From the promise of enterprise AI to proof to execution and beyond
Global technology and policy leaders at AI Impact Summit 2026 discussed how trust, governance and collaboration will determine whether AI can deliver sustainable value at scale.
At the AI Impact Summit 2026, held at Bharat Mandapam in New Delhi, a panel of global technology and policy leaders came together to examine one of the defining questions of this AI-first decade: how can enterprises and societies build trust in artificial intelligence while still enabling innovation at scale?
Moderated by Mridu Bhandari of Network18, with Wipro as Knowledge Partner and in association with CNBC-TV18, the discussion framed the challenge through a broader lens of ‘People, Planet and Progress’.
From a public policy standpoint, Paul Hubbard, First Assistant Secretary for AI Delivery and Enablement at the Australian Government’s Department of Finance, insisted that the conversation around AI must begin not with technology but with public value. “I bring an economics lens to AI,” he said. “For me, it is not about technological adoption alone. It is about what generates public value and public welfare.”
Hubbard also cautioned against framing the debate as a trade-off between innovation and trust, saying, “Trust is the foundation that allows innovation to happen. Governments must start with the problem they are trying to solve and meet citizens where they are in their understanding of AI.”
From an infrastructure perspective, Erik Ekudden, Chief Technology Officer at Ericsson, highlighted how connectivity networks are evolving from passive carriers of data into active platforms that enable AI experiences. “Networks are becoming the fabric we all depend on,” he noted. “As AI moves from centralised training to being distributed inference across devices and the network edge, the network itself becomes a host for those experiences. But the fundamentals remain the same: networks must be secure and trusted.”
For financial institutions, where trust is fundamental to the business itself, Divyesh Vithlani, Group Chief Technology and Transformation Officer at First Abu Dhabi Bank, emphasised that responsible AI adoption must be embedded into the organisation’s operating architecture. “In banking, trust is not philosophical; it is existential,” he said. “Our approach entails a platform-first strategy, embedding ethical AI, data governance and model governance into the foundation. That allows the organisation to scale AI safely while maintaining the risk discipline that banking demands.”
And finally, from an enterprise transformation perspective, Hari Shetty, Chief Strategist and Technology Officer at Wipro, argued that the conversation around AI must move beyond experimentation. “AI is no longer about pilots, but rather, it is about delivering value,” he said. “Don’t start with the model. Start with the problem. Only when solutions work consistently in real enterprise environments do they move from promise to proof.”
Over the course of the session, the discussion touched on a wide range of related themes: from accountability in enterprises and society to the evolving relationship between humans and intelligent systems. Panellists also examined how organisations are measuring AI’s impact, pointing to metrics such as operational efficiency, fraud prevention, customer trust and capital efficiency as emerging indicators of real value creation.
The conversation at the summit reflected a shared conclusion that as the AI era progresses and gains momentum, technology alone will not define the next decade of AI. Trust, governance and collaboration across governments, enterprises and technology ecosystems will ultimately determine whether AI delivers on its promise for society.
Moderated by Mridu Bhandari of Network18, with Wipro as Knowledge Partner and in association with CNBC-TV18, the discussion framed the challenge through a broader lens of ‘People, Planet and Progress’.
To translate these principles into action, the conversation focused on what were described as the ‘seven chakras’ of aligned global cooperation: human capital, inclusion, trust, resilience, science, resources and social good - pillars that can transform AI ambition into accountability.
From a public policy standpoint, Paul Hubbard, First Assistant Secretary for AI Delivery and Enablement at the Australian Government’s Department of Finance, insisted that the conversation around AI must begin not with technology but with public value. “I bring an economics lens to AI,” he said. “For me, it is not about technological adoption alone. It is about what generates public value and public welfare.”
Hubbard also cautioned against framing the debate as a trade-off between innovation and trust, saying, “Trust is the foundation that allows innovation to happen. Governments must start with the problem they are trying to solve and meet citizens where they are in their understanding of AI.”
From an infrastructure perspective, Erik Ekudden, Chief Technology Officer at Ericsson, highlighted how connectivity networks are evolving from passive carriers of data into active platforms that enable AI experiences. “Networks are becoming the fabric we all depend on,” he noted. “As AI moves from centralised training to being distributed inference across devices and the network edge, the network itself becomes a host for those experiences. But the fundamentals remain the same: networks must be secure and trusted.”
For financial institutions, where trust is fundamental to the business itself, Divyesh Vithlani, Group Chief Technology and Transformation Officer at First Abu Dhabi Bank, emphasised that responsible AI adoption must be embedded into the organisation’s operating architecture. “In banking, trust is not philosophical; it is existential,” he said. “Our approach entails a platform-first strategy, embedding ethical AI, data governance and model governance into the foundation. That allows the organisation to scale AI safely while maintaining the risk discipline that banking demands.”
And finally, from an enterprise transformation perspective, Hari Shetty, Chief Strategist and Technology Officer at Wipro, argued that the conversation around AI must move beyond experimentation. “AI is no longer about pilots, but rather, it is about delivering value,” he said. “Don’t start with the model. Start with the problem. Only when solutions work consistently in real enterprise environments do they move from promise to proof.”
Over the course of the session, the discussion touched on a wide range of related themes: from accountability in enterprises and society to the evolving relationship between humans and intelligent systems. Panellists also examined how organisations are measuring AI’s impact, pointing to metrics such as operational efficiency, fraud prevention, customer trust and capital efficiency as emerging indicators of real value creation.
The conversation at the summit reflected a shared conclusion that as the AI era progresses and gains momentum, technology alone will not define the next decade of AI. Trust, governance and collaboration across governments, enterprises and technology ecosystems will ultimately determine whether AI delivers on its promise for society.
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