AI Investing: Speed Trumps Strategy in the Age of GenAI

At the SaaStr AI Summit 2025, Bessemer Venture Partners' Talia Goldberg and Google Cloud's COO Francis Duza discussed the rapid adoption of AI and its impact on investment strategies.

The Speed Revolution

Speed of execution is now paramount. As Talia Goldberg explains, early-stage competitive moats are less about traditional advantages and more about adaptability in this fast-paced market. "The number one thing that we look for in teams is speed of execution," she states.

At the earliest stages, you really don’t have moats. You have teams you’re building, and how fast you can move and adapt to this rapidly changing market is so critical.

Francis Duza echoes this sentiment, noting the unprecedented adoption rate of AI across industries. "In my three decades plus in tech, this is the fastest I’ve seen adoption of any technology ever," he observes, citing Verizon, Seattle Children's Hospital, and Toyota as examples of rapid enterprise adoption.

Labor Budget: The New Frontier

AI is shifting the focus from software budgets to labor budgets. Goldberg notes, "Markets used to tap into just software budget. We’re now seeing that change into labor budget." This expands the addressable market significantly, as labor represents a much larger portion of company budgets than software.

Healthcare, traditionally slow to adopt new technologies, is leading the charge in AI implementation due to its potential for labor cost savings. Companies like Abridge are demonstrating this by securing substantial contracts with hospitals through AI-powered automation of tasks like medical scribing.

Enterprise Leading the AI Revolution

Large enterprises are surprisingly at the forefront of AI adoption. Duza observes, "We’re seeing large companies lead the revolution as much as digital natives." This is driven by the immediate and significant cost savings AI can deliver.

The Multi-Model Future

A multi-model approach is key to success in the AI landscape. Duza emphasizes the importance of platform openness, stating, "We don’t believe there’s going to be one model to rule them all." Google's Vertex AI platform supports numerous models from various vendors, reflecting this belief.

Google's AI Strategy and Startup Opportunities

Google is focusing on infrastructure, core models, and select horizontal applications. This leaves significant opportunities for startups in vertical markets, specialized workflows, and industry-specific solutions.

  • Google's Focus: Infrastructure, Core Models, Horizontal Applications
  • Startup Opportunities: Vertical Applications, Specialized Workflows, Industry-Specific Solutions

The New Venture Math: Leverage and Scale

AI empowers small teams to achieve unprecedented scale. Duza highlights the potential for even small teams to become major players, citing Cursor's impressive revenue with a lean team.

The Importance of Data

High-quality, contextual data is crucial for AI advancement. Goldberg emphasizes the importance of "conversational data," and companies like Recall AI are building infrastructure to capture and structure this data.

Key Takeaways for SaaS Leaders

For CEOs and Founders:

  • Prioritize speed.
  • Focus on labor replacement.
  • Embrace model diversity.
  • Specialize.

For Investors:

  • Prioritize execution speed.
  • Consider labor budget TAM.
  • Assess platform risk.
  • Focus on category creation.

Conclusion

The companies that will thrive in the age of AI are those that embrace speed, focus on labor transformation, and build for a multi-model future. The opportunity is vast, but the pace is relentless. Adaptability and rapid execution are essential for success.