Dassault CSO: Frugal AI Needed to Combat Energy Surge
AI-related data centre energy consumption could reach 3% of global power demand by 2030, with some regions confronting more severe pressures. Ireland, which hosts major digital service providers, faces the prospect of AI-related data centre energy use reaching 35% of national power consumption.
The International Organization for Standardization has published guidance ISO/IEC 42005 to help companies assess AI's broader impact on society, including environmental costs. The development comes as the sector grapples with balancing technological advancement against energy constraints.
Philippine de T'Serclaes, Chief Sustainability Officer of French software company Dassault Systèmes, maintains optimism about AI's environmental potential despite the mounting energy demands.
Machine learning algorithms deliver grid efficiency improvements
Recent studies demonstrate machine learning algorithms can improve grid efficiencies by 15% and boost battery storage efficiency by 10-20%. AI could reduce schedules for new clean energy projects by approximately 20%, potentially saving hundreds of billions of dollars by 2050.
McKinsey estimates that AI and ML could accelerate 47% of initiatives required to achieve the global 1.5-degree pathway under the Paris Agreement. The technology has already contributed to sustainable innovation, including lightweight packaging requiring less transport energy and advanced materials for efficient batteries. Recent research demonstrates AI-developed paint coatings that could reduce building temperatures by 20°C.
Current deployment patterns raise concerns about energy sourcing. MIT's Technology Review warns that rapid application growth means "data centers are expected to continue trending towards using dirtier, more carbon intensive forms of energy."
Dassault Systèmes partners with Quanta Cloud Technology for efficiency gains
Addressing this challenge, Dassault Systèmes has formed partnerships with Quanta Cloud Technology (QCT), the Taiwanese server manufacturer, for efficiency gains. Philippine advocates "Frugal AI" approaches that emphasise lightweight models and measurable impact.
We have what we need to make the infrastructure and ecosystems that power AI start working more effectively today.
Model pruning allows programmers to remove unnecessary neural network connections, reducing computational requirements while maintaining accuracy. This technique cuts energy consumption without sacrificing performance.
Data centre optimisation offers immediate efficiency opportunities. Cooling systems account for up to 40% of energy use and selecting effective systems can improve efficiency by 30%. Philippine references work at Dassault Systèmes using virtual twins on the 3DEXPERIENCE platform to enable sustainable operations through partner collaboration.
Modelling scenarios perform trade-off analyses between technology configurations, helping teams optimise setups and accommodate future technologies. Dassault Systèmes collaborates with QCT to simulate data centre heat and airflow patterns for building effective air conditioning systems.
The company's solutions support Bouygues Construction, the French building company, in modular construction processes, while helping Olivier Naar design modular nuclear reactors.
"I don't see isolated projects," Philippine says, "I see interconnected, mutually enhancing nodes within a wider value network."
Dassault Systèmes participates in Coalition for Sustainable AI
The company participates in network effects through initiatives like the Coalition for Sustainable AI. Philippine emphasises that technical fixes alone cannot address sustainability challenges, noting that processing power value depends on application purposes, regardless of data centre efficiency.
"I see how those same techniques can help build modular data centers. I see how we can power them with electricity that is low-carbon and convenient," she says.
Philippine emphasises that broader thinking beyond technical solutions remains essential. The sustainability challenge extends beyond infrastructure improvements to encompass fundamental approaches to AI development and deployment.
"AI will be what we make of it," she says. "Circular thinking needs to be embedded not just in our processes and products, but also in our methods and in the way we think about the world."
The data centre industry faces mounting pressure to balance AI's transformative potential against environmental constraints. While technical solutions offer pathways to improved efficiency, the scale of projected energy demand requires comprehensive approaches spanning technology, policy and business practices.
"We have what we need to make the infrastructure and ecosystems that power AI start working more effectively today. What we make of it? Well, that's up to us."
