and performance improvements continue even when staffing is constrained or turnover is high.

Building intelligence is therefore not just about efficiency or sustainability, but a direct response to structural labour shortages and the need to operate complex assets with fewer resources.

From Buzzwords to Execution  

Customer centricity, service models, and AI-driven energy efficiency are often discussed as buzzwords. However, in industrial and building contexts, these concepts are now highly practical.

Customer centricity manifests in how solutions are structured around constraints like limited CAPEX, regulatory pressure, skills gaps, security requirements, and the need for measurable and guaranteed outcomes.

Service manifests in models where risk is shared, savings are guaranteed, and energy budgets finance transformation.

AI manifests in very specific applications that move beyond dashboards to prescriptive and, increasingly, autonomous building behaviour.

For senior industrial leaders, buildings and technical infrastructure are becoming strategic levers in the race for cost efficiency, resilience, compliance, and differentiated customer value.

Time to Bring Buildings Online  

The distinction between physical and digital infrastructure is fading. Buildings are turning into data-rich, AI-enabled systems that can learn, adapt, and contribute directly to competitive advantage. To bring buildings online, organisations must understand that:

• Regulatory pressure and geopolitical volatility are not temporary storms, but structural drivers accelerating the need for intelligent, efficient, and resilient buildings.  
• The path to competitiveness lies in combining real-world infrastructure upgrades with digital platforms and AI, rather than pursuing each in isolation.  
• Energy as a Service models can convert energy savings into investment capacity, lowering the barrier to modernisation and shifting risk away from asset owners.  
• Platforms and ecosystems will determine long-term winners, as openness, interoperability, cybersecurity, and app-based innovation are now strategic selection criteria.  
• Autonomous and human-centric buildings are rapidly moving from vision to reality, driven as much by labour constraints and resilience needs as by sustainability goals.

The technology, business models, and reference cases now exist to move at scale. The decisive step is to bring buildings and technical infrastructure properly online, and to treat them not as sunk costs, but as active, evolving contributors to industrial transformation and market advantage.