
Powering the AI revolution: Solving the energy and sustainability puzzle of data centers
In a world increasingly driven by data and digital intelligence, the race to build bigger and faster
AI
models is fundamentally reshaping the
energy
landscape. From powering predictive algorithms to training generative models like ChatGPT,
Artificial Intelligence
(AI) is no longer just a tool—it's the engine behind the modern economy. But this engine has a growing appetite, and at its core lies one of the most energy-intensive infrastructures of the digital age: the data center.
The Surge of AI—and Its Energy Wake
The AI boom is rewriting the rules of infrastructure planning. According to the International Energy Agency (IEA), global data center electricity consumption could double by 2026, reaching over 1,000 terawatt-hours (TWh)—roughly comparable to the annual electricity demand of Japan. This spike is being driven not only by hyperscale cloud providers, but also by a new generation of AI workloads that require massive computing power and near-continuous uptime.
A single AI query can require 10 times more energy than a typical web search. With audio-visual generative tools on the rise, the pressure on energy systems will only intensify. Already, data centers consume about 1.5% of global electricity and contribute to 1% of energy-related greenhouse gas emissions—figures expected to rise sharply as AI adoption scales.
The Power Trilemma: Energy, Carbon, and Water
Behind every AI interaction is a complex physical footprint: rows of processors, high-density cooling systems, and vast power supply chains. Nearly 40% of a data center's electricity goes to computing, and another 40% to cooling. But energy and emissions aren't the only concerns—water use is an emerging and often underappreciated pressure point.
Consider this: a 20-question AI session can indirectly consume about 500ml of water, primarily for cooling. In the U.S., mid-sized data centers can withdraw up to 300,000 gallons of water a day—enough to meet the daily needs of 100,000 households. By 2027, AI-related water withdrawals could reach up to 6.6 billion cubic meters globally, compounding the environmental burden in already water-stressed regions.
This growing trilemma—energy intensity, carbon emissions, and water use—is pushing the industry to rethink how data centers are powered and cooled.
Redefining the Energy Stack: Smarter Solutions for a more sustainable AI
To support AI's exponential growth while meeting
sustainability
targets, the industry is turning to next-generation energy technologies. These innovations are enabling resilient, efficient, and lower-carbon emission power systems—a crucial shift for an AI-driven future.
https://www.youtube.com/watch?v=7I8Szv2W-6Y
1. High-Efficiency Turbines for More Sustainable Power
Flexible gas turbine technologies are gaining traction for their ability to help deliver high power -density at a lower-carbon power. GE Vernova's aeroderivative gas turbines, for example, are engineered for high performance with lower emissions, offering the ability to run on natural gas, hydrogen blends, or biofuels. Their modularity and fast ramp-up capabilities make them ideal for powering high-load facilities like AI data centers—especially in regions with constrained grid access or unstable supply.
Just as important, these turbines consume significantly less water than traditional power systems—an advantage in arid zones like India, the Middle East, or sub-Saharan Africa.
2. Resilient Grids and Smart Storage
Reliable power isn't just about generation—grid stability and storage are critical, especially for data centers that can't afford downtime. Integrated systems like GE Vernova's FLEXRESERVOIR provide a modular solution: combining battery storage, inverters, and intelligent energy management systems to help facilities integrate renewables, manage peak loads, and ensure 24/7 uptime.
Such systems are key to balancing AI data center load fluctuations, ensuring power stability, and providing the fast-response backup power to the facilities.
3. Cooling Reinvented: Toward Zero-Water Operations
On the cooling front, innovation is transforming efficiency. Traditional water-intensive methods are giving way to advanced alternatives:
Liquid cooling systems now deliver targeted heat removal at the chip level.
Immersion cooling submerges hardware in specialized fluids, improving performance and slashing water use.
Rear-Door Heat Exchangers allow localized cooling for high-density racks, reducing overall system demand.
These approaches not only boost energy efficiency but also set the stage for near-zero water usage—a breakthrough for future-ready data centers.
Regional Relevance: India as an AI Growth Hub
India is fast emerging as a pivotal AI marketplace. Although it generates nearly 20% of the world's data, it currently hosts only 5.5% of global data center capacity—a stark infrastructure shortfall. This gap is driving a wave of investment, with up to $60 billion expected in cloud and server infrastructure.
'As government policy pushes digitalization and lower-carbon emitting energy systems adoption, India has the potential to become a sustainable data center hub. But doing so will require smart, efficient energy systems that address both power and water constraints—an area where advanced technologies like GE Vernova's turbines and storage platforms can make a meaningful difference.' –
Venkat Kannan
, President, Gas Power Solutions, Asia at GE Vernova.
The Path Forward: Building a Sustainable Digital Future
The
AI revolution
is already reshaping economies—but how we power it will define its long-term impact. Solving the Power Trilemma with performance and sustainability demands a hybrid, intelligent energy mix—where flexible generation, renewable integration, and innovative cooling converge.
By deploying scalable solutions tailored to local realities—and by embracing technologies that reduce both emissions and water use—we can build an AI infrastructure that's not just powerful, but planet-positive.
This is the crossroads where AI meets energy innovation. And the future of computing will be shaped by how we solve the puzzle of power.

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles


Economic Times
10 minutes ago
- Economic Times
Is 'vibe coding' the hottest skill for IT jobs? With industry leaders riding the trend, it is the new must-have skill for coders
iStock Tech companies are now hiring engineers based on their ability to use AI coding tools, a skill dubbed 'vibe coding.' With firms like Visa, Reddit, and DoorDash listing it as essential, the trend promises faster product development. (Representational image: iStock) Move over traditional coding tests—tech companies now want you to 'vibe' with code. A new trend called vibe coding is sweeping through Silicon Valley, and major companies like Visa, Reddit, DoorDash, and even Google are paying attention. This intuitive, AI-driven approach to software development is not only changing how code is written, but also who gets hired to write it. Forget perfect resumes; your mastery of AI code generators might just be your ticket to the next big to Business Insider, job listings are no longer just asking for Python or JavaScript. Business Insider has uncovered a wave of job postings from industry giants like Visa, Reddit, DoorDash, and cybersecurity unicorn Snyk, explicitly demanding experience with or familiarity with AI code generators like Cursor and Bolt. This isn't just a niche requirement; for some, it's quickly becoming "essential." Visa, for instance, recently posted three generative AI engineer positions in Austin that list familiarity with vibe coding tools as "essential." Reddit is actively seeking an engineer to integrate AI coding tools and engage directly with the broader vibe-coding community to "drive adoption." DoorDash and Snyk also feature similar requirements, with Snyk specifically seeking "deep expertise."Perhaps the most striking embrace comes from Y Combinator startup Domu Technology, which has declared "vibe coding experience" a "non-negotiable." Their job description boldly states that at least half of the hired candidate's current code should already be underlying motivation behind this fervent embrace of vibe coding is singular: speed. These companies are desperate to "turbocharge" their engineering teams and boost "velocity" – the rate at which they can build and ship products. CTO of Intuit, Alex Balazs, has approved multiple AI coding tools, including Cursor and Microsoft Copilot, stating he has "no regrets." He reveals that "a great engineer using one of these tools can be up to 40% faster in terms of coding." Streaming service Tubi wants an engineer to integrate AI tools to "boost velocity," and Udacity seeks to "accelerate" product development through AI-savvy hires. Visa's positions also specifically mention "rapid" code and prototype generation. The term "vibe coding" itself gained prominence from influential tech leaders. Google and Alphabet CEO Sundar Pichai has openly shared his "delightful" experiences with "vibe coding" — a casual yet cutting-edge way of using AI tools to build webpages with minimal manual programming. Speaking at Bloomberg Tech , Pichai mentioned experimenting with AI-powered coding assistants like Cursor and Replit to create a custom webpage. He emphasized the immense power AI is bringing to web development, a level unseen in 25 years. This shift isn't just about speed; it's about a more intuitive, AI-driven approach where developers become collaborators with AI, simply explaining their desired outcome in plain language rather than writing lines of code. OpenAI co-founder Andrej Karpathy first popularized the concept, suggesting developers can "forget that the code even exists" as natural language prompts become the new programming interface. This trend is backed by massive user growth and investment, with Cursor hitting $100 million in annual recurring revenue and Amazon reportedly in talks to deploy Cursor for its staff. While vibe coding is undeniably gaining traction, it's crucial to understand it's not yet threatening the jobs of seasoned senior engineers. Experts clarify that AI code generators are primarily useful for automating "boilerplate code" and simpler tasks, freeing up engineers to focus on more complex, higher-level problems. Mohammad Sanatkar, a former senior machine learning engineer at Waymo now running an AI agents startup, notes that these tools excel at tasks like building a website's front page, but "I don't think they are skilled enough to do core software improvements" or handle shipping production-ready code. Intuit's Balazs echoed this, stating his company appreciates engineers who "love leveraging AI" to solve problems, rather than exclusively seeking "vibe coders." While the term may sound like Gen Z jargon, vibe coding has become a serious global movement. The cultural shift is undeniable. With powerful backers, exponential growth, and the support of tech leaders like Sundar Pichai, vibe coding may soon become as mainstream as GitHub. Vibe coding represents more than a toolset—it's a mindset. It breaks down the gatekeeping of traditional programming, making it more about creativity than technical ritual. Whether you're a beginner with big ideas or a seasoned coder looking to cut corners, AI has become a collaborator, not a competitor.


Time of India
15 minutes ago
- Time of India
CEO Sundar Pichai reveals Google's ‘Most Important Metric' and how company is tracking it
Google CEO Sundar Pichai revealed that AI has boosted software engineering productivity by 10%, a metric the company actively tracks. Google measures this by assessing the increase in engineering capacity, in hours per week, gained through AI tools. Google CEO Sundar Pichai has claimed that artificial intelligence (AI) is increasing the productivity of the company's software engineers. He also noted that the Alphabet-owned tech giant is actively measuring the impact of AI on its engineers. During a recent episode of the "Lex Fridman Podcast,' Pichai explained that Google is closely observing how AI is boosting the output of its software developers. As per Pichai, it is "the most important metric,' and the company 'carefully measures it.' He even mentioned that Google actively measures 'how much has our engineering velocity increased as a company due to AI?" Pichai noted that the company currently estimates a 10% boost in engineering velocity attributed to AI. How Google tracks AI's role in increasing productivity of its engineers According to a report by Business Insider, a Google spokesperson explained that the company tracks AI's role in improving productivity of software developers by measuring the increase in engineering capacity created, in hours per week, through the use of AI-powered tools. To put it simply, it's a way of measuring how much extra time engineers are gaining for using AI tools by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like 5 Books Warren Buffett Wants You to Read In 2025 Blinkist: Warren Buffett's Reading List Undo As for whether Google expects that 10% figure to continue rising, Pichai didn't clarify. However, he noted that agentic capabilities, where AI can take actions and make decisions more autonomously, will unlock the "next big wave." Google has also developed its internal tools to assist engineers with coding. Last year, it launched an internal coding copilot named "Goose," trained on 25 years of Google's technical history, Business Insider previously reported. While AI is playing a growing role, Pichai said during the podcast that Google still plans to hire more engineers next year. 'The opportunity space of what we can do is expanding too,' he said, adding that he hopes AI will reduce some of the grunt work and free up time for more enjoyable aspects of engineering. Meanwhile, the company is also monitoring the volume of code being generated by AI within Google, a figure which is reportedly on the rise. At Alphabet's most recent earnings call, Pichai mentioned that more than 30% of the company's new code is now generated by AI, up from about 25% in October 2024. Apart from Google, Microsoft UK CEO Darren Hardman said its GitHub Copilot coding assistant now writes 40% of the company's code at London Tech Week this week. He noted that this change is 'enabling us to launch more products in the last 12 months than we did in the previous three years.' In April, Meta CEO Mark Zuckerberg predicted that AI could handle half of Meta's developer work within a year. HP EliteBook Ultra Review: Thin, light, power in a premium package AI Masterclass for Students. Upskill Young Ones Today!– Join Now


Time of India
22 minutes ago
- Time of India
Meta builds AI superintelligence lab, eyes $10 billion deal with Scale AI's Alexandr Wang
Why Meta's betting big on Wang and Scale AI Live Events Zuckerberg's long game: From early losses to AI powerhouse AI arms race: The billion-dollar club What's already in motion at Meta (You can now subscribe to our (You can now subscribe to our Economic Times WhatsApp channel Meta is setting up a new artificial intelligence research lab with a bold goal: to develop 'superintelligence,' a system that could surpass human cognitive abilities. The news, first reported by The New York Times, marks Meta's most ambitious AI project to the centre of this effort is Alexandr Wang , the 28-year-old founder and CEO of Scale AI. He is expected to play a leading role in the new lab's operations. Meta is also in advanced discussions to invest over $10 billion in his start-up, according to a separate report by Bloomberg. The deal may also see a number of Scale AI staff transition to companies declined to comment on the has emerged as one of the most prominent figures in the AI industry. His company, Scale AI, supplies data infrastructure essential for training large language models — the same kind used in AI systems like ChatGPT. His addition to Meta's team reflects a larger recruitment drive by the tech to sources cited by The New York Times, Meta has offered compensation packages ranging from seven to nine figures to top researchers from rivals like Google and OpenAI. Some have already agreed to come on push to hire top AI minds comes amid internal challenges. The company has faced management struggles, employee churn and several underwhelming product launches in its AI division, two of the people familiar with the matter told the Zuckerberg, Meta's chief executive, is not new to the AI race. After losing a bid to acquire DeepMind in 2013 — a key moment that propelled Google's AI efforts — he launched Meta's first dedicated AI lab the same year. Since then, Meta has invested heavily in AI, building tools for content moderation, recommendation engines, and now, generative sees 2025 as a turning point. 'AI is potentially one of the most important innovations in history,' he said in February. 'This year is going to set the course for the future.'Meta has earmarked up to $65 billion for capital spending on AI infrastructure this year is not the only tech firm placing massive bets on AI. Microsoft has invested over $13 billion in OpenAI, the creator of ChatGPT. Amazon has pumped $8 billion into Anthropic, while Google paid $3 billion last year to license technology and recruit talent from a start-up known for its conversational companies are all chasing artificial general intelligence (AGI), a system that can replicate human intelligence across any domain. Meta, however, is setting its sights even higher — superintelligence , which would go beyond AGI in both scope and superintelligence remains a theoretical goal, it's considered by leading researchers to be the ultimate destination for AI before the formation of this new lab, Meta had begun rolling out AI products at scale. Last month, the company revealed that its AI assistant now supports over a billion monthly active users across apps like Facebook, Instagram, and February, CNBC reported that Meta was preparing to launch a stand-alone Meta AI app in the second quarter, along with a paid-subscription model similar to OpenAI's the high costs and intense competition, Meta appears determined to lead the next wave of AI innovation — and with Wang on board, it's signalling that this ambition is more than just stakes are clear. If Meta succeeds, it won't just catch up to its rivals — it could redefine the field. With billions in play, the hiring of Wang, and a lab focused on the frontier of AI capabilities, Meta is gambling big on a future where machines might not just match human minds — but exceed the industry, and for users around the world, the outcome of this gamble will shape the direction of technology for years to come.