AI-Powered Maintenance: The Key to Efficiency, Resiliency and Sustainability in Future-Ready Data Centers

By Venkataraman Swaminathan, Vice President, Secure Power Division, Schneider Electric Greater India

Data center operators are investing in state-of-the-art infrastructure to keep up with AI’s growing demands, but surprisingly, many are still relying on outdated maintenance processes to manage their mission critical equipment — from servers to cooling systems to power supply units.

With rising energy demands, staffing shortages, stricter sustainability regulations, and increasing risk of facing higher costs and downtime, the pressure is building for a change. More than ever, leveraging the power of AI is essential. That’s why Condition-Based Maintenance (CBM) is no longer optional. It’s a must for data centers that want to stay competitive, resilient and future-focused.

Why Traditional Data Center Maintenance Falls Short
In an age where technology is advancing at lightning speed, data centers operating on traditional time-based or reactive maintenance models are at significant risk of unnecessary downtime, inefficient resource use, higher maintenance costs, and compliance penalties. On top of that, they risk losing their competitive edge as others embrace more advanced, AI-ready solutions.

So, why are traditional maintenance strategies missing the mark? As AI demand grows, data centers are quickly evolving to meet expanding connectivity needs with greater computational power and capacity. They are growing in physical size, integrating new technologies, and expanding across multiple regions, creating a vast and complex web of equipment and assets — all requiring sophisticated maintenance. What’s more, the growing usage of AI applications intensifies workload management and maintenance demands. Most critically, failures in new technologies or AI applications can be extremely costly, especially in sectors like finance, healthcare, and e-commerce, where downtime can result in significant reputational damage and severe financial consequences.

In a nutshell, relying on time-based or reactive maintenance models is a gamble many data centers can’t afford. According to Uptime Institute data, the average cost of IT downtime can range from $5,600 to $9,000 per minute, with some outages costing companies over $1 million.

The risk for outages is amplified as the industry faces significant staffing shortages. In 2024, half of operators (51%) reported difficulty in finding qualified candidates to fill their job openings — for the third year running. In addition, Uptime Institute estimates, based on 25 years of data, show human error plays a role in more than 66% of data center outages.

Data centers still relying on traditional maintenance systems are at an even higher risk for downtime due to three sub-optimal processes. First, many maintenance organizations still rely on calendar-based schedules, servicing equipment based solely on set dates. This approach can waste valuable time and resources on unnecessary maintenance while increasing the risk of unexpected failures and costly downtime. Second, many equipment contracts cover a thin slice of the technology. The software and services used to manage data center equipment are still maintained at the individual asset level, not at a systems-wide (systemic) level. And third, many technicians lack the understanding, connectivity, and manpower to manage equipment from other providers or across a multi-faceted data center ecosystem.

So what’s the key to overcoming this major maintenance dilemma? Let’s take a deeper dive into how data centers can leverage AI to say goodbye to maintenance headaches and hello to a more optimized, advanced approach.

The Solution: Systemic Condition-Based Maintenance (CBM)
As data centers face tremendous growth and mounting operational complexity, the adoption of a new, more systemic, AI-driven solution is critical. By embedding AI and Condition-Based Maintenance (CBM) into the fabric of infrastructure management, data centers can cut costs, minimize downtime, optimize maintenance, and more.

CBM offers a holistic approach to overcoming maintenance challenges to deliver reliable, resilient, and efficient operations. It covers the entire lifecycle — from consulting and design to asset digitization to data-driven maintenance and modernization execution. Most importantly, it allows data centers to shift away from a reactive, calendar-based maintenance schedule to a smarter, AI-driven approach that focuses on the actual condition of equipment. This transformative shift in operations helps data center operators overcome the shortage of skilled technicians while boosting efficiency, resilience, and sustainability.

How does CBM work? It all boils down to data. Leveraging sensors that deliver real-time data on various factors, including temperature, vibration, pressure, and wear and tear, CBM monitors critical equipment continuously. Through predictive analytics, often with the help of AI or machine learning, data center operators can detect issues before they escalate, identify patterns, and optimize schedules to perform maintenance only when needed. The ability to leverage actionable insights gleaned from key data points shifts maintenance from a reactive to proactive process, helping to extend the life of the equipment and addressing potential failures before they cause serious disruptions.

In addition, CBM enables precise interventions, reducing unnecessary servicing to minimize the potential for human error. Over time, CBM-enabled data center operations not only run more smoothly, but they also improve upon themselves by harnessing the power of continuous learning. Each new data point generated refines performance, driving a cycle of continuous optimization.

Notably, even the smartest tech can’t replace human intuition, good judgment, and creativity. While AI does the heavy lifting, human feedback is a critical element of every CBM strategy, providing additional clarity and ingenuity to solving challenges that may arise or identifying abnormal events taking place within a data center’s ecosystem.

Measurable Benefits for Efficiency, Resilience, Reliability, and Sustainability
The benefits of AI-powered maintenance are undeniable. Here, we take a closer look at how implementing a CBM strategy can transform a data center from basic to next level.

Improved Efficiency and Uptime
Bolstered by the power of predictive analytics, CBM proactively detects and addresses potential failures before they lead to costly downtime. According to data from the International Energy Agency (IEA), AI-driven maintenance reduces costs and downtime by 20%.

Optimized Resource Allocation
CBM reduces manual monitoring, freeing up staff to focus on higher-value tasks. This is critical amid ongoing talent shortages. Integrating CBM from Day One, or the design phase, can pay off in a big way down the line. According to a recent Schneider Electric report, early CBM implementation can result in up to a 40% reduction in on-site maintenance interventions and a 20% decrease in operational costs. Plus, it can decrease unplanned downtime risk by up to 75%. This approach minimizes human error, reduces downtime risks, and stabilizes operational expenses (OPEX)

Enhanced Sustainability
CBM lowers energy waste and extends the lifespans of valuable, mission-critical equipment, supporting carbon reduction goals. By proactively monitoring and maintaining equipment based on its actual condition, CBM helps systems run at peak efficiency, reducing unnecessary energy consumption, contributing to sustainability efforts.

Strengthened Reliability
Data center reliability is crucial for keeping operations running smoothly, preventing data loss, and delivering consistent access to resources. CBM helps businesses maintain continuity, meet service goals, and improve performance and infrastructure strength. This is particularly critical given the continued shortage of qualified service technicians.

Stronger Cybersecurity
Security risks? Consider them handled. CBM makes it far more difficult for bad actors to compromise the data center environment by continuously monitoring and assessing the health of critical systems. With real-time insights into equipment performance, AI can quickly detect anomalies or potential vulnerabilities, enabling swift responses before threats can escalate. AI-powered maintenance also eliminates operational silos and centralizes management of critical infrastructure, reducing attack surfaces and minimizing potential points of entry.

Reduced Risk and Costs
Lastly, CBM helps prevent unplanned outages and minimizes the need for emergency repairs, which can significantly cut overall operational expenses. For instance, Compass Data Centers cut costs through AI-powered maintenance, with a shift to CBM leading to a 40% reduction in manual, on-site interventions and a 20% decrease in OPEX.

A Strategic Imperative for Executives
The bottom line: The time to act is now. Implementing CBM is the key to future-proofing data center operations, minimizing risk, and ensuring long-term success.

To fully realize the benefits of CBM, organizations must take a strategic, proactive approach to electrical asset management. Whether designing a new facility or upgrading existing infrastructure, careful planning will ultimately lead to a smooth transition and maximized, long-term impact.

If you can, integrate CBM from the start. When designing a new facility, baking AI-driven maintenance into the infrastructure from the get-go helps achieve seamless, data-powered maintenance from the very beginning.

If you are transitioning legacy systems, make sure you have a plan. Start with a phased approach to implement data integration across systems. This will allow you to more effectively mitigate risks related to operational disruptions.

Future-Ready Data Centers Demand CBM
In today’s fast-paced, ever-evolving digital world, we can’t deny the power of AI. It’s not just a tool or a passing trend — it’s a driving force for real transformation. To stay ahead and stay relevant, data center leaders must embrace systemic CBM now. Without CBM, data centers are exposed to critical risks — costly outages, missed opportunities, and the danger of falling behind in an increasingly competitive landscape. On the other hand, data centers that adopt CBM will evolve into future-ready powerhouses, harnessing AI to optimize operations, enhance efficiency, and drive innovation to tackle whatever comes next.