AI facing the profitability wall: how can you avoid paying for nothing?
Summary
The article argues that companies have moved from enthusiastic AI adoption to stricter cost control as token usage and infrastructure bills rise. It highlights the gap between AI experimentation and measurable business value, citing examples of budget overruns and failed projects. It recommends hybrid architectures, stronger governance, and selective use of private GPUs or open source models to reduce inference costs. The piece also frames Europe’s AI opportunity around frugal innovation and closer cooperation between research and industry.
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