The primary threat from AI disruptors isn't immediate customer churn. Instead, incumbents get "maimed"—they keep their existing customer base but lose new deals and expansion revenue to AI-native tools, causing growth to stagnate over time.

As SaaS firms use AI to optimize operations, they feed models data on how their products are built. This creates a deflationary spiral where customers can use the same AI to build cheaper alternatives, threatening the core SaaS business model by accelerating price and profitability compression.

As AI infrastructure giants become government-backed utilities, their investment appeal diminishes like banks after 2008. The next wave of value creation will come from stagnant, existing businesses that adopt AI to unlock new margins, leveraging their established brands and distribution channels rather than building new rails from scratch.

AI infrastructure leaders justify massive investments by citing a limitless appetite for intelligence, dismissing concerns about efficiency. This belief ignores that infinite demand doesn't guarantee profit; it can easily lead to margin collapse and commoditization, much like the internet's effect on media.

As AI makes software development nearly free, traditional engineering moats are disappearing. Businesses must now rely on durable advantages like network effects, economies of scale, brand trust, and defensible IP to survive, becoming "unsloppable."

The narrative of AI replacing jobs is misleading. The real threat is competitive displacement. Professionals will be put out of business not by AI itself, but by more agile competitors who master AI tools to become faster, smarter, and more efficient.

If AI makes intelligence cheap and universally available, its economic value may collapse. This theory suggests that selling raw AI models could become a low-margin, utility-like business. Profitability will depend on building moats through specialized applications or regulatory capture, not on selling base intelligence.

AI acts as a force multiplier for individuals who learn to leverage it, allowing them to achieve the output of a much larger team. The threat isn't the technology itself, but competitors who adopt it faster to gain a significant advantage.

SaaS products like Salesforce won't be easily ripped out. The real danger is that new AI agents will operate across all SaaS tools, becoming the primary user interface and capturing the next wave of value. This relegates existing SaaS platforms to a lower, less valuable infrastructure layer.