Big Tech's race to dominate AI is starting to look less like visionary innovation and more like a dangerous addiction. Since 2023, tech giants have poured hundreds of billions into AI infrastructure, models, and moonshot products that may not reach meaningful enterprise adoption for years. Meanwhile, the technologies that actually run businesses today—cloud platforms, core SaaS tools, security, analytics, and integrations—are being quietly deprioritized. Roadmaps slip, support thins out, and customers are nudged toward immature AI features instead of getting the reliability and improvements they actually need.

This imbalance isn't just a product strategy mistake; it's a looming revenue and trust crisis. Enterprise buyers are already feeling neglected as "legacy" products stagnate while marketing and engineering obsess over AI. In regulated and risk-averse industries, where AI adoption is inherently slow, the gap between investment and return is growing wider. That gap is where churn, budget cuts, and new competitors thrive. If Big Tech doesn't rebalance—protecting the core while building the future—it risks funding the AI revolution by eroding the very customer relationships that make it possible.