The launch of ChatGPT in November 2022 marked a pivotal moment in AI adoption. In just a little more than two years, AI has become a cornerstone of business operations. A McKinsey & Company global survey in 2024 indicates that 65% of organizations are now regularly using generative AI, nearly doubling from the previous survey ten months prior.
However, the AI boom has a hidden cost, as AI's energy demands are staggering. Cornell University’s 2023 study highlights that processing 50 ChatGPT prompts consumes nearly 500ml of water. Goldman Sachs further reveals that ChatGPT requires ten times more electricity than Google’s search engine to process a single query.
As AI use grows, data centers—already responsible for 1% to 2% of global power consumption—could account for 3% to 4% by 2030, potentially doubling their carbon emissions. Without intervention, this trajectory jeopardizes businesses' ability to meet net-zero targets by 2050.
A Vision for Sustainable AI
Despite these challenges, AI’s potential to support sustainability is immense. Leaders are now rethinking how AI can contribute to environmental goals rather than hinder them. Sheila Rohra, CEO of Hitachi Vantara, notes in a recent article how the training phase of machine-learning models requires huge amounts of energy. “If businesses routinely retrain these models, their energy needs will be substantial and long-term. This simply won’t be sustainable with their ESG goals. We need to retune algorithms, so they require less retraining and energy consumption,” she says.
Smarter algorithms and energy-efficient data storage platforms are at the heart of this transformation. By optimizing machine learning and infrastructure, businesses can decarbonize data centers while maintaining AI-driven insights to advance broader sustainability objectives.
Decarbonizing Data Centers
Hitachi Vantara is leading the charge with solutions designed to reduce data center emissions. Its Virtual Storage Platform One (VSP One) Block has demonstrated a 30% to 40% reduction in power consumption. Rohra notes that transparency and commitment are essential: “We are proud to say our technology has one of the lowest carbon footprints compared to other data-infrastructure providers.”
This approach is already delivering results. For instance, Infosys leveraged Hitachi Vantara’s technology to cut electricity and air-conditioning costs by 60%, all while achieving 90% faster application performance. Similarly, BMW Group benefitted from a seamless storage migration that reduced its carbon footprint by 70% and cut power consumption by 80%.
AI’s Role Beyond Data Centers
The potential of AI extends far beyond infrastructure. For example, AI can revolutionize carbon accounting by automating complex calculations, providing accurate and actionable insights for businesses. It can also enhance energy trading by analyzing market fluctuations, helping organizations save money while optimizing their energy usage.
Hitachi Vantara’s AI discovery service exemplifies this broader impact. By generating data-driven insights, the service supports key decisions in areas like manufacturing, logistics, and energy management. Rohra explains, “Some businesses lack the expertise to transition to energy-efficient operations. AI can simplify this process by highlighting short- and long-term sustainability benefits while reducing costs.”
Achieving sustainable AI requires a holistic strategy that combines smarter algorithms, efficient infrastructure, and forward-thinking leadership. The journey is not without hurdles, but the opportunities are transformative. Hitachi Vantara’s commitment to carbon neutrality by 2030 underscores its belief that businesses can embrace AI sustainably.
The future of AI doesn’t have to come at the planet’s expense. By prioritizing innovation alongside environmental responsibility, solution providers can help customers harness AI to build a greener, more sustainable world.
Learn more about how to decarbonize the data center with Hitachi Vantara sustainability solutions.
Image credit: Hitachi Vantara