https://arab.news/442f8
Concerns about an AI bubble have intensified since the start of 2026, as investors and policymakers focus on whether, and when, it might burst. But the real question is not whether current valuations are inflated; it is whether AI’s emerging business model differs from those of earlier technological revolutions.
For decades, scale has been the primary driver of tech companies’ performance and valuations. As apps, websites, online retailers, and social media platforms expanded their user bases, marginal costs fell, network effects took hold, and pricing power increased. Valuations came to reflect long-term growth potential rather than short-term profitability.
The forces that defined past tech winners are unlikely to dominate AI’s rollout, because the competitive dynamics differ across six critical dimensions. First, capital expenditure is no longer a shallow moat; it is a formidable barrier. In earlier technological waves, capital requirements were largely confined to the startup phase and relatively modest. Facebook, for example, initially raised just $500,000 in seed funding.
But those earlier innovations were built on top of existing infrastructure such as Linux, Apache, MySQL, and PHP — the so-called LAMP stack — which dramatically lowered upfront costs. AI, by contrast, is extraordinarily capital intensive. Industry-wide capital investment is projected to exceed $7 trillion by 2030 as companies build data centers, expand computing capacity, and invest in specialized hardware. Unlike previous tech cycles, these investment requirements will not fade as the industry matures and may even intensify.
