The data center industry is at the precipice of a complete transformation. As AI dramatically changes computation capabilities, data centers are becoming high-performance, energy-intensive facilities that must balance security, scale, and speed without sacrificing security. Data center automation is driving this transformation by enabling better system integration and control, improving energy efficiency, and enhancing flexibility.
However, the path forward isn’t easy – factors like cost, environmental concerns, and public perception are all moving targets. Sustainable growth requires strategic control system architecture, experienced engineers, and a process automation solution to the biggest issue with AI-driven data centers: power consumption.
AI is the future of automation; data centers must scale to support AI, but they have to do it intelligently. Let’s discuss the state of the data center industry, forecasts, challenges, and how automation technology can be leveraged to solve its own problems:
Projections for Data Center Automation & AI
Globally, an estimated $300 billion dollars will be spent on data center infrastructure this year. The data center industry is set to grow 15% each year, which will still fall short of what’s needed. Some relevant projections we’re seeing in the data center industry include:
- Globally, data center electricity usage is set to double in just five years, from 536 TWh in 2025 to a projected 1065 TWh in 2030.
- Hyperscalers will need to invest nearly $2 trillion in data center-related capital globally between 2024 and 2030.
- The demand for AI-ready data center automation is set to grow 33% annually between 2023 and 2030.
- Preleasing rates for data center space will skyrocket up to 90% and competition for space will continue to hike rent prices.
- The global market for data center liquid cooling is set to expand more quickly than the industry itself, from $4.9 billion in 2024 to $21.3 billion in 2030.
- AI workloads are projected to account for 70% of demand on data center capacity by 2030.
- The US is set to continue as the largest data center market, accounting for nearly 20% of the global market.
- Secondary and tertiary markets (e.g. Indiana, Ohio, Virginia) – locations which coincide with major gas pipelines – are expected to house 70% of the data center growth in the US.
Challenges to Meeting Demand: Power & Impact
With the rapid development of AI and its applications, data centers have semi-jokingly been referred to as “AI factories”. No longer just about storing data, these facilities must now provide real-time computation and industrial data analytics at scale, adapt to changing workloads, and optimize energy consumption.
But there is a big obstacle data centers must overcome: balancing power needs for massive cooling operations and compliance with environmental impacts like water usage and power grid stress. Addressing this becomes even more complicated with increasing government oversight and growing public resistance to the construction of new hyperscale data centers.
Both in the US and abroad, governments are increasing regulations on data center development to stem growth – a result of public interest in housing and retail development, concern the current infrastructure can’t support the rapid growth, and fear major expansions will nullify decarbonization efforts. Data center emissions are projected to double by 2030 as increased demand for power will likely rely on natural gas to bridge the gap between hydrogen and nuclear power.
While at first this dilemma seems unresolvable, emerging strategies in choice of location and power autonomy coupled with building automation companies implementing integrated data center infrastructure management (DCIM) provide a pathway forward. The key to sustainable growth will be an all-encompassing approach focused on integrated lifecycle analysis (LCA) on environmental, social, and economic impacts of the industry.
Exploring Energy Solutions for AI-Ready Data Centers
The reality is that, regardless of the obstacles, we must find a way to integrate data centers into the fabric of societal infrastructure – we simply can’t progress otherwise. Understanding this reality, major developments in automation technology and development strategy open doors for other ways to decrease emissions, impact, power stress, and more:
Gradual Fossil Fuel Transitions
Natural gas infrastructure is expanding to meet the needs of data center growth. Natural gas is readily available, cheap, reliable, and energy dense. However, even the smartest gas facilities rarely reach 50% efficiency. Steam methane reforming disassociates natural gas into hydrogen and carbon monoxide, which increases efficiency to 75% when combined with carbon capture storage.
Integrating ~20% hydrogen into natural gas can be achieved without significant equipment or automation upgrades to existing plants or major changes to pipelines. This offers an affordable, low-impact bridge to transition away from natural gas and toward cleaner hydrogen power.
Flexible, Autonomous Power Systems
Hyperscalers are leading the charge with hybridized power systems controlled by intuitive automation systems that can prioritize where and when power is sent throughout the building. This allows integration of clean energy sources without sacrificing power reliability. It also lessens stress on the power grid and opens the possibility to previously non-viable locations for new data centers.
Another development is the implementation of microturbines for natural gas and microreactors for nuclear energy. The deployment speed of natural gas microturbines ensures reliable power even in grid outages and makes it the convenient choice of backup power for renewables like solar and wind.
Similarly, microreactors can bridge the transition to nuclear power with an uptime of 12-24 months (as opposed to 10-20 years), lower upfront cost, passive cooling technology, safer fuels, and modular design, which makes scaling simple. Microreactors have flexible load-carrying capacity complementary to data center automation systems managing integrated power sources.
Data Center AI Infrastructure
AI-driven integrated controls can also optimize efficiency with predictive maintenance, machine learning, and digital twin. Advancements in graphics processing unit (GPU) and central processing unit (CPU) architecture can support AI models on massive scales, enhance AI performance, and absorb workload. Connectivity and bandwidth advancements enable faster data transfer and lower latency rates, improving AI workload efficiency.
AI rack design is also responding to the power problem by developing integrated AI solutions and modular racks that allow efficient scaling. At the same time, hyperscalers with the capital to do so are investing heavily in advancing AI technologies, including tensor processing units (TPU) custom-designed for AI workloads, custom hardware optimized for AI, and chip technology, including modifying/recycling legacy AI chip technology.
Advancements in Liquid Cooling
At this scale of data center automation, air cooling just doesn’t cut it. Liquid cooling presents several issues related to environmental regulations, as some coolants are controlled or restricted. Direct-to-chip cooling is currently the most common method used across data centers because it’s efficient and allows densification of computing (i.e. more workload per rack) without overheating and can be run on a closed loop to recycle the liquid.
A newer technology called immersion cooling is gaining traction because it increases cooling efficiency, reduces waste, and can be used with non-toxic, non-flammable, biodegradable dielectric fluids. Single-phase immersion cooling is very low maintenance and easy to access when repairs are needed, adding to its convenience and efficiency.
With evolving technology and expanding rules and regulations, the elusive solution to the data center dilemma is actually quite simple: strategy, planning, and patience. We must keep goal horizons aligned so that growth, decarbonization, social ethics, and economic trajectories are equally weighed in decision making. Cooperation throughout each step of the supply and service chains is vital.
Zero Defects, Zero Trust: A Main Automation Partner for Data Centers
E Tech Group’s depth of experience in the Mission Critical field has led us to enterprise our Zero Defect control system design for data center automation. A method entrenched in zero-trust access, multifactor authentication, and security redundancies, Zero Defect architecture minimizes risks of system failures and security breaches while optimizing energy efficiency and usability of operational data.
No question – the growing demand on data centers coupled with the power-hungry nature of AI is a stress on the industry. A Main Automation Partner can take some of that pressure away by guiding you through a sustainable growth process focused on short-term ROI and long-term success.