The public-cloud market is hitting unprecedented scale in 2025. The three dominant service providers, Amazon Web Services (AWS), Microsoft Azure, and Google Cloud, continue to post record growth, fueled by generative AI, massive data flows, and enterprise migrations. According to market trackers, global cloud-infrastructure spending hit roughly US $99 billion in Q2 2025 alone, growing more than 25 % year-on-year.
That scale is impressive, but the flip side is equally important. With scale comes structural exposure to over-consumption, waste, runaway costs, and sub-optimized deployments. This article reviews the numbers behind the “Big Three,” highlights where cost leakages occur, and shares steps enterprises can take to avoid being part of the waste wave.
As the calendar flips toward the end of the fiscal year for major technology suppliers, procurement teams are entering a critical, and often perilous, window. January fiscal year-end suppliers are pushing hard to “make the number,” and their account teams are laser-focused on closing deals that boost quarterly and annual performance metrics. That urgency can cut both ways.
While suppliers will apply every sales pressure tactic in their playbook to close favorable deals for them, savvy buyers can use this moment to turn the tables and secure exceptional commercial outcomes, if they plan correctly. At NET(net), we’ve seen it all: inflated “act now” discounts, bundling traps, extended terms that favor lock-in, and artificial deadlines designed to create FOMO. The key is preparation, understanding the supplier’s motivations, market conditions, and your leverage.
Imagine this: 95% of enterprise generative-AI pilots deliver zero ROI. That’s not a rumor; that’s MIT’s 2025 analysis of real-world deployments. Yet year after year, CIOs chase the next “peak of inflated expectations,” following analyst firm frameworks as if they were navigational charts to innovation rather than treasure maps to someone else’s revenue.
Enter Gartner’s Hype Cycle, Magic Quadrant, and Forrester’s Wave , models revered as industry gospel but often the very machinery driving the disillusionment they pretend to measure
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