AI unbound
featuring TED

As access to powerful AI capabilities expands, organisations are facing a new challenge: if everyone can leverage the same technology, what will create lasting competitive advantage?

At the European premiere of AI Unbound featuring TED, selected leaders from business, technology and academia explored how AI is reshaping enterprises, industries and decision-making. From the rise of agentic AI and AI-first organisations to the future role of human judgement, trust and expertise, the discussions revealed that the real transformation goes far beyond productivity gains.

Across the evening, one message stood out: the organisations that succeed in the AI era will not be those with access to the most capable models, but those that can feed them the right data, apply them in the right processes, govern them properly and turn that into meaningful value.

With contributions from Ericson Chan, Group Chief Information & Digital Officer at Zurich Insurance Group, Vikke Kandell, incoming Group CIO at ABB, and Christian Westermann, Partner and AI Leader at PwC Switzerland, the discussion centred on overcoming the roadblocks that stand between AI ambition and meaningful adoption. 

AI has the potential to accelerate decision-making, execution and innovation. At the same time, increasing volumes of data and growing autonomy require stronger foundations of trust.

The challenge for leaders is therefore not simply how to use AI to move faster. It is how to move faster while preserving confidence, accountability and trust.

The panel conversation, moderated by Carolin Roth, financial journalist and moderator, provided behind-the-scenes insights from Zurich, ABB and PwC. The panel challenged leaders to reconsider how they measure the return on AI. Usage and time saved are useful indicators, but they do not necessarily show whether AI is creating meaningful business value. In growing organisations, the impact may not appear as a lower cost base. It may instead become visible through increased capacity, faster execution or the ability to generate more revenue with the same resources. Measuring the return on AI therefore requires a broader set of metrics. 

The discussion also highlighted that many organisations are moving beyond experimentation. While sharing ideas is relatively straightforward, the more difficult challenge lies in scaling successful solutions across business units and creating the technology foundations that allow them to be adopted consistently across the enterprise.

Ericson Chan explored why AI should be viewed not as another technology trend, but as the new operating system of the future enterprise. 

He framed the evolution of AI through three distinct waves. The first was defined by large language models, the second by reasoning capabilities, and the third by agentic systems capable of increasingly autonomous action. What began as a period of fascination and experimentation is now progressing beyond productivity gains towards enterprise-wide transformation. 

Rather than focusing on isolated use cases, organisations need to examine how AI can be embedded across the entire value chain. The question is no longer where AI can improve a single process, but how it can reshape the way value is created, delivered and captured across the business. The answer lies in rethinking how the business itself operates and how AI acts as a force multiplier. This multiplier effect applies to risk as much as it does to performance. AI should not be treated simply as an isolated risk category. As it becomes embedded across processes and decisions, it can amplify existing strengths, weaknesses and risks throughout the enterprise. The outcome depends not on technology alone, but on how effectively organisations combine leadership, execution and innovation. 

Ericson Chan argued that AI transformation should start not with the technology itself, but with business value. His practical sequence for action: identify where meaningful value can be created, prioritise what should happen first, determine whether successful initiatives can be scaled and establish how impact will be measured over time.

One of the most important shifts he mentioned during his keynote was that AI is no longer primarily a technology story. It is increasingly a human story. Success depends less on access to technology and more on how leaders, teams and organisations adapt, collaborate and make decisions in an AI-enabled environment.

Christian Westermann challenged some of the most established assumptions about professional services. He illustrated this through a moment in 1997 that many saw as an ending: Deep Blue's defeat of Garry Kasparov. At the time, everybody concluded that chess was dead and that nobody would play any more. Everybody was wrong. Today there are more chess players than ever.

What happened instead was that Kasparov took the game to a different level and introduced Centaur Chess: human and AI playing against other pairs of human and AI. The game became bigger, with strategies far more complex than those of the 1990s, and the human ceiling was raised – players learned from the machines they played with and against. This story became the foundation for a broader lesson about AI.

Chess, however, is a closed game: the rules are transparent and there is no ambiguity. The lesson Westermann draws from this is a practical one: wherever your business has a clear rulebook and no ambiguity, plan from the point of view that the machine will take it over at some time.

Yet this does not make people less important. It simply shifts where their value is created. Westermann showed that the uniquely human contribution lies in the ability to navigate ambiguity, build trust, understand context and, above all, take responsibility and ownership. That is something AI was not made for.

Consulting is one of the industries that were impacted first and significantly, which is why these patterns are already visible in delivery today. Teams are becoming smaller and more cross-functional, equipped with the best of tools and delivering the same output with fewer people. And rather than using AI merely to perform existing work more cheaply, organisations can redirect human capacity towards challenges that were previously considered too complex, too expensive or too difficult to tackle.

The message was clear: AI changes not only how work is performed, but also what becomes possible. The real power of AI, he argued, is not in automation and not in efficiency. It emerges when AI is brought together with knowledge, and when that knowledge is connected to other knowledge. That is when you can ask questions you did not ask before and gain clarity about your company that you did not have before. Or, as he put it: that is more than an efficiency gain – it is the start of a new game.

We are seeing a future where AI takes on much of the groundwork that follows clear rules, allowing organisations to operate through smaller, cross-functional, AI-augmented teams. Human judgement, trust and client relationships become increasingly important while technology handles much of the underlying analytical effort. The question is no longer only what decisions can be automated, but how humans and AI make better decisions together.

This does not remove the need for human judgement. Instead, it changes the way judgement is exercised. Leaders will increasingly need to combine AI-generated insight with experience, context and accountability.

Marc Holitscher, National Technology Officer at Microsoft Switzerland, posed this question, which increasingly defines the AI era, and explored how technology ecosystems can accelerate AI adoption and help organisations build sustainable momentum.

The answer presented throughout this section was not centred on technology alone. Instead, the emphasis was placed on expertise, trust and the ability to turn experience into quality.

One recurring idea was the concept of a learning loop that compounds expertise over time. Technology can amplify knowledge, but sustainable advantage depends on how organisations accumulate expertise, transfer it across teams and turn experience into better decisions and outcomes.

The argument becomes even more relevant as generative AI lowers barriers to content creation and problem solving.

In a world where access to intelligence becomes widespread, competitive advantage increasingly depends on judgement rather than volume, on knowing what matters rather than simply creating more.

The final keynote of the evening was delivered by Dr Jonnie Penn, TEDx speaker, historian of technology, bestselling author and AI ethicist at the University of Cambridge. His presentation traced the trajectory of AI as part of a longer technological arc.

He framed AI within a broader technological evolution from semiconductors and systems to networks, cloud, platforms, the internet and now AI. This progression was presented not as a series of isolated innovations, but as compounding layers of digitalisation that have steadily expanded what organisations can achieve.

Dr Jonnie Penn explored the transition from deterministic systems towards generative reasoning and beyond. Whereas previous generations of technology primarily processed structured information, modern AI systems increasingly operate within domains that include language, meaning and judgement.

Understanding the evolution helps explain why AI is becoming much more than a productivity tool. It is beginning to influence the way organisations discover knowledge, make decisions and create value.

Across the programme, one message stood out: AI is changing the logic of work, not simply the tools of work.

• Closed systems will increasingly become machine-owned. Human value will move towards ambiguity, judgement, trust and responsibility. In consulting, this shift is already challenging traditional assumptions, from hours-based delivery models to organisational structures built around large pyramids of people.
• Agentic AI signals the next stage of enterprise transformation, extending AI from understanding and generation towards autonomous execution. 
• As AI capabilities become more widely available, differentiation will not come from access to technology alone. It will come from the expertise organisations compound, the trust they protect and the knowledge they make their own.
• And as enterprise velocity increases, trust becomes a strategic requirement rather than a compliance exercise. 

In that sense, AI Unbound featuring TED was not simply another event about AI. It was about what organisations choose to do with intelligence once it becomes abundant and how they transform that intelligence into meaningful value.