As Artificial Intelligence (AI) rapidly redefines the technological landscape in the Philippines, organizations are under pressure to modernize their data centers. AI’s demands for increased power, cooling, and scalability

are pushing businesses to reconsider their IT infrastructure to stay competitive and meet growing operational needs.

According to a PricewaterhouseCoopers (PwC) Philippines

study,

74% of CEOs in the country believe AI technologies such as Generative AI will enhance efficiency and benefit employees. They are optimistic that this will open doors on integrating other AI technologies in the future.

However, recognizing the importance of AI is just the first step. According to a Cisco

study,

the Philippines faces significant challenges in AI readiness, with most organizations classified as “Followers” or “Laggards” across multiple pillars, such as infrastructure and strategy. The study revealed that only 14% of Philippine organizations are fully

prepared with scalable IT infrastructure for AI, while 49% report limited scalability and require upgrades. On the strategic front, 77% of organizations are considered “Pacesetters” or “Chasers” in terms of AI adoption, yet only 26% prioritize it in their

budgets. Moreover, 98% of businesses report increased urgency to adopt AI, but only 29% have a comprehensive change management plan.

So this raises an important question: Are organizations in the country truly prepared for AI at scale, especially as they increasingly rely on it to redefine their operations?

As AI becomes central to business operations, enterprises face an urgent need to modernize their data centers to handle the heightened demands of this technology. Vertiv Philippines Sales Director Pamela Albar emphasized the critical role data centers play

in this shift.

“Large companies rely on enterprise data centers to support their IT needs. These centers house high-density infrastructures, including servers, racks, and network systems that process crucial internal data. With the rise of AI, these data centers are now compelled

to process AI workloads too. That’s why these facilities must have essential infrastructure like power, cooling, and environmental monitoring systems. Any downtime can severely impact business operations and the chance to stay competitive in today’s AI-driven world,” said Albar.

To keep pace with fast-evolving technology, Vertiv shares several strategies for optimizing data center capacity, ensuring that businesses stay ahead in the AI technology race.

Winning the AI tech race means addressing infrastructure challenge

AI presents a double-edged sword for large companies. While it improves processes and drives innovation, it also introduces new challenges—particularly the need for infrastructure that can handle higher-density operations.

AI applications are power-intensive, demanding significant electricity, energy, and processing resources. To function effectively, these applications require advanced hardware such as Graphics Processing Units (GPUs), which accelerate graphics and rendering

tasks. However, traditional enterprise data centers, which typically support around 10 kilowatts per rack, are ill-equipped to meet the substantial 50 to 100 kilowatts per rack required by AI applications. This creates intense pressure on organizations to

cope with the surge in demand for business applications that require minimal latency. Consequently, data centers must adapt to the increased heat, energy usage, and workload generated by these activities.

Vertiv recognizes the need to bridge the gap between IT and data centers. To this end, they offer comprehensive solutions tailored to the specific demands of AI workloads.

Scaling up for AI: The need for a 360 data center solution

The fast-paced growth of AI applications for businesses underscores the importance of scalability. Failing to prioritize scalability puts organizations at risk of falling behind in the AI race. Therefore, businesses need to build future-ready data center infrastructure

that can scale to meet evolving demands.

Three core areas should be prioritized when improving enterprise data centers for AI: power, cooling, and infrastructure

Addressing power demand

AI workloads, particularly those involving large-scale data processing and machine learning, require immense computational power. Traditional power systems are often insufficient, leading to inefficiencies and even downtime.

To address this, modern data centers need solutions that can deliver high-density power while ensuring energy efficiency. For instance, adopting scalable power solutions like modular UPS systems can help businesses maintain continuous power flow even during

grid failures. Additionally, smart power distribution allows real-time monitoring and control, ensuring that power is delivered precisely where and when it’s needed, reducing waste and operational costs. Implementing these solutions means businesses can meet

AI’s growing power requirements while optimizing energy use and minimizing disruptions.

Embracing advanced cooling solutions

AI systems, particularly those using GPUs, generate substantial heat. Excessive heat can slow down processing speeds and damage hardware. To manage this, businesses should adopt innovative cooling solutions.

Liquid cooling technologies directly cool critical components inside servers, ensuring that no excess heat builds up. Combining liquid cooling with air systems can optimize energy consumption and extend equipment life, allowing businesses to operate AI applications at peak performance. Some examples are Direct-to-Chip Liquid Cooling, Modular Rack Cooling, Rear-Door Heat Exchangers, and more.

Investing in scalable and flexible infrastructure

Addressing infrastructure demands requires creating a flexible and scalable environment that grows alongside AI needs. Traditional data centers can be rigid, but AI requires modular infrastructure for seamless expansion.

Prefabricated modular data centers, for instance, provide a plug-and-play solution that allows businesses to add capacity quickly without long lead times. These modular units come equipped with integrated power and cooling systems, making deployment faster

and more efficient. Remote monitoring tools also provide full visibility into data center performance, helping businesses predict maintenance needs and avoid costly downtimes.

Looking Ahead to the Future of AI and Businesses

As technology continues to evolve, every business must prioritize future-proofing its operations. The future of industry demands 24/7 efficiency with no tolerance for downtime, and organizations that fail to meet these standards risk falling behind. Vertiv understands this challenge and is at the forefront of supporting the growing demand for AI technologies, bridging the gap between AI and data centers.

Vertiv’s 360AI Reference Solution provides a comprehensive and transformative approach to managing high-density AI workloads. With scalable designs tailored to meet a wide range of needs—from single racks to expansive, modular data centers—this solution addresses the core challenges of AI infrastructure: power, cooling, and deployment efficiency. Vertiv’s 360AI not only ensures efficient power distribution and advanced cooling strategies but also simplifies deployment through its pre-engineered, modular systems, reducing setup time by up to 50%. Vertiv also offers reference designs, enabling businesses to draft comprehensive strategies that align with their specific AI needs and growth objectives.

By delivering an all-in-one solution that integrates these essential components, Vertiv is empowering organizations to keep pace with the AI revolution. The key to staying ahead in the AI tech race lies in being agile, efficient, and future-ready. With Vertiv’s 360AI, businesses can confidently embrace the future of AI with the reliability and scalability they need to thrive.

To learn more about how Vertiv supports the continuity of today’s vital business operations, visit Vertiv.com