Kategorie: Innovation Culture

Artificial intelligence is changing the rules for people entering the workforce. Many tasks that were once considered classic entry-level work can now be automated or at least significantly accelerated: research, initial analysis, drafting presentations, writing first versions of documents, generating code snippets, preparing data and responding to customer enquiries. Precisely because of this, it is no longer enough for graduates and junior employees to be hardworking, reliable and technically competent.

While many countries are still debating whether students should be allowed to use ChatGPT in the classroom, Estonia has chosen a far more ambitious path. Through AI Leap, the Baltic nation is...

Malta is taking a step that no other country has attempted on this scale so far: the government plans to offer citizens and registered residents a free one-year subscription to ChatGPT Plus. The only requirement is the completion of a short online course in AI literacy. Once completed, participants receive access to a premium AI service that would normally require a monthly subscription.

While many AI companies mainly talk about benchmarks, model sizes and chatbots, is pursuing a far more radical approach: the startup Andon Labs is deploying AI agents into real economic environments with real budgets, real people, real contracts and real consequences.

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.

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.