Kategorie: Innovation Management

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.

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.

Artificial intelligence is widely seen as the engine of a new productivity era. Yet a recent analysis discussed in the Harvard Business Review suggests a more complex picture. The research identifies a growing phenomenon among knowledge workers that the authors describe as “AI Brain Fry” — a form of mental fatigue caused by intensive interaction with, and supervision of, AI tools.