Kategorie: Artificial Intelligence

Autonomous AI agents are widely seen as the next evolution of software. They plan, decide and increasingly act on their own. That is precisely what makes them so powerful and, at the same time, so risky. The more autonomy a system is given, the closer it gets to a point where control is no longer guaranteed. The so-called “Rule of Two”, a security principle introduced by Meta, is a direct response to this tension. It is neither a complex framework nor a new technology, but a deliberately simple rule addressing a fundamental issue: the concentration of power within a single system.

At CHI 2026 in Barcelona, Apple is not showcasing major product launches, but something arguably more significant: a set of research contributions that offer a rare glimpse into how the company is thinking about the future of interfaces, accessibility and data-driven design.

Generative AI is not just transforming processes, products or business models. It is going deeper — into the core of organisations: leadership, accountability and structure. What once felt relatively stable is now being redefined. New roles are emerging, organisational charts are becoming more fluid, and leadership itself is undergoing a fundamental shift.

Agents are widely seen as the next evolution of AI. Systems such as Claude (including Cowork) or automation platforms like n8n promise to plan and execute entire tasks autonomously. Yet this is precisely where a new cost dynamic emerges — one that is catching many organisations off guard in 2026. AI is no longer priced per request, but per underlying computation.

Introducing generative AI is not an IT project. It is a management challenge. While tools can be deployed quickly, real success depends on something else entirely: strategy, leadership, organisation and culture. Companies that treat generative AI as just another software upgrade will struggle to unlock its potential — and may even introduce new layers of complexity.

A debut novel becomes a bestseller, a publisher picks it up, the US release is prepared – then an AI detector reveals that 78 per cent of the text was probably machine-generated. Hachette pulls the book. What remains is more than a scandal: it's the blueprint for the crisis of trust facing the entire creative economy.

What began as a global augmented-reality game is quietly becoming infrastructure for autonomous machines. Over the past decade, millions of players of Pokémon Go have taken photos of streets, buildings and public landmarks while hunting for virtual creatures. Today, that same visual data is helping delivery robots navigate cities with remarkable precision.

When introduced its assistant , it was quickly positioned as Europe’s alternative to ChatGPT. Over the past months, the system has evolved considerably, adding multimodal capabilities, integrations with business tools and a clear emphasis on European data sovereignty. At the same time, its development also reveals where the current limits of this alternative still lie.