Banks spend 93% of their AI budget on technology. Only 7% goes to people. And then they wonder why 95% see no impact on their P&L.
On March 31, 2026, I gave a keynote at the Zühlke Banking Talk in Schlieren on why the future of AI is “cybernetic” and what it takes to become an AI-native bank. The evening brought together perspectives from academia, a major German bank, and practitioners from Swiss financial institutions.
I am honored to share that I have been named a Digital Shaper 2026 in the Mentors category. The Digital Shapers initiative, organized by BILANZ, Handelszeitung, and digitalswitzerland with the support of Huawei, recognizes 100 of Switzerland’s most influential digital minds each year across ten categories.
It is not the technology that is under pressure, but its integration into everyday business operations. Budgets are tightening, regulation is taking hold, and boards are demanding robust results rather than more roadmaps. The era of non-committal pilot projects is ending.
Although AI has moved fast, many organisations haven’t. Most leaders we speak to aren’t short on ideas, proofs of concept, or vendor demos. The challenge is turning AI into something repeatable, a capability you can trust, scale, and steer without creating new risks or bottlenecks.
To stay competitive, companies need a radical upgrade. The Cybernetic Enterprise transforms organizations into learning systems that adapt faster than their market changes.
2026 will be the year when the wheat is separated from the chaff in AI: it’s not the better model that makes the difference, but the ability to deliver impact under real-world conditions. What decision-makers need to know and do now so that AI evolves from experiment to true partner.
Artificial intelligence (AI) is everywhere. Yet lasting business value often remains elusive. Too many companies still see AI as a tool or quick fix, rather than what it can be: a strategic partner for continuous learning and adaptation. To achieve competitive advantages in a dynamic, data-driven world, organizations must fundamentally restructure themselves as a Cybernetic Enterprise, where AI is firmly anchored as a feedback and learning amplifier. Instead of viewing AI in isolation or as an add-on, it should become an integral part of the organizational operating system. Only when AI transforms data, processes, and customer interactions into actionable learning does a useful tool become a true gamechanger, one that makes companies more agile, capable of learning, and future-oriented.
Understand why most digital transformations fail, and you’ll figure out what tomorrow’s leading businesses will all have in common. Here’s how Cybernetics solves AI challenges at scale.
Discover the people, processes and technology you’ll need to mitigate setbacks on your transformation journey, and unlock AI-augmented ROI that compounds as it scales.
Most companies that work in an agile way today while simultaneously trying to implement AI will not survive the next decade, in my opinion. The reason: their operating system is too old. The future is not agile. The future is not AI either. The future is cybernetic.
Digital and agile was yesterday # Many companies believe they can secure their future with a dash of agility and rapid AI pilot projects. But those who simply “graft” artificial intelligence onto outdated structures will fail. A radical upgrade of the operating model is needed.
Does AI really solve the problems we have? What does it mean for innovation and intellectual property? Will AI replace patent analysts? In this webinar with IamIP, I cut through the fog of AI hype and share a practical framework for understanding where AI genuinely adds value, and where it falls short.
