India AI summit targets data control and skills gap

Global technology executives are urging governments and companies to prioritise data control, workforce skills and organisational design as India's AI Impact Summit seeks agreement on a shared roadmap for artificial intelligence governance.

The summit brings policymakers, industry leaders and experts together in India amid intensifying international debate over how to regulate AI and align national approaches.

Commentators say the initiative highlights both the momentum behind AI deployment and the gaps that remain in oversight, accountability and long-term structural change within organisations.

Data control

Levent Ergin, chief strategist for agentic AI, regulatory compliance and sustainability at Informatica (Salesforce), said the renewed focus on governance comes as countries compete to scale AI systems and infrastructure.

"With global consensus on AI governance still fragmented, the push at India's AI Impact Summit to shape a shared roadmap is timely. As countries accelerate AI capability, the real differentiator will not be model size but control. The ability to know where data comes from, how it is used and how decisions are monitored at scale is crucial.

"Our research shows 65% of organisations report high employee trust in AI data, yet 71% admit their workforce needs significant upskilling to use it responsibly. That gap between confidence and capability grows as AI is embedded into public services and critical sectors. AI systems are only as effective as the context they are built on, making trusted data, transparency and oversight essential to scaling AI safely," Ergin said.

His comments reflect a wider shift among regulators and business leaders, who increasingly view data lineage, explainability and traceability as central requirements in AI policy discussions.

Governments are scrutinising how organisations obtain, process and share data. Companies face pressure from regulators, customers and employees to show that AI systems rely on accurate, governed data and that decisions can be audited.

Skills gap

The figures Ergin cited point to a disconnect between internal confidence in AI-generated outputs and the skills needed to interpret or challenge them responsibly.

Workforces in both the private and public sectors are grappling with rapid deployment of tools that automate decisions or shape frontline services. Staff training, data literacy and understanding of AI risks have become recurring themes in board discussions and regulatory guidance.

Executives and policymakers at the summit are expected to examine how AI is reshaping labour markets and job design, and what education and training systems need to keep pace with adoption across sectors such as healthcare, finance, manufacturing and government services.

Structural change

Nick Reed, chief strategy officer at Bizzdesign, said the summit signals a shift from AI ambition to questions about long-term organisational architecture and governance.

"With the India AI Impact Summit convening world leaders to move AI from ambition to accountable impact, the real test now lies in translating AI vision into structural change. AI has the potential to reshape productivity, enable new forms of work, and unlock meaningful growth, but realising that promise requires moving beyond isolated experimentation to systemic impact.

"That shift is less about simply deploying AI models and more about redesigning how organisations operate. Sustainable value emerges when AI is woven into the architecture of the enterprise through purposeful operating model design across business processes, data, people, systems and governance. Structural coherence helps organisations see how intelligence influences decisions, how dependencies cascade and where accountability resides, which is what makes effective governance possible at scale.

"As regulatory frameworks like the EU AI Act raise expectations around traceability and oversight, that governance capability becomes a foundation for both compliance and competitive advantage. Organisations with architectural coherence in place are better positioned to adapt, scale AI confidently and convert responsible innovation into a durable strategic advantage," Reed said.

Reed's comments align with a growing pattern in corporate AI strategy: boards and executives are pairing pilots and proofs of concept with broader reviews of operating models, data architecture and risk management.

Analysts expect regulatory initiatives, including the EU AI Act and emerging national regimes in Asia, North America and the Middle East, to reinforce the trend. Companies that invest in consistent governance structures and clear accountability frameworks may find it easier to adapt as rules evolve.

Governance momentum

The India AI Impact Summit comes amid competing national strategies and industry efforts on AI standards. Multilateral bodies, regional blocs and individual governments are developing frameworks addressing safety, ethics, transparency and cross-border data flows.

Industry figures say alignment across these approaches will shape trade, investment and innovation, and influence how quickly organisations in different jurisdictions can scale AI services.

"With global consensus on AI governance still fragmented, the push at India's AI Impact Summit to shape a shared roadmap is timely. As countries accelerate AI capability, the real differentiator will not be model size but control. The ability to know where data comes from, how it is used and how decisions are monitored at scale is crucial."