Kategorie: Innovation Management

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.

By 2026, leadership has not been dramatically reinvented, but it has been quietly redefined. Artificial intelligence is no longer an innovation project or a future ambition; it has become part of everyday operations. Reports are generated automatically, decisions are prepared by data models, assistants and agents handle routine tasks. For managers, this shift changes the nature of effectiveness. What matters less is technical depth, and what matters more is the ability to connect technology, people and organisational purpose.

Just a few years ago, the job title sounded like something out of a future trends report. Today, it's rapidly becoming reality: the Human-Machine Teaming Manager is emerging as a key figure in organisations seeking to bridge the gap between human intuition and machine efficiency. As artificial intelligence and automation become deeply embedded in workflows, a new professional role is taking shape—at the intersection of technology, psychology, and organisational development.

Artificial intelligence is no longer just an experiment for major companies – it's a proven driver of business value. That’s the key finding from a new study by the Human-AI Research Department at the Wharton School, which surveyed more than 800 senior executives from large US firms. Around 75 per cent of respondents said their AI projects are already delivering a positive return on investment – a striking result amid ongoing scepticism around the real-world impact of AI.

Artificial intelligence is transforming the world of work at breathtaking speed. Algorithms are screening job applications, optimising production workflows and handling customer queries. But who decides how these systems are used? And what role do employees play in that decision? In Germany, the answer is clear: co-determination.