As AI systems become more autonomous, the conversation is shifting from capability toward something much bigger: trust, legitimacy, identity and participation in digital systems.

In this episode of Shaken Not Burned, Felicia speaks to Erika Maslauskaite, co-founder and CEO of AlongID, about the rapidly evolving world of digital identity, interoperability and cross-border trust infrastructure — and why these questions are becoming increasingly important as AI agents begin acting on behalf of people and organisations.

From digital wallets and verification systems to fraud, privacy and governance, the conversation explores the growing tension between convenience, security and control in an increasingly AI-driven world.

Because beneath the technology itself sits a deeper challenge: how do societies build systems that people can trust, how do institutions adapt to rapid technological change, and what happens when increasingly autonomous technologies collide with fragmented infrastructure and real-world human complexity.

This episode is a grounded and wide-ranging discussion about digital identity, AI infrastructure and the future of participation in an increasingly connected world.

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Generative AI promised to transform how we work, while Agentic AI is beginning to transform how businesses themselves are built.

In this week’s episode of Shaken Not Burned, Felicia Jackson talks to Ethan Ouyang, who is AI ATOMS Spokesperson and responsible for North America Market & Partnerships. ATOMS is the venture building platform developed by DeepWisdom, one of China’s leading artificial intelligence companies. It has been designed as an agentic AI system, helping businesses, particularly small and medium-sized enterprises, integrate AI into their operations.

Unlike traditional generative AI tools, agentic AI systems can take goals, execute tasks, adapt in real time and increasingly function as operational actors inside organisations. From launching products to running marketing campaigns and managing workflows, these systems are beginning to shift AI from a support tool to fundamental business infrastructure. This trend is dramatically raising the stakes in today's AI conversations.

As AI systems move from producing outputs to taking actions, they are not simply improving productivity; they are beginning to reshape entrepreneurship, business formation and operational decision-making itself. Using DeepWisdom’s platform Atom, AI agents are increasingly able to research markets, design products, launch businesses, run marketing and optimise revenue — pushing AI beyond content generation into execution.

But this rapid acceleration of capabilities raises deeper questions. As AI capability expands, governance, ownership, financial models and operational discipline are still evolving. What happens when businesses can be built faster than the systems designed to regulate them? Where does accountability sit when AI agents act on behalf of founders or organisations? And what risks emerge when speed outpaces governance?

This conversation explores:

• The shift from generative AI to agentic AI
• How AI is transforming business creation and operational execution
• Human-in-the-loop decision-making and delegated authority
• Ownership, IP and evolving business model challenges
• Why governance structures may be lagging behind capability
• Sustainability, infrastructure, and the resource demands

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AI is becoming one of those topics where the scale of the claims can make it surprisingly difficult to work out what is actually happening.

We are told it will transform business, unlock extraordinary productivity gains, reshape jobs, and even help solve major global challenges like climate change. At the same time, there are growing concerns about energy demand, governance failures, bias, job losses, and the sheer speed at which these systems are developing.

The dominant narrative tends to swing between utopian optimism and existential fear, often without spending enough time on a more practical question: what actually happens when AI is introduced into real organisations, real systems, and real decision-making? This is the focus of this week’s episode, which is the first in our AI series.

Rather than debating whether AI is inherently good or bad, Felicia Jackson speaks with Professor Saeema Ahmed-Kristensen, Associate Pro Vice Chancellor for Research and Impact at the University of Exeter and Director of DIGIT Lab, about something much more grounded: why so many digital and AI transformation efforts struggle in practice and what that reveals about the limits of technology alone.

One of the most useful distinctions in the conversation was between problems that are well-defined and those that are not. AI is particularly powerful when objectives are clear, data is available, and success can be measured relatively easily. In those contexts - pattern recognition, diagnostics, optimisation - it can offer extraordinary value. But many of the most important challenges organisations face are different.

Sustainability, climate strategy, major organisational change, and social systems are messy, politically embedded and filled with trade-offs. They are often what researchers describe as wicked problems: issues where there is no single right answer, where choices create consequences elsewhere, and where uncertainty is part of the challenge itself.

That distinction matters because it shifts the conversation. It suggests that AI may be extremely useful in supporting parts of decision-making, but it does not remove the need for human judgment. In fact, in many cases, it may make governance, accountability, and strategic clarity even more important.

AI is powerful, but power is not wisdom. Better tools do not automatically create better outcomes. What they do do is make it even more important to understand what kind of organisations, systems and governance structures are capable of using them responsibly. As this new Shaken Not Burned AI arc begins, that feels like the right place to start.

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