AI represents a fundamental platform shift, driving unprecedented capital expenditure and infrastructure investment across the tech industry. Despite massive spending on GPUs and data centers, current large language models function primarily as commodities lacking inherent network effects or pricing power. This necessitates a shift in focus from model development to practical deployment and operational integration. Historical parallels, such as the evolution of spreadsheets and mobile data, indicate that transformative technologies often begin by optimizing existing tasks before enabling entirely new business models. True value capture will likely emerge not from the models themselves, but from their application in automating complex workflows and identifying previously impossible analytical insights. As the industry moves beyond the initial hype, the focus must shift toward solving specific, high-value problems rather than simply increasing software output.
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