Sustainable Digital Infrastructure Accord: Advancing AI Infrastructure in Asia-Pacific

Contents

Executive Summary

This panel discussion examines the urgent need for sustainable data center infrastructure across Asia-Pacific as AI adoption accelerates dramatically. The session introduces the Sustainable Digital Infrastructure Accord (SDIA)—a collaborative, regional framework launching in spring 2024 to establish voluntary sustainability targets for data centers, balancing India's projected 6+ gigawatt capacity growth by 2030 with water scarcity and renewable energy integration challenges.

Key Takeaways

The SDIA Is an Industry-Led Initiative, Not a Regulatory Burden: Unlike the EU's top-down approach, Asia-Pacific's diversity necessitates voluntary, collaborative standard-setting with four measurable pillars—energy efficiency (PUE targets), clean energy coverage, water management, and circular economy practices. Industry is moving ahead of policy.
Sustainability Trade-Offs Are Real, Context-Dependent, and Technical: There is no universal best practice. Water-cooled data centers minimize power use but strain scarce aquifers; air-cooled systems use more power but conserve local water. Policy frameworks must enable evidence-based, region-specific design choices rather than imposing uniform mandates.
India Is Well-Positioned But Needs Coordinated Execution: India's renewable energy capacity (220 GW, targeting 500 GW by 2030), ambitious AI ambitions, and strong government backing create opportunity—but fragmented state policies, slow grid interconnection, and ad hoc clustering undermine efficiency. Planned infrastructure zones and uniform green energy norms are critical.
The Investment Window Is Open Now (But Time-Bound): Capital allocation for data center and renewable energy buildout is flowing today; investors expect multi-decade certainty in return. Delays in policy clarity or grid permitting risk missing this critical window—the stakes are estimated at $90 billion+ for India alone and hundreds of billions globally.
AI Will Get More Efficient, Not Less: Current AI is "the most inefficient it's ever going to be." Continued innovation in chip design, infrastructure optimization, and operational efficiency means sustainability challenges are solvable—but only with intentional investment by industry, government, and policymakers working in alignment.

Key Topics Covered

Sustainable Digital Infrastructure Accord (SDIA): Regional baseline initiative with four pillars (energy efficiency, clean energy, water management, circular economy)
AI Infrastructure Demand in Asia-Pacific: Exponential growth trajectory, India's role as emerging data center hub
Energy and Power Challenges: India's renewable energy targets (500 GW by 2030) and grid integration needs
Water Stress and Resource Management: Competition between data center cooling and local water availability in water-scarce regions
Regional Policy Fragmentation: Risk of inconsistent standards across different countries/states without coordinated frameworks
Industry Leadership on Sustainability: Data center operators' proactive innovation vs. compliance-driven approaches
Technological Efficiency Gains: AI model efficiency improvements, PUE metrics, cooling innovations
Infrastructure Investment Timelines: Multi-year capital deployment windows and long-term policy certainty requirements
Hyperscaler Commitments: Google and other cloud providers' renewable energy and water replenishment targets
Government Enablement: Tax incentives, infrastructure status, state-level data center policies

Key Points & Insights

AI and Sustainability Are Inseparable: Energy use for the digital ecosystem is projected to reach 8-10% (possibly higher) of global consumption. Ms. Sundar Rajan frames sustainability as foundational to AI's viability—without it, AI becomes "irrelevant and meaningless" given existential planetary risks.
India's Specific Vulnerability: With 18% of the world's population living on 4% of freshwater resources, a single hyperscale facility can consume ~25 million liters of water annually per megawatt of IT load. Data centers could triple or quadruple India's electricity consumption by 2030, making water and energy trade-offs acute.
Rapid Efficiency Gains in AI: Google's Gemini demonstrated 33x efficiency improvement per prompt over 12 months; Google data centers' output per unit electricity increased sixfold over 5 years. This suggests AI workloads will become increasingly efficient as technology matures—the opposite of the infrastructure problem compounding.
Technology-Driven Sustainability Maturity: The industry has shifted from compliance-driven sustainability (tracking PUE) to design-phase integration of sustainability goals. Modern air-cooled chiller systems with closed-loop water cycles demonstrate negligible water evaporation while maintaining power efficiency, offering context-specific solutions.
One-Size-Fits-All Policies Fail in Diverse Climates: Asia-Pacific's heterogeneity (tropical Singapore/Malaysia vs. cold Japan vs. arid Australia) demands flexible frameworks. Remote, water-scarce locations may require air-cooled designs (higher power use) vs. water-cooled alternatives (higher water stress), requiring evidence-based trade-off analysis.
Regional Coordination Prevents Fragmentation: Without the SDIA, each country/state could impose bespoke sustainability checklists, fragmenting efforts. India's state governments already have divergent green power norms—uniformity would improve consistency and reduce compliance burden.
Hyperscaler Commitments Drive Standards: Google's 100% renewable energy matching since 2017, target of 100% carbon-free energy by early 2030s, and 120% freshwater replenishment by 2030 set industry benchmarks. Customer demand (enterprises, consumers) for responsible AI operations is a key driver.
Infrastructure Zones Accelerate Deployment: Ad hoc clustering (e.g., Ambattur in Chennai, Salt Lake in Kolkata) is less efficient than planned digital infrastructure zones with pre-built power, connectivity, and land. State-level coordination could halve time-to-operation for capacity buildout.
Last-Mile Grid Interconnection Is Bottleneck: Despite ample renewable generation capacity coming online, transmission infrastructure permitting can take 10 years vs. 24-36 months for renewable zones. This misalignment breaks the economics of sustainable infrastructure investment.
Policy Certainty and Speed Are Preconditions: Long-term investment in data center infrastructure (20-30 year horizons) requires clarity on green energy schemes, taxation, and efficiency targets. Simultaneously, policymakers must accelerate permitting and grid access timelines to match market velocity.

Notable Quotes or Statements

Ms. Sundar Rajan (Broadband India Forum): "Even AI must take into account the fact that first and foremost we need to ensure the sustainability of the planet. Otherwise, AI would become irrelevant and meaningless if the existential threat that this can pose is not addressed."
Bimal Candel (ST Teledia Global Data Centers India): "AI and sustainability they go hand in hand. They are two sides of the same coin... Sustainability is not only influencing and impacting how we build, where we build, what we build. Sustainability is at the core of the data center design and the delivery and of course the operations as well."
Alexander Smith (Google, Global Infrastructure and Energy): "Artificial intelligence now is the most inefficient that it's ever going to be and there's significant upside... Gemini... demonstrated that it's basically now 33 times more efficient per prompt than it was at the beginning of that 12 month period."
Alexander Smith: "Doing AI the right way... if it is done the right way, then there's no reason that it cannot be sustainable. There's no reason that it doesn't need to result in moms and dads or startups paying more for their electricity bills."
Sukrit Anand (Digital Realty): "Power has emerged as a protagonist in this AI growth story... The responsibility is on the industry, the operators, the users, the hyperscalers, the power providers to actually integrate sustainability and energy into the base design itself."
David Gross (APDCA, opening remarks): "We regard the governor's mechanism as something where governments and industry can formally discuss these issues and learn around these issues... [The SDIA] will provide a real framework to discuss this and a real baseline to measure this against."

Speakers & Organizations Mentioned

Entity	Role/Affiliation
David Gross	APDCA (Asia-Pacific Data Center Association) representative; moderator
Ms. Rena Sundar Rajan	Chairperson, Broadband India Forum
Bimal Candel	CEO, ST Teledia Global Data Centers India
Alexander Smith	Principal, Global Infrastructure and Energy, Google
Sukrit Anand	Vice President, Investments and Strategy, Digital Realty
Broadband India Forum (BIF)	Non-partisan technology forum and think tank (partner organization)
APDCA	10-member association of colocation data center operators; ~250 data centers in APAC (42 completed in India, 15 under construction)
Ministry of Electronics and Information Technology (Meity), Government of India	Co-organizer
Google	Major hyperscaler; announced gigawatt+ facility investment with Shaka partner; 18+ megawatts renewable energy added to Indian grid
Indian Government (State Level)	10 state governments with data center policies; budgets included infrastructure status (2022) and 22-year tax holiday for foreign capacity users (2026 budget)

Technical Concepts & Resources

Key Metrics & Targets

PUE (Power Usage Effectiveness): Energy efficiency metric for data centers; subject to annual reconsideration in SDIA framework
Carbon-Free Energy: Google targeting 100% carbon-free energy operations by early 2030s (currently at ~2/3 progress)
Water Replenishment: Google's target of 120% freshwater replenishment by 2030 (returning more water to local watersheds than consumed)
Energy Consumption Projections: Digital ecosystem estimated at 8-10% of global energy use; data centers could triple/quadruple India's electricity consumption by 2030
Capacity Projections: India's data center capacity grew 4x in 5 years (400 MW in 2020 → 1.7 GW in 2025); expected to reach 6+ GW by 2030-2032

Technologies & Approaches

Air-Cooled Chiller Systems: Closed-loop water systems with minimal evaporation; higher power use but critical in water-scarce regions
Water-Cooled Data Centers: Lower power use but significant water consumption (~25 million liters/year per megawatt IT load in some cases)
Renewable Energy Integration: Solar, wind, hydro, nuclear; corporate power purchase agreements (PPAs) enabling private renewable procurement
Circular Economy Practices: Waste heat recovery for new projects; embodied carbon accounting; local sourcing in supply chains
AI Models Referenced: Google Gemini (33x efficiency improvement in 12 months; used as example of ongoing AI efficiency gains)

Policy Frameworks & Initiatives

Sustainable Digital Infrastructure Accord (SDIA): Voluntary, regional framework launching spring 2024 (March/April); modeled on EU's Climate Neutral Data Center Pact but adapted for Asia-Pacific diversity
SDIA Four Pillars:
1. Energy Efficiency (PUE targets, annually reconsidered)
2. Clean Energy Coverage (renewable + carbon-free energy procurement)
3. Water Management (local stress assessment, context-specific targets)
4. Circular Economy (waste heat management, embodied carbon, local supply chains)
India's Renewable Energy Targets: 220 GW current capacity (non-fossil + renewable); 500 GW target by 2030; 61% of energy from renewables by 2030; net-zero by 2030
Green Power Norms: India's states currently have divergent banking/solar power norms; uniformity flagged as critical for consistency
Digital Infrastructure Zones: Proposed state-level development with pre-built power, connectivity, and land to accelerate data center deployment
Corporate Power Purchase Agreements (PPAs): Market mechanism enabling hyperscalers to directly procure renewable energy; variable availability across APAC jurisdictions

Sustainability Trade-Offs Highlighted

Power vs. Water: Water-cooled systems optimize power efficiency but stress local aquifers; air-cooled systems use more power but preserve local water (context-dependent optimal choice)
Clustering vs. Distributed Deployment: Geographic concentration (e.g., Ambattur) reduces costs but may strain local infrastructure; distributed zones spread benefits but increase transmission complexity
Grid Permitting vs. Renewable Buildout: Renewable energy zones can come online in 24-36 months; transmission infrastructure permitting can take 10 years (bottleneck identified)

Context & Significance

This session occurred during India's AI Summit, reflecting India's emergence as a critical node in Asia-Pacific's AI infrastructure buildout. The discussion is timely given:

Hyperscaler announcements of major India investments (Google, others)
Projected tripling/quadrupling of India's data center electricity demand by 2030
Acute water stress in regions where data centers are clustering (e.g., Greater Noida)
Divergent state-level policies creating compliance fragmentation
Global AI adoption acceleration creating urgent infrastructure demands

The SDIA represents an attempt to establish regional coordination before fragmentation hardens—a proactive industry and policy initiative rather than reactive compliance.