The session titled Strengthening Data and AI Collaboratives for Economic Growth and Social Good, held during the India AI Impact Summit at Bharat Mandapam, convened international policymakers, researchers, development experts, and civil society leaders to examine how trusted data ecosystems can power responsible AI adoption while driving inclusive economic growth and social progress.

As governments and institutions increasingly rely on data driven systems to support governance, healthcare, climate action, and development planning, the session highlighted the importance of accessible, interoperable, and responsibly governed datasets. Speakers emphasised that effective AI deployment depends not only on technological advancement, but on collaboration, transparency, and shared governance frameworks that enable secure and ethical data exchange.

Session Context

The panel addressed one of the defining challenges of AI adoption globally: building trusted data infrastructures capable of supporting evidence based decision making at scale. Participants discussed how Data and AI Collaboratives can unlock siloed data, enable secure sharing across institutions, and establish governance models that balance innovation with accountability.

“Trusted data ecosystems are the foundation for evidence based decision making and responsible AI deployment.”
— Session Perspective

The conversation reinforced the view that AI driven progress requires collective action across governments, academia, development organisations, and industry to ensure outcomes remain inclusive and equitable.

Speakers And Participants

The session featured a diverse set of global voices representing multilateral institutions, policy bodies, academia, and technology ecosystems:

• Alexandru Oprunenco, United Nations Development Programme (UNDP)

• Ambassador Harry Verweij, Ministry of Foreign Affairs, The Hague, Netherlands

• Anna Tumcadóttir, Creative Commons

• Ariane Hildebrandt, Federal Ministry for Economic Cooperation and Development (BMZ)

• Dr Agnes Kiragga, African Population Health Research Council

• Dr Cecilia Celeste Danesi, Artificial Intelligence and Civil Law, School of Law (UBA)

• Dr Hwirin Kim, World Meteorological Organisation

• Fred Werner, International Telecommunication Union (ITU) – Keynote Address

• Gaurav Godhwani, CivicDataLab

• Kathleen Victoir, Pasteur Network

• Nasubo Ongoma, Qhala

The panel reflected a strong global consensus that collaborative data governance is becoming essential for scaling ethical and impactful AI systems.

Keynote Perspective

Delivering the keynote address, Fred Werner from the International Telecommunication Union highlighted the growing importance of global standards and interoperability frameworks as nations expand their AI ecosystems.

“AI cannot create value without trusted data foundations. Interoperability and governance must evolve alongside innovation.”
— Fred Werner, ITU

His remarks positioned data governance as a strategic enabler of innovation, international cooperation, and long term digital resilience.

Speaker Perspectives

Alexandru Oprunenco, UNDP

“Public value from AI depends on whether data ecosystems are inclusive, accessible, and designed for societal benefit.”

He emphasised that collaborative data frameworks can help governments strengthen public services and improve policy outcomes through evidence based decision making.

Anna Tumcadóttir, Creative Commons

“Open and responsibly shared knowledge strengthens innovation ecosystems and helps AI development remain transparent and equitable.”

Her perspective focused on balancing openness with safeguards to support innovation while maintaining trust and accountability.

Dr Cecilia Celeste Danesi, School Of Law (UBA)

“As AI systems shape decisions, legal frameworks must evolve to protect rights while enabling responsible innovation.”

She highlighted the importance of aligning data sharing practices with evolving legal and ethical standards.

Dr Hwirin Kim, World Meteorological Organisation

“Cross border data collaboration is critical for addressing global challenges such as climate resilience and disaster preparedness.”

Her comments reinforced the need for international cooperation when using AI to address shared global risks.

Gaurav Godhwani, CivicDataLab

“Data collaboratives are not only technical initiatives. They are governance models that bring together public institutions, communities, and researchers.”

He emphasised the role of civic participation and transparent frameworks in building trustworthy AI ecosystems.

Key Themes Discussed

Building Trusted Data Ecosystems

Speakers stressed that public trust requires clear governance structures, accountability mechanisms, and transparent data stewardship models.

Unlocking Siloed Data

Panellists discussed how secure and structured collaboration can help institutions share data responsibly to improve outcomes across healthcare, climate, and governance.

Inclusive Innovation

Ensuring that AI solutions serve diverse populations and emerging markets emerged as a central discussion point.

Collaborative Governance Models

The session highlighted decentralised models where governments, development agencies, academia, and civil society collectively shape data governance.

“Data collaboratives are becoming essential infrastructure for inclusive AI growth and long term economic resilience.”
— Panel Insight

Economic Growth And Social Good

Participants agreed that strong data collaboration frameworks can accelerate:

• improved public service delivery

• climate and environmental research

• population health insights

• inclusive entrepreneurship and digital innovation

The discussion reinforced that economic growth enabled by AI must remain aligned with ethical standards and equitable data access to ensure broad societal benefit.

Knowledge Partner Contribution

The session was supported by CivicDataLab, whose work in advancing open data practices and evidence based governance closely aligned with the panel’s emphasis on collaboration and transparency.

Strategic Relevance

The panel positioned Data and AI Collaboratives as a crucial next step in global AI maturity. Rather than viewing data purely as a technical asset, speakers framed it as a shared resource that requires collective governance to unlock meaningful public value.

The session also reflected the broader India AI Impact Summit theme that scaling AI responsibly depends on collaboration across borders, sectors, and disciplines.

Looking Ahead

As AI continues to reshape public systems and governance models, participants concluded that the future of AI will depend on trusted data ecosystems that prioritise transparency, inclusion, and accountability. Continued global collaboration will be essential to build interoperable frameworks capable of supporting ethical innovation while delivering measurable economic and social outcomes.