Companies are now rejecting expensive SaaS contracts because their internal teams can build equivalent custom solutions in days using AI coding tools. This trend signals a fundamental threat to the traditional SaaS business model, as the 'build vs. buy' calculation has dramatically shifted.
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The rise of AI services companies like Invisible and Palantir, which build custom on-prem solutions, marks a reversal of the standardized cloud SaaS trend. Enterprises now prioritize proprietary, custom AI applications to gain a competitive edge.
While AI expands software's capabilities, vendors may not capture the value. Companies could use AI to build solutions in-house more cheaply. Furthermore, traditional "per-seat" pricing models are undermined when AI reduces the number of employees required, potentially shrinking revenue even as the software delivers more value.
"Vibe coding" platforms, which allow users to create apps from natural language, pose a direct threat to the B2B SaaS market. For simple workflows, it is becoming faster for a team to build its own personalized app than to navigate the sales, procurement, and integration process for an existing SaaS product.
AI is becoming the new UI, allowing users to generate bespoke interfaces for specific workflows on the fly. This fundamentally threatens the core value proposition of many SaaS companies, which is essentially selling a complex UX built on a database. The entire ecosystem will need to adapt.
AI is making core software functionality nearly free, creating an existential crisis for traditional SaaS companies. The old model of 90%+ gross margins is disappearing. The future will be dominated by a few large AI players with lower margins, alongside a strategic shift towards monetizing high-value services.
The ease of building applications on top of powerful LLMs will lead companies to create their own custom software instead of buying third-party SaaS products. This shift, combined with the risk of foundation models moving up the stack, signals the end of the traditional SaaS era.
The dominant per-user-per-month SaaS business model is becoming obsolete for AI-native companies. The new standard is consumption or outcome-based pricing. Customers will pay for the specific task an AI completes or the value it generates, not for a seat license, fundamentally changing how software is sold.
The core value proposition of no-code platforms—building software without code—is being eroded by AI tools. AI-assisted 'vibe coding' makes it much easier for non-specialists to build internal line-of-business apps, a key use case for no-code, posing an existential threat to major players.
Nimble small and medium-sized businesses will increasingly use AI to build custom internal tools, especially for CRM. They will opt to create the 20% of features they actually need, rather than pay for complex, expensive enterprise software where they ignore 80% of the functionality.
In the future, it will be easier for businesses to build their own custom software (e.g., Salesforce) through prompting than to buy and configure an off-the-shelf solution. This shift towards "liquid software" will fundamentally challenge the one-size-fits-all SaaS model, especially for companies that currently rely on implementation partners.
