Hyperscalers Chase AI Billions as Core Cloud Services Risk Neglect

3 articles · Updated · InfoWorld · Aug 18

AWS, Microsoft Azure and Google Cloud are steering capital and executive attention toward AI platforms, chips and large-scale compute as enterprise demand for GPUs and model services surges.
That shift risks slowing improvements in core cloud products—storage, databases, networking, identity and monitoring—that still carry most day-to-day enterprise workloads and require constant investment.
The warning is that AI add-ons such as chatbots and natural-language assistants do not fix fundamentals like reliability, recovery, security, price-performance, service limits and support quality.
Enterprises, many of which will spend most cloud budgets on traditional infrastructure over the next 2 to 5 years, are urged to scrutinize release histories, outage patterns and road-map commitments.
The concern follows a broader AI spending boom: Google and Amazon this week lifted 2026 capex forecasts to $195-$205 billion and $220 billion, underscoring how strongly hyperscalers are prioritizing AI.