Unlocking EU–India Opportunities for the Twin Transition

Contents

Executive Summary

This roundtable discussion at the AI Impact Summit explores EU-India collaboration opportunities around the "twin transition"—simultaneous advancement in artificial intelligence and sustainability. Speakers from industry (Airbus, SAP, Schneider Electric, Ericsson, Merck) and the EU Commission emphasize that AI must be human-centric, ethically grounded, and coupled with measurable sustainability outcomes. The discussion highlights the strategic importance of India's scale, talent, and digital infrastructure as a foundation for creating globally interoperable standards and trusted, low-carbon AI deployment.

Key Takeaways

AI adoption at scale demands simultaneous investment in energy infrastructure. The next decade's competitive advantage goes to nations/companies that solve power delivery, cooling, and grid digitization for AI workloads—not just AI algorithms.
EU-India partnership creates a "trust-based transition." Digital interoperability (e-signatures, wallets), ethical AI standards, and regulatory alignment enable faster, lower-risk adoption of AI and sustainability solutions globally.
India's dual strength—massive engineering talent + infrastructure pressure—makes it the optimal testing ground for responsible, sustainable AI. Solutions proven to work in India's scale and complexity conditions are likely to succeed anywhere.
Industrial AI (drug discovery, manufacturing, agriculture) delivers faster ROI and impact than consumer AI. Focus resources on sector-specific, measurable outcomes rather than generic AI platforms.
Trust is non-negotiable and design-stage critical. Ethics, cybersecurity, and transparency built in from the beginning—not retrofit—determine whether AI gains customer/citizen acceptance and delivers sustainable competitive advantage.

Key Topics Covered

EU-India Strategic Partnership & Trade
- Recent EU-India Free Trade Agreement (FTA) negotiations concluded
- Digital interoperability and e-signature mutual recognition initiatives
- European Business Wallet and Aadhaar/DigiLocker interoperability projects
AI as Human-Centric Technology
- AI as an enabler of human capability, not replacement
- Ethical AI design and responsible innovation frameworks
- Role of trust and digital ethics in AI adoption
Energy & Infrastructure Challenges
- AI data centers consume unprecedented energy (compared to continental scale)
- Shift from "data centers" to "AI factories" requiring 1 MW+ power densities
- Need for smart grid digitization and energy intelligence
Sector-Specific AI Applications
- Drug discovery and autonomous labs (bioconvergence)
- Predictive maintenance in aviation and logistics optimization
- 5G-enabled precision surgery, smart manufacturing, autonomous robotics
- Agricultural AI and ocean cleanup systems
Sustainability & Net-Zero Goals
- Green ledgers and carbon accounting via AI
- Sustainable aviation fuel production from agricultural waste (India potential)
- Energy efficiency through intelligent home and industrial systems
- Reducing AI model energy consumption by 90–95% through optimization
Regulatory & Standards Alignment
- Global regulatory fragmentation in AI
- Need for unified standards and mutual recognition frameworks
- Balance between innovation, security, national sovereignty, and ethics
India's Unique Position
- Large engineering talent pool in power, automation, and software
- 5G infrastructure foundation (Reliance Jio, Airtel)
- Digital stack (UPI, Aadhaar, DigiLocker) as platform for innovation
- High pressure on infrastructure as testing ground for global solutions

Key Points & Insights

AI is fundamentally an infrastructure challenge, not just an algorithm problem. Energy consumption and cooling requirements for AI "factories" are driving architectural changes (800V DC electrical systems, 1 MW+ rack densities) that require completely new power infrastructure planning.
The "twin transition" is inseparable—AI and sustainability must be designed together from inception, not bolted on afterward. Green ledgers, sustainable procurement, and carbon accounting must be integrated into AI-driven systems from the start.
Trust and ethics are competitive advantages, not compliance burdens. Companies embedding digital ethics frameworks, cybersecurity, and transparency into products from design phase build customer confidence and differentiate in markets.
India's scale is both a testing ground and solution factory. With 1.4 billion people, infrastructure pressure, and a massive pool of software/engineering talent, solutions proven in India often work globally. Conversely, India offers unparalleled volume for piloting innovations.
Digital interoperability between EU and India is an immediate, achievable deliverable. E-signatures, digital wallets (Aadhaar/European Citizens Wallet), and identity systems can achieve mutual recognition within short timelines, unlocking business-to-government and business-to-business efficiency.
Industrial AI, not large language models, will drive the largest economic impact. Use cases in drug discovery (Synthia, Edison models), smart manufacturing (digital twins), precision agriculture, and supply chain optimization are already delivering measurable ROI and reducing costs/time-to-market.
Energy intelligence solves the AI-sustainability paradox. AI algorithms can optimize power consumption (20–30% household savings, 90–95% AI model optimization), making AI part of the decarbonization solution, not just the problem.
5G and edge AI are foundational for India's next innovation wave. Mature 5G networks (Modi's 100 5G initiative) combined with AI-powered edge devices unlock precision use cases (telesurgery, smart ports, autonomous factories) that give early-mover nations competitive advantage through decade's end.
Regulatory fragmentation is slowing deployment but reflecting legitimate concerns (national security, cultural values). A pragmatic path forward balances openness with security through trusted data layers (Syntropy model) where users retain IP/cybersecurity control.
Supply chain resilience requires coordinated EU-India collaboration. Bilateral benchmarking of standards, shared R&D infrastructure (supercomputing partnerships), and co-creation of sector-specific solutions (e.g., sustainable aviation fuel) create mutual strategic advantage.

Notable Quotes or Statements

Jürgen Westermeyer (Airbus): "AI is not a replacement for expertise. Rather, it is a responsible and ethical enabler designed to augment human capability." / "Sustainability must be embedded into its design and governance from the outset, not threaded in as an afterthought."
Roberto Viola (EU Commission DG CONNECT): "Europe has launched a project which brings together all what we do in terms of identity, signature for companies, time stamping... the European business wallet... with a specific provision that says this can be source of mutual recognition [with India]."
Olivier Blum (Schneider Electric): "AI needs compute, and the biggest constraint to get compute is the energy." / "AI needs energy, but energy needs intelligence." / "When you crack the code in India, you crack the code for the planet."
Dr. Klaus Neumann (SAP): "AI also uses a lot of energy... the usage of AI data centers in the United States in four years is the same as the usage of electricity for the whole African continent." / "We can reduce energy consumption also in AI by up to 90–95% by using the right technology."
Dr. Christian Wicker (Merck Life Science): "The biggest impact will come from industrial AI [not LLMs]." / "2026 is the first year that we'll have AI-driven drugs in clinical trials." / "Having ethics by design right in the beginning, make it a little bit independent of regulation and country."
Dr. Lovneesh Chanana (SAP, wrap-up): "We have the interwoven digital and sustainability agenda... BRILLIANT [bilateral benchmarking, responsible resilience, innovating impact, leveraging R&D, low-carbon ledgers, inclusive interoperability, accelerating action, net-zero networks, trust-based transition]."

Speakers & Organizations Mentioned

Role/Title	Name	Organization
Moderator & Secretary-General	Sonia Parashar	FEB (Federation of European Businesses in India)
President & Managing Director (India/South Asia)	Jürgen Westermeyer	Airbus, FEB President
Director-General, DG CONNECT	Roberto Viola	EU Commission
Global Head, SAP Labs Network	Dr. Klaus Neumann	SAP
Global CEO	Olivier Blum	Schneider Electric
Head of Advanced Technology & CTO	Dr. Magnus Everbring	Ericsson Group
Head, Global Digital Policy, Science & Tech	Christian Wicker	Merck Life Science
CEO (Audience Q&A)	Pramod Kaushik	Hexagon
Panelist (Audience Q&A)	Ajit Mankotia	NXP
Wrap-up / Chair, Digital Economy Committee	Dr. Lovneesh Chanana	SAP
Vice President, attendee	Deepak Sharma	Schneider Electric

Additional institutions/initiatives referenced:

Airbus, Merck Life Science, SAP, Schneider Electric, Ericsson, NXP
Ministry of Electronics & IT (India), Reliance Jio, Airtel
Palantir (Syntropy JV with Merck)
Equinix, Lenovo, NVIDIA
OZO (ocean cleanup startup)
Hyundai Manufacturing, National University Hospital Singapore
Ray-Ban / Meta

Technical Concepts & Resources

AI Models & Platforms

Synthia — Drug discovery model for molecule design (Merck)
Edison — AI model for drug development (Merck)
Skywise Platform — Predictive maintenance for aviation; saves global airline industry $200M+ annually (Airbus)
Syntropy — Joint venture (Merck + Palantir) for trusted data sharing layer with IP/cybersecurity control
Digital Twin — Virtual replica of physical systems for manufacturing, pre-surgery planning, optimization

Infrastructure & Technology

5G Networks — Foundational layer for edge AI, telemedicine, autonomous systems; India's Modi 100 5G initiative cited
Edge AI — AI inference at device/local level (NXP focus); reduces latency, power, and cloud dependency
XR (Extended Reality) + 5G — Telesurgery, precision manufacturing visualization, real-time translation
Smart Manufacturing & RPA — Robotic Process Automation for both large enterprises (humanoid robots) and MSMEs (AI-driven CAM programming)
Humanoid Robotic Systems — AI-aware, learning robots for hazardous/ergonomically demanding tasks
800V DC Electrical Infrastructure — Next-generation power distribution for AI data centers (3–5 years out)

Digital Identity & Interoperability

Aadhaar — India's digital ID system
DigiLocker — India's digital document wallet
European Citizens Wallet — EU's universal digital identity in rollout (2024)
European Business Wallet — Unified digital trust document framework (signature, timestamping, identity)
UPI (Unified Payments Interface) — India's digital transaction platform
e-Signature Mutual Recognition — EU-India bilateral agreement enabling cross-border digital document recognition

Energy & Sustainability

Green Ledger — AI-driven carbon accounting and ESG reporting (SAP)
Energy Intelligence / Smart Grid Digitization — AI-optimized demand-side management for 20–30% household savings
Sustainable Aviation Fuel (SAF) — India agricultural waste-to-fuel opportunity; Airbus–Gati Shakti research partnership
Predictive Maintenance AI — Reduces downtime, extends equipment life; major aviation/manufacturing ROI driver
AI Model Optimization — Can reduce energy consumption 90–95% through architecture/algorithm tuning

Data & Ethics Frameworks

Code of Digital Ethics — Merck compliance framework for all AI products/services
Digital Ethics Advisory Panel — Multi-stakeholder governance (civil society, academia, industry)
Trusted Data Layer — IP-controlled, cyber-secured data sharing without centralized ownership (Syntropy model)

Regulatory / Standards

EU-India FTA (Free Trade Agreement) — Recently concluded; trade & technology council active
Trade & Technology Council (EU-India) — Bilateral mechanism for standards alignment, digital simplification, supply chain resilience
Global AI Regulatory Fragmentation — Each nation defining own AI rules; speaker argued for more global standards alignment without compromising security/values

Policy & Business Implications

For policymakers:

Digital interoperability frameworks (wallets, e-signatures) can be negotiated and deployed within months, unlocking trade efficiency.
Energy infrastructure planning must precede (or parallel) AI investment; grid digitization and renewable energy are prerequisites.
Regulatory alignment on AI (ethics, transparency, cybersecurity) builds confidence and reduces deployment friction.

For enterprises:

Industrial AI use cases (drug discovery, predictive maintenance, smart manufacturing) outperform generalist AI in ROI and measurable impact.
Ethics and security must be designed in from inception; retrofit approaches fail on customer trust and regulatory compliance.
Partnerships with India (talent, scale testing, manufacturing) and EU (standards, regulatory clarity) are complementary and urgent.

For India specifically:

Position as the "AI-sustainability proving ground" for global corporations; scale + talent + infrastructure pressure = unmatched testing environment.
Leverage Aadhaar/UPI/5G/DigiLocker stack as foundation for AI-native services export and IP creation.
Invest in industrial AI R&D (biotech, manufacturing, agriculture) where India has existing strengths; avoid competing in consumer LLM space.