Category Archives: Business

Schweizerhalle created dead fish, 5 years later we had an Hazardous Incident Ordinance – we need the same for AI

Safety regulation usually follows a visible incident, not foresight. AI failures often leave no smoke, no dead fish, no front-page photograph, so political attention lags. Switzerland could move now with two simple steps: require critical infrastructure operators to declare autonomous AI systems, and ensure agent escape or permission escalation is treated as a reportable security incident, not merely “misalignment.” Continue reading →

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“What has been thought, cannot be un-thought” – we need AI certification fast

Voluntary restraint by individual labs will not prevent harmful outcomes from frontier AI, because the real risk is created at deployment. We need an aviation-style certification regime for high-risk AI deployments: independent testing, continuous monitoring, mandatory incident reporting, and enforceable accountability. Without it, insurance and boards will increasingly refuse large-scale agentic systems, and regulators will lose authority by lacking technical capability. Continue reading →

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Which AI Projects Survive When Token Subsidies End?

Many enterprise AI pilots look ROI-positive only because model pricing is still effectively subsidized. As token costs shift and agentic workflows multiply usage, the winners will be AI projects priced and managed around measurable outcomes. Stress-test your business case at 3× today’s rates and demand cost-per-outcome, not cost-per-seat. Continue reading →

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AI might end up a controlled substance

Public sentiment is turning against AI—not over superintelligence fears, but over electricity and water consumption that show up on real utility bills. As compute becomes measurable and governable, regulation is shifting toward licensing and metering AI like a controlled substance. The winners won’t just have the best models—they’ll have accountability, auditability, and paperwork ready. Continue reading →

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A Stress Diagram Cannot Be Scraped

Frontier models are becoming interchangeable; the differentiator is context. In industrial manufacturing, the real moat is connecting physical test signals, structured lab data, and cross-system workflow agents that turn measurements into decisions. The winners will pair AI capability with deep domain expertise and the operational wiring that models can’t replace. Continue reading →

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Buy the Workflow, not the Agent

If you are buying an agent platform in 2026, you are buying a rebuild in 2027. A few early indicators paint the following picture: The agent is not the problem; the architecture around it is. An agent has three things … Continue reading →

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The Regulator nobody lobbied against

The AI industry spends big on lobbying. OpenAI’s CEO personally argued against safety regulations and transparency requirements. The industry’s message was consistent. Regulation will kill innovation. A patchwork of state laws will fragment compliance. Let us self-regulate. They possibly were … Continue reading →

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The Token Tax

Every time an AI model gets called, GPU cycles get burned. GPUs cost 6-8x more per operation than traditional CPU compute. That is structural, and right now it is mostly hidden to everyday (enterprise) users. OpenAI projects a cash burn … Continue reading →

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The Paradox Is back

In 1987, Robert Solow looked at two decades of corporate IT investment and wrote one of the most quoted lines in economics. “You can see the computer age everywhere but in the productivity statistics.” Nearly forty years later, replace “computer” … Continue reading →

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The big Recomposition

In the previous posts I argued that most companies think about AI linearly. Make the process faster. But keep the layout the same. Bolt the electric motor onto the old belt-and-shaft system and call it AI-progress. But there is a … Continue reading →

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