While public markets reacted negatively to ServiceNow's M&A activity, the strategy is a deliberate offensive move to lead in AI. By acquiring companies in high-growth areas like AI-powered cybersecurity, ServiceNow is expanding its market and solidifying its position as an "AI have" rather than signaling weakness.

Established SaaS companies struggle to implement AI because their teams are burdened with supporting existing customers, fixing feature gaps, and fighting legacy competitors. AI-native startups have a massive advantage as they don't have this baggage and can focus entirely on the new paradigm.

Amplitude's CEO acquired multiple founder-led companies as a deliberate strategy to counteract the inherent slowness of a large SaaS business. This injects a startup's pace and an AI-native mindset directly into the organization to accelerate its AI transformation.

To ensure their competitive moats endure in the age of AI, software incumbents must execute a three-step plan: 1) Replatform their tech stack to eliminate legacy debt, 2) Define an organic and M&A roadmap for AI features, and 3) Develop a clear strategy to price and charge for new AI functionality.

The traditional wisdom to "build what's core" to your business is becoming obsolete for AI. The immense cost and rapid advancement of foundational models by major labs mean most companies are better off buying or partnering for core AI capabilities rather than attempting to build them in-house.

The initial AI rush for every company to build proprietary models is over. The new winning strategy, seen with firms like Adobe, is to leverage existing product distribution by integrating multiple best-in-class third-party models, enabling faster and more powerful user experiences.

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.

In a fast-moving field like cybersecurity, it's impossible to build everything in-house. By treating M&A as an extension of the R&D department, a large company can leverage the venture-backed ecosystem to acquire innovative teams and products that are already validated.

Forgo building custom AI tools for common problems. Instead, purchase 90% of your AI stack from specialized vendors. Reserve your in-house engineering resources for the critical 10% of tasks that are unique to your business and for which no adequate third-party solution exists.