A single feature advantage is insufficient for an AI startup to displace a software giant like Salesforce. True disruption requires a fundamental shift across user interface (proactive agents vs. forms), data utilization (unstructured data), and business model (monetizing tasks vs. seats).
Incumbent companies are slowed by the need to retrofit AI into existing processes and tribal knowledge. AI-native startups, however, can build their entire operational model around agent-based, prompt-driven workflows from day one, creating a structural advantage that is difficult for larger companies to copy.
In the previous SaaS era, emulating giants like Salesforce was a common but flawed strategy for startups. In the new AI era, there is no playbook at all, forcing founders to rethink go-to-market strategies from first principles rather than copying incumbents.
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.
Counter to fears that foundation models will obsolete all apps, AI startups can build defensible businesses by embedding AI into unique workflows, owning the customer relationship, and creating network effects. This mirrors how top App Store apps succeeded despite Apple's platform dominance.
The current moment is ripe for building new horizontal software giants due to three converging paradigm shifts: a move to outcome-based pricing, AI completing end-to-end tasks as the new unit of value, and a shift from structured schemas to dynamic, unstructured data models.
The most durable moat for enterprise software is established user workflows. The current AI platform shift is powerful because it actively drives new behaviors, creating a rare opportunity to displace incumbents. The core disruption isn't just the tech, but its ability to change how people work.
Incumbents face the innovator's dilemma; they can't afford to scrap existing infrastructure for AI. Startups can build "AI-native" from a clean sheet, creating a fundamental advantage that legacy players can't replicate by just bolting on features.
The shift to AI creates an opening in every established software category (ERP, CRM, etc.). While incumbents are adding AI features, new AI-native startups have an advantage in winning over net-new, 'greenfield' customers who are choosing their first system of record.
The true advantage for new AI-native companies lies not in simply using AI tools, but in building entirely new business models around them. This mirrors how Direct-to-Consumer brands leveraged Shopify not just to sell online, but to fundamentally change distribution, marketing, and customer relationships, thereby outmaneuvering incumbents.
Sierra CEO Bret Taylor argues that transitioning from per-seat software licensing to value-based AI agents is a business model disruption, not just a technological one. Public companies struggle to navigate this shift as it creates a 'trough of despair' in quarterly earnings, threatening their core revenue before the new model matures.