Energy technology: The foundation for digital and business growth

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Organizations need resilience, sustainability, and scalability to unlock the productivity gains of AI and digital transformation.

Digital transformation initiatives have focused primarily on software, data, connectivity, and cloud technologies, while the physical infrastructure supporting the digital environment has received less strategic attention.

AI, increased electrification, and rising energy demand are changing this equation. IT and business leaders must now consider data centers, smart buildings, and other physical assets in their digital transformation strategies. The reasons are clear:

165%

increase in data center power by 2030.

AI is expected to drive a

up to 12%

of total U.S. electricity by 2028, up from about 4.4% in 2023.

Data centers are expected to consume

30%

of energy in commercial buildings is wasted.

On average,

nearly 40%

of global energy demand.

Industry accounts for

In a real-time, data-saturated world, organizations need more than connectivity and dashboards. They need energy and industrial intelligence that makes complex systems observable, contextual, and safe to automate at scale. The next phase of transformation is not simply collecting more data, but enabling systems to sense, decide, and act across physical operations.

As intelligence moves beyond digital systems and into the physical world, organizations must ensure the electricity, energy, and operational infrastructure that supports AI and digital innovation is flexible, resilient, and scalable. It must also be capable of operating and optimizing itself in real time.

The reality today is that many enterprises still work in silos. The IT shop handles compute; the operations team is responsible for operational technology and production assets; facilities teams manage building and structural data; and energy and sustainability teams track information related to power, electrification, efficiency, and decarbonization.

This siloed approach is no one's fault. Rather, it is typically the result of how operations have evolved and modernized over time. Yet it is a significant roadblock for enterprises as they seek to reap the potential benefits promised by AI and digital transformation.

The solution is energy technology, which helps organizations ensure IT performance reliability, operational resilience, and sustainability.

Source: Foundry 2026 AI Priorities Survey

98%

of IT decision-makers say their organizations are piloting, implementing, or upgrading AI technologies

63%

expect their organization's AI spending to increase in 2026

What is energy technology?

Schneider Electric defines energy technology as the convergence of electrification, automation, and digital intelligence.

Electrification creates the foundation for a more efficient, resilient, and sustainable energy system. Automation allows systems to monitor conditions, make decisions, and respond in real time, preempting costly downtime and disruption. And digital intelligence brings together IT and physical systems information, turning data into decisions and actions that help organizations reduce energy waste, cut costs, improve operational performance, and proactively prevent downtime.

The right energy technology solutions converge these capabilities, enabling the management of one coordinated system rather than separate domains.

Why energy technology matters for enterprise leaders

Energy is no longer just a facilities issue, and infrastructure is no longer only an operational concern. Both now need to be managed as strategic priorities for business and technology leaders. Energy can no longer be treated as a stable, predictable utility operating quietly in the background. Like digital systems, energy systems increasingly require active measurement, coordination, and optimization. Left unaddressed, these deficiencies create business and operational risk.

Energy technology presents an opportunity to ensure uptime, resilience, scalability, and operational efficiency, while making progress toward sustainability goals. The convergence of energy infrastructure, operational systems, and digital intelligence delivers business value across data centers, buildings, industries, and IT infrastructure.

Energy and industrial intelligence: the capability to transform operational, energy, and enterprise data into decisions that improve resilience, efficiency, and growth.

From data centers to AI factories: Building the infrastructure behind the AI economy

The race to deploy AI is creating unprecedented demand for infrastructure that can be delivered faster, operate more efficiently, and adapt to rapidly changing compute requirements. Modular architectures, liquid cooling, and intelligent energy management are becoming foundational capabilities for AI factory operators.

AI and accelerated computing require not just processors and models, but also high-density power, cooling, electrical distribution, as well as energy and industrial intelligence. When organizations don’t treat cooling or electrical capacity as a strategic priority, they can incur higher costs, deployment delays, and lost business opportunities.

AI factories depend on the convergence of energy systems, automation, and digital intelligence. Connected power, cooling, and IT infrastructure continuously generate operational data that can be analyzed in real time to optimize efficiency, capacity, resilience, and sustainability. This unified architecture helps operators manage increasingly complex AI workloads while maintaining performance and availability.

Every AI model depends on physical infrastructure. Power, cooling, automation, and software must work together as a single intelligent system to support AI at scale. The organizations leading the AI economy are not just investing in graphics processing units (GPUs). They are investing in the energy infrastructure, energy and industrial intelligence, and digital resilience required to transform power into AI outcomes. AI readiness begins with energy readiness.

ENERGY TECHNOLOGY IN ACTION

A European high-performance computing (HPC) colocation provider integrated connected power management, infrastructure-management software, and round-the-clock expert services, achieving a highly efficient power usage effectiveness (PUE) score of 1.15 while maintaining full redundancy. The deployment demonstrates how intelligent energy management can help organizations scale high-performance AI workloads efficiently and reliably.

60%

faster deployment with prefabricated data center solutions

30-60%

energy savings with direct-to-chip liquid cooling

39%

savings in data center operations staffing costs through intelligent infrastructure management

Source: Schneider Electric

97%

46%

32%

are investing in HPC and cloud infrastructure to build AI capabilities

identify IT infrastructure and systems integration — including governance, maintenance, and security — as an implementation challenge

of IT decision-makers report challenges implementing new AI initiatives

Source: Foundry 2026 AI Priorities Survey

Smart buildings: Turning facilities into intelligent assets

Within most buildings, systems that monitor power, HVAC, occupancy, security, and other facility conditions have traditionally been managed separately. Energy technology allows these systems to share information and automatically adjust operations based on actual conditions.

Sensors and intelligent controllers collect data about occupancy, temperature, equipment performance, and energy consumption. Edge controls and automation use that information to adjust HVAC and room conditions as occupancy and other conditions change. Software combines building, power, and operational data to identify waste, detect emerging equipment issues, and help facilities teams move from reactive to proactive management.

43%

of IT decision-makers say their organizations are using or exploring AI for process automation

31%

of IT decisions makers are using or exploring AI for predictive maintenance

Source: Foundry 2026 AI Priorities Survey

ENERGY TECHNOLOGY IN ACTION

At the South Australian Health and Medical Research Institute (SAHMRI), Schneider Electric's connected building management technologies helped optimize building performance through integrated monitoring, analytics, and automation. The organization achieved up to 30% energy savings and 40% water savings, while improving operational efficiency.

Energy technology enables organizations to achieve:

up to 40%

reductions in building energy consumption with digital retrofits and electrification

A full ROI in

< 2 yrs

for buildings under 100,000 square feet

up to 45%

reduction in carbon emissions through digital building and power management

Source: Schneider Electric

The next generation of buildings will not simply consume electricity. They will help balance, store, shift, and optimize energy demand, providing flexibility to increasingly dynamic power systems.

Industries: Coordinating energy with production

Industrial operators, regardless of their business sector, must balance energy constraints with production, quality, maintenance, and throughput requirements. Simply cutting power consumption may reduce output or interrupt essential processes.

Energy technology combines information about energy availability and price with production data, allowing operators to determine when to run, slow, or shift processes rather than treating energy and output as separate concerns. Sensors and edge systems collect machine readings, inspection images, and equipment-health data from the production environment.

Software-defined automation gives industrial operations a more open and flexible alternative to traditional systems, making it easier to connect equipment, introduce new technologies, and adapt production as requirements change.

Open, software-defined automation removes technology silos, enables interoperability, and gives operations the flexibility to integrate AI and new equipment while adapting to changing business requirements without extensive reengineering.

ENERGY TECHNOLOGY IN ACTION

A company that develops chemical recycling technology adopted an open, software-defined automation architecture to provide connectivity across equipment. They reduced developmental errors by 40% and cut design costs by around 30%.

Source: Schneider Electric, based on customer and internal projects

reduction in CAPEX and 15% reduction in OPEX

up to 20%

up to 15%

savings in process energy consumption

improvement in operational efficiency and reduced downtime

up to 15%

Energy technology that combines power and process for industries can lead to:

Infrastructure and grids: Building more adaptive, resilient energy systems

Infrastructure operators across utilities, mobility networks, transportation systems, and the grid must manage increasingly distributed and electrified systems. Sensors, smart meters, and connected low- and medium-voltage equipment provide real-time information about electrical distribution, alarms, circuit capacity, and equipment condition.

A unified digital layer can connect energy and industrial intelligence with physical assets to provide a consolidated view of grid systems and conditions. Advanced analytics can forecast capacity requirements, identify emerging equipment problems, and help operators move from reactive repairs toward predictive maintenance.

Together, these capabilities can help operators improve uptime, reduce maintenance and field visits, limit electrical losses, and plan infrastructure investments more wisely.

Energy technology for critical infrastructure can lead to:

15-25%

lower electrical-infrastructure CAPEX

up to 40%

reduction in maintenance activities and planned downtime for electrical-distribution equipment

Source: Schneider Electric

As electrification initiatives accelerate and energy demand becomes more dynamic, resilience depends on visibility, flexibility, and intelligence. Organizations need systems that can anticipate disruptions, optimize energy use in real time, and adapt automatically as conditions change.

ENERGY TECHNOLOGY IN ACTION

An electricity distribution company set out to upgrade its medium-voltage distribution system to support renewable energy goals while also enhancing grid reliability. By modernizing its grid with energy technology, the organization achieved an anticipated loss reduction of 10% to 15% and laid the foundation for its 45% clean energy generation target.

A platform approach to energy technology

Autonomous buildings, AI-assisted industrial processes, intelligent infrastructure, connected equipment, robotics, and electric mobility are becoming a reality across sectors. Organizations need a platform that converges electrification, automation, and digitalization in the physical world to bring together these tools and systems. This vision reflects Schneider Electric's belief that digital innovation, energy management, and industrial automation must advance together to create a more efficient, resilient, and sustainable future.

Schneider Electric has always been at the forefront of energy and technology, bridging the digital and physical worlds with energy technology through its EcoStruxure platform. EcoStruxure is Schneider Electric’s open, AI-powered, software-defined architecture for connecting energy, operational, and enterprise data with intelligent devices and control systems. Its foundational data model gathers and organizes operational data, adding context through digital twins and powering autonomous systems that produce predictive insights.

By bringing together these layers, organizations can gain the visibility and control needed to reduce costs, improve reliability, and adapt their energy and industrial infrastructure more quickly as conditions change.

These capabilities are critical for IT and business leaders as they make decisions in the AI era and amid their ongoing digital transformation efforts. In the era of intelligence, competitive advantage won’t come from digital systems alone. Rather, it will increasingly depend on how effectively organizations connect intelligence, energy, and operations across the physical world.

EcoStruxure enables:

Intelligent devices to sense physical conditions

Automation of edge control and computing systems for real-time response and action as conditions change

Contextualization of software and services information to support enterprise-level decisions and continually optimize operations

Source: Goldman Sachs

Source: U.S. Department of Energy

Source: IEA, Energy Efficiency 2025

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