The true revolution of artificial intelligence (AI) lies not in the technology itself, but in how organizations learn and innovate with it. Recently, the Financieel Dagblad warned in an article about “desk bagger”: mediocre AI output that actually reduces productivity. I would like to nuance that analysis and argue that the problem is not technology, but our own linear thinking.
AI is often seen as a panacea that instantly produces perfect results. In reality, AI is a learning partner: those who use AI to learn and improve create a flywheel for innovation. True progress is cyclical: experiment, correct, try again. And this is all the more true when working with AI.
From output to impact
Organizations often steer by deliverables, but the value is not in the initial output, but in the learning process that follows. AI can produce mountains of text and analysis, but that doesn’t mean the quality or relevance goes up. Therefore, the right question is not “What does AI produce?” but “What do we learn with AI, and what difference does it make?” Impact must be the new measure.
Practical examples illustrate this approach:
- In healthcare, daily feedback on AI analysis of scans led to faster diagnoses and increased patient confidence.
- In finance, cyclical improvement turned an irritating chatbot into a valuable assistant for customers and employees.
- In government, short improvement cycles led to faster and more transparent permit applications.
Exponential learning
Exponential learning occurs when organizations deploy AI cyclically (plan, do, check, act). Each round produces better results, sharper questions and more confidence. The pace of learning thus becomes the new competitive factor. The real revolution is in the learning and adaptive power of organizations, not merely in the computational power of AI.
Leadership in a new era
This requires new leadership: giving space to experiment and learn from mistakes. Leaders who deploy AI strategically are building a culture of reliability, speed and innovation. The bottleneck is not “desk bagger,” but governance that clings to linear thinking. Organizations that see AI as a learning partner are making a difference for customers, employees and society.
Conclusion: the AI revolution does not founder on poor output, but on our own linear expectations. Those who embrace AI as an engine for learning and improvement create an organization that becomes faster, more reliable and thus future-proof.
