Why Sustainable Data Centers Are Becoming a Business Requirement

Data centers have become some of the most important pieces of infrastructure behind the digital economy. Cloud applications, streaming services, enterprise software, artificial intelligence, digital platforms and connected systems all depend on computing infrastructure operating continuously in the background.

That infrastructure also requires significant amounts of energy.

The International Energy Agency estimates that data centers consumed around 415 TWh of electricity globally in 2024, representing about 1.5% of global electricity consumption. Its base case projects data center electricity consumption to more than double to around 945 TWh by 2030, with AI-driven accelerated servers accounting for a substantial share of the increase.

This is changing the way businesses need to think about digital infrastructure.

Energy efficiency is no longer only an environmental consideration. It increasingly affects infrastructure costs, scalability, resilience, procurement decisions and long-term technology strategy.

For organizations building or expanding digital infrastructure, sustainable data centers are becoming a business requirement.

What Makes a Data Center Sustainable?

A sustainable data center is not simply a facility powered by renewable energy. Sustainability involves the efficiency of the entire infrastructure system, including computing equipment, cooling, electricity sourcing, water consumption and hardware lifecycle management.

Several factors determine the overall sustainability of a data center.

Energy Efficiency

The most obvious factor is how efficiently a data center converts electricity into useful computing.

Servers, storage systems, networking equipment and other IT infrastructure consume electricity continuously. Additional energy is required for cooling, power distribution, backup systems and other facility operations.

Improving server utilization, reducing unnecessary workloads, optimizing infrastructure and selecting more efficient hardware can reduce the energy required to deliver the same computing capacity.

This makes energy efficiency relevant to both sustainability and operating costs.

Efficient Cooling

Cooling is another important part of data center energy consumption.

Traditional air cooling systems can become increasingly demanding as computing density increases. AI workloads are particularly important because high-performance accelerators can generate significantly more heat than conventional computing equipment.

This is driving interest in technologies such as liquid cooling, more efficient airflow management and intelligent thermal monitoring.

The objective is not simply to keep equipment cool. It is to maintain the required operating conditions while using as little energy and water as practical.

Renewable and Lower-Carbon Electricity

The source of electricity matters as much as how efficiently it is consumed.

A highly efficient data center operating entirely on a carbon-intensive electricity grid can still have a substantial operational emissions footprint. Conversely, renewable electricity can reduce the emissions associated with the same computing workload.

Businesses are therefore increasingly looking at renewable energy procurement, power purchase agreements, on-site generation and the carbon intensity of local electricity grids when evaluating digital infrastructure.

This is part of a broader shift in how businesses approach energy. Renewable energy is increasingly being considered alongside energy security, operating costs and long-term resilience, as discussed in an analysis of solar energy and operational decarbonization in India.

Water and Resource Efficiency

Energy is not the only resource involved.

Some data center cooling systems require significant amounts of water, making water availability an increasingly relevant consideration in infrastructure planning. Hardware also has an environmental footprint extending beyond its operational electricity consumption.

Equipment manufacturing, replacement cycles, refurbishment, reuse and end-of-life management all contribute to the broader resource impact of digital infrastructure.

A sustainable data center therefore needs to be considered as a complete infrastructure system rather than simply an electricity consumer.

Why Data Center Sustainability Is Becoming a Business Issue

The sustainability of digital infrastructure increasingly affects business decisions.

Energy Costs Affect Infrastructure Economics

Electricity is a major operating cost for data centers.

As computing requirements increase, inefficient infrastructure can create unnecessary operating expenses. Improving utilization, cooling efficiency and power management can therefore have a direct financial benefit.

For businesses running large digital workloads, sustainability and efficiency can increasingly become part of the same infrastructure conversation.

Data Center Expansion Depends on Energy Availability

Data center growth is also becoming an energy infrastructure issue.

The IEA expects global data center electricity consumption to reach around 945 TWh by 2030 in its base case. It also expects electricity consumption from accelerated servers, largely associated with AI, to grow particularly quickly.

This creates a challenge for organizations planning new infrastructure. Access to sufficient electricity, grid capacity and reliable power can become as important as access to land, connectivity and computing equipment.

A data center cannot scale simply because additional servers are available. The surrounding energy infrastructure also needs to support that growth.

Customers Are Asking More Questions

Sustainability requirements are also moving through business relationships.

Large enterprises increasingly ask suppliers and technology providers for information about emissions, energy use and sustainability practices. Procurement teams may request environmental information as part of supplier assessments, particularly when technology infrastructure forms a meaningful part of the service being purchased.

For technology companies, this means sustainability data can increasingly become part of the information they need to provide customers.

NatNavi’s Impact Companies database reflects this broader shift toward more structured sustainability information about businesses, technologies and solution providers.

Sustainability Data Is Becoming More Important

Organizations cannot manage what they cannot measure.

Businesses increasingly need visibility into the environmental impact of the infrastructure supporting their operations. For cloud and data-intensive businesses, that can include electricity consumption, renewable energy use, emissions and other infrastructure metrics.

This creates a need for better data from both internal infrastructure teams and external technology providers.

AI Is Changing the Data Center Sustainability Equation

Artificial intelligence is making this issue more important.

AI workloads can require substantially more computing capacity than many conventional software workloads. Training large models, operating inference systems and supporting high-performance AI applications can require large numbers of specialized accelerators.

The IEA estimates that electricity consumption from accelerated servers is projected to grow by around 30% annually through 2030 in its base case.

That does not mean every AI application has the same energy footprint. Workload design, model size, hardware utilization, inference frequency and infrastructure efficiency all influence energy consumption.

The important point is that AI is increasing the need to consider energy efficiency at the architecture level.

AI Efficiency Is Not Only About the Model

When organizations discuss efficient AI, the conversation often focuses on the model itself.

Infrastructure matters too.

Efficient AI systems can involve:

• Better hardware utilization
• Appropriate model selection
• Efficient inference
• Workload scheduling
• Optimized data movement
• Efficient storage
• Intelligent resource allocation
• Monitoring of computing demand

A smaller and more efficient model running on well-utilized infrastructure can have a very different resource profile from a large model running continuously on underutilized hardware.

Sustainability therefore needs to become part of AI infrastructure planning rather than something considered after deployment.

How Data Center Sustainability Can Be Measured

Organizations need meaningful metrics to understand infrastructure efficiency.

Power Usage Effectiveness

Power Usage Effectiveness, or PUE, is one of the most widely used data center efficiency metrics.

It compares the total energy consumed by a data center with the energy delivered to its IT equipment.

A lower PUE generally indicates that a greater proportion of the facility’s energy is being used by computing equipment rather than supporting infrastructure such as cooling and power systems.

However, PUE does not tell the entire sustainability story.

A data center can have an efficient PUE while still relying heavily on carbon-intensive electricity.

Renewable Energy Use

The percentage and type of renewable electricity used by a data center can provide additional insight into its operational emissions profile.

Organizations should look beyond simple claims of being “renewable” and understand how renewable electricity is sourced, accounted for and matched with consumption.

Carbon Intensity

The carbon intensity of electricity varies considerably between regions and grids.

Two data centers with identical computing equipment and energy efficiency can therefore have very different operational emissions depending on where they operate and how their electricity is generated.

Water Use

Water consumption can be particularly relevant in regions where water availability is constrained.

Cooling technology, local climate and facility design can all influence water requirements.

Hardware Lifecycle

Sustainability also extends to the physical equipment itself.

Organizations can consider:

• Hardware utilization
• Equipment lifespan
• Maintenance and refurbishment
• Reuse opportunities
• Responsible recycling
• Electronic waste management

Looking at the complete lifecycle provides a more useful picture than focusing only on electricity consumption.

Why Data Center Location Matters

Location is becoming an increasingly important part of sustainable infrastructure strategy.

A data center’s location can influence:

• Electricity carbon intensity
• Renewable energy availability
• Grid reliability
• Electricity costs
• Cooling requirements
• Water availability
• Network connectivity
• Regulatory conditions

For example, a cooler climate may reduce cooling requirements, while a region with abundant renewable electricity may provide opportunities to reduce operational emissions.

However, sustainability cannot be considered independently from other infrastructure requirements.

A suitable location needs to balance energy, reliability, connectivity, latency, cost, security and access to infrastructure.

The most energy-efficient location is not automatically the right location for every workload.

Strategies for Building More Sustainable Data Centers

Organizations have several ways to reduce the environmental impact of digital infrastructure.

Improve Workload Efficiency

Start with the workloads themselves.

Reducing unnecessary processing, improving server utilization and removing idle infrastructure can reduce energy consumption without reducing useful computing capacity.

Modernize Infrastructure

Modern cloud-native architectures, virtualization and more efficient hardware can improve infrastructure utilization and reduce unnecessary capacity.

Modernization can also make it easier to monitor workloads and allocate computing resources dynamically.

Optimize Cooling

Cooling systems should be designed around the actual characteristics of the workload.

High-density AI infrastructure may require different cooling approaches from conventional enterprise computing.

Monitoring temperature, airflow and equipment utilization can also help identify opportunities for improvement.

Use Cleaner Energy

Where practical, organizations can consider renewable energy procurement, on-site generation or infrastructure providers with access to lower-carbon electricity.

The objective is to connect infrastructure growth with a more resilient and lower-carbon energy strategy.

Use Intelligent Infrastructure Management

Data and automation can play an important role in improving infrastructure efficiency.

Real-time monitoring can identify underutilized resources, unusual energy consumption, cooling inefficiencies and workload patterns.

AI can also be used to optimize infrastructure operations, provided the additional computing required by those systems is considered as part of the overall equation.

Extend Hardware Lifecycles

Replacing equipment purely because newer hardware is available can create unnecessary material and environmental impacts.

Improving utilization, maintaining equipment properly and extending useful lifecycles where appropriate can reduce resource consumption.

Questions Businesses Should Ask Their Data Center and Cloud Providers

Businesses do not always operate their own data centers.

Cloud providers, colocation companies and infrastructure partners may control much of the underlying technology.

That makes the questions businesses ask their providers important.

Some useful questions include:

1. What is the facility’s PUE?
2. What percentage of its electricity comes from renewable sources?
3. How is renewable energy accounted for?
4. What is the carbon intensity of the electricity used?
5. How much water does the facility consume?
6. How is energy consumption measured?
7. Can customers access energy or emissions data associated with their workloads?
8. How does the provider manage high-density AI workloads?
9. How are hardware assets managed at the end of their useful life?
10. What infrastructure efficiency improvements are planned?

The objective is not to find a provider with a perfect sustainability profile.

It is to understand the infrastructure behind the technology a business depends on.

Sustainable Data Centers Are Becoming Part of Technology Strategy

Sustainability and technology infrastructure can no longer be treated as completely separate areas.

When an organization plans a new digital platform, expands cloud infrastructure or introduces AI workloads, energy and resource requirements can influence the architecture and operating model.

That can affect decisions about:

• Infrastructure architecture
• Cloud providers
• Data center location
• Hardware selection
• Workload scheduling
• Energy procurement
• Cooling technology
• Infrastructure monitoring
• Supplier selection
• Long-term operating costs

This is why sustainable data centers are becoming a business requirement rather than simply an environmental initiative.

What Comes Next for Sustainable Data Infrastructure

The next phase of data center development will likely involve much closer integration between computing infrastructure and energy systems.

AI-driven infrastructure optimization, liquid cooling, renewable-powered facilities, higher-efficiency computing, carbon-aware workload scheduling and improved infrastructure emissions data are all part of this transition.

The important shift is that sustainability is becoming part of how digital infrastructure is designed and operated.

Data centers will need to deliver computing capacity while making better use of energy, water, hardware and other resources.

For businesses, the question is therefore moving beyond whether their technology infrastructure is powerful enough.

It is increasingly about whether that infrastructure can scale efficiently, reliably and responsibly.

Sustainable infrastructure is becoming a technology decision

The digital economy depends on infrastructure that consumes real resources.

As cloud computing, AI and data-intensive applications continue to grow, organizations will need greater visibility into the energy and resources required to operate them.

Sustainable data centers are not simply about using renewable electricity or improving a single efficiency metric. They involve decisions across infrastructure architecture, energy sourcing, cooling, hardware, data and operations.

Organizations that treat energy-conscious infrastructure as part of technology strategy will be better positioned to manage the costs, resource requirements and operational challenges that come with continued digital growth.