Revolution in Thermal Management: Specialist Assesses Advances in Heat Transfer Optimization with Artificial Intelligence in Data Centers

The importance of data centers for organizations has grown significantly in recent years, even though the emergence of this resource is nearing a century of existence. Over this time, the rise of new technologies has driven a satisfactory level of progress, and the outlook for a future already in motion has become quite favorable—not only for the professionals involved but, above all, for the users of these resources.

One of the most recent boosts to advancements in data centers is directly tied to the emergence of Artificial Intelligence (AI). While data centers have been building a globally consolidated history since the 1940s, the first experiments with Artificial Intelligence may date to a similar period chronologically. However, the face of AI as we know it today has only truly emerged and become widespread over the last two decades or so, when areas beyond the military and academia gained access to this reality.

And one very specific factor has tightened the relationship between AI and storage devices: a fundamental operational need was made easier—namely, cooling equipment. This step is crucial to strategic maintenance planning, preservation, and effective safety in the use of these electronic giants spread across the globe.

“When we talk about the benefits of a well-implemented cooling system for data centers, we’re talking about reducing energy consumption and, consequently, lowering operating costs. Over the long term, we can also point out that equipment can become smaller in physical and structural size, which, in short, can lead to huge environmental advantages by meeting Sustainability criteria during manufacturing and maintenance.”

This relevant synthesis of the relationship between AI and resource optimization in data center cooling systems comes from Indian mechanical engineer Mohit Shrivastava. With nearly 13 years of experience in the field, his expertise in discussing the most effective ways to transfer heat in such projects—based on his own hands-on work—is just one of the credentials he has acquired along the way.

Verified Data

The progress in this field can easily be illustrated by 2024 figures, with Brazil serving as an example. The South American nation is one of the leading economies in Latin America, the Southern Hemisphere, and among emerging countries. In this local market alone, a major industry player invested approximately US$ 2 billion in improving its data center systems last year.

It is estimated that the same market, on a global scale, reached close to US$ 10 trillion. This would represent growth of around 10% compared to the previous year’s results. The amount is linked not only to required structural upgrades but also to consulting services for public- and private-sector institutions worldwide.

“There’s no doubt that proper equipment maintenance is central to the strategic planning behind these investments. Optimizing the proper use and service life of these databases—alongside their security—may well be the main focus of these plans and investments. In other words, proactive planning to anticipate problems is something those responsible cannot forgo. After all, we’re talking about greater security for all users, who place significant trust in these services, as well as about the credibility earned by organizations that approach this responsibility as strategically as possible.”

Successful Scenarios

Artificial Intelligence has opened up multiple possibilities for achieving the resource optimization that Mohit Shrivastava highlights in the context of data center cooling systems. These possibilities range from system planning to ensuring no potential improvement is overlooked at any stage.

One example comes from Nordic countries in Europe, where the environment makes it possible to use cold seawater. AI plays its part by calculating the exact formula to apply in the process. However, as emphasized, this is just one possibility, as the use of other renewable sources is also being expanded through the new partnership.

“And it doesn’t stop there. Optimizing these resources covers every stage of the process. Another example is in the training of on-site professionals. We are dealing with tools capable of enhancing the skills of an already trained workforce, providing new platforms, and implementing new structures that are far more accessible and faster in carrying out these necessary operational steps—while also being much safer and more efficient.”

A Distinguished Career

Mohit Shrivastava is an experienced mechanical engineer with over 13 years in engineering analysis, electromechanical systems, and energy modeling. He is currently Director of Engineering Analytics at Switch, Inc., where he leads initiatives to integrate advanced Artificial Intelligence (AI) and Machine Learning, predictive analytics, and digital engineering tools to optimize data center performance.

The Indian expert has also stood out for other innovative pursuits in the field. One of these involves solving complex engineering challenges by bridging the physical and digital worlds—leveraging the expertise he has built in computational modeling, control systems, and machine learning.

Previously, as Senior Mechanical Engineer III at Amazon Web Services, Shrivastava led energy audits, developed physics based models in Python for predicting energy consumption, and created global PUE/WUE strategies for more than 200 hyperscale data centers. He also served as a Technical Lead and Founder of Data Center AI Research Group in integrating AI and Machine Learning into operational workflows to enhance diagnostics and engineering insights.

He holds both a bachelor’s and a master’s degree in Mechanical Engineering from Mississippi State University in the United States and is a licensed Professional Engineer (PE) in California and Oregon. Shrivastava is currently pursuing ISO 50001 auditor certification and holds credentials in advanced HVACR and pressure vessel design. With a passion for digital transformation, he is committed to building future-ready infrastructure through data innovation and sustainable engineering.