Despite the narrative that AI-native startups will replace legacy SaaS, frontier AI lab Anthropic is hiring a Salesforce admin. This "revealed preference" demonstrates the powerful lock-in, complexity, and scale advantages that incumbents like Salesforce still possess, even among their would-be disruptors.

Related Insights

Unlike the slow denial of SaaS by client-server companies, today's SaaS leaders (e.g., HubSpot, Notion) are rapidly integrating AI. They have an advantage due to vast proprietary data and existing distribution channels, making it harder for new AI-native startups to displace them. The old playbook of a slow incumbent may no longer apply.

As AI commoditizes user interfaces, enduring value will reside in the backend systems that are the authoritative source of data (e.g., payroll, financial records). These 'systems of record' are sticky due to regulation, business process integration, and high switching costs.

Investor Mitchell Green argues that the fear of AI "vibe coding" away SaaS businesses is overblown. Incumbents like Workday spent decades building trust and deep enterprise integrations, a moat that can't be easily replicated with code alone, regardless of AI's power.

The AI revolution may favor incumbents, not just startups. Large companies possess vast, proprietary datasets. If they quickly fine-tune custom LLMs with this data, they can build a formidable competitive moat that an AI startup, starting from scratch, cannot easily replicate.

The "SaaSpocalypse" narrative misses a key reason large enterprises buy from vendors like Salesforce. It's not just about features, but accountability—like hiring McKinsey, it provides "air cover" and "a throat to choke." This institutional trust is a powerful moat against nascent, AI-generated tools.

AI favors incumbents more than startups. While everyone builds on similar models, true network effects come from proprietary data and consumer distribution, both of which incumbents own. Startups are left with narrow problems, but high-quality incumbents are moving fast enough to capture these opportunities.

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).

AI doesn't kill all software; it bifurcates the market. Companies with strong moats like distribution, proprietary data, and enterprise lock-in will thrive by integrating AI. However, companies whose only advantage was their software code will be wiped out as AI makes the code itself a commodity. The moat is no longer the software.

Incumbent SaaS companies like Salesforce are cutting off API access to prevent AI startups from siphoning value. To build a durable business, new AI companies cannot simply be a "system of action" on top of old platforms; they must aim to become the new system of record, which requires building complex data migration tools from day one.

The idea that AI will eliminate SaaS is overblown because it incorrectly projects small startup behavior onto large enterprises. Fortune 100s face immense change management, security, and maintenance challenges, making replacing established vendors with internal AI-coded tools impractical.