The current surge in AI-related capital expenditure by major tech companies—Amazon, Microsoft, and Google—has sparked intense market reactions, but to understand the long-term implications, it’s essential to step back and consider the broader context. Bernard Golden, CEO of Navica, offers a framework called KGB to analyze the future of hyperscaler spending, outlining three possible scenarios. The first, K, stands for “Keeping Up With the Joneses.” In this scenario, the big tech firms are locked in a competitive arms race, investing heavily to avoid falling behind. Executives may view AI integration as existential, fearing that failure to keep pace could lead to obsolescence, much like the decline of Sears. Critics argue this leads to wasteful spending driven more by fear than strategy, potentially resulting in massive losses. The second scenario, G, is the Goldilocks outcome—spending that’s just right. In this view, capex increases reflect solid, data-driven confidence in sustained demand. These companies have deep visibility into customer needs through real-time usage data, long-term contracts, and ongoing enterprise deals. Their spending isn’t reckless; it’s a measured response to growing, predictable demand and strong monetization potential. The third scenario, B, is the “Boat” model—inspired by the movie Jaws, where the police chief realizes he’ll need a much larger vessel to face the shark. Here, demand for AI infrastructure is so explosive that no matter how much capacity is built, it’s consumed immediately. The real constraint isn’t spending but the ability to build fast enough—limited by chip supply, server availability, power grids, and data center construction timelines. The risk isn’t overspending; it’s under-investing. Currently, the K and B camps are in sharp conflict, while G proponents remain calm, observing that the scale of these businesses is often misunderstood. AWS, for example, generates around $142 billion in annual revenue, growing at 24%—meaning over $34 billion in new revenue is expected in the next year alone. Azure and Google Cloud, while slightly behind, are still massive and backed by deep financial resources. Moreover, the AI boom isn’t happening in a vacuum. It’s part of a decades-long shift from analog to digital systems—following the rise of the internet, cloud computing, and enterprise software. AI is the latest phase in this transformation, with significant growth still ahead. The fact that these companies chose to dramatically increase capex despite the 2022 market downturn is telling. Their executives, many of whom were deeply affected by that episode, are now betting big again—likely because they have access to information and insights that investors don’t. Their equity-based compensation means they have a strong personal stake in long-term success. This suggests that the current spending may not be driven by hype, but by a belief that demand is real, massive, and growing faster than infrastructure can keep up. If so, this might truly be the Jaws moment—where the real danger isn’t spending too much, but failing to build a big enough boat to meet the challenge.