SaaStr Annual 2024: Mastering Growth in the AI Era: How to Stand Out, Acquire Customers, and Raise VC Dollars with Glasswing Ventures, Zetta Venture Partners, and B Capital Group

The AI wave has created a new paradigm in enterprise software, and companies worldwide are investing billions in new technologies across a variety of use cases. For startups looking to capitalize on this opportunity, an effective differentiation strategy is more important than ever to attract enterprise customers and raise outside capital. This panel session features Rudina Seseri, Founder and Managing Partner of Glasswing Ventures; Jocelyn Goldfein, Managing Director and General Partner of Zetta Venture Partners, and Karen Page, General Partner at B Capital Group for a dive into the shifting fundraising environment around AI technologies, what VCs look for when investing in AI-enabled companies, and how such companies can acquire customers and scale a truly valuable and viable product.

1. Mastering Growth in the AI Era: How to Stand Out, Acquire Customers, and Raise VC Dollars Karen Page General Partner B Capital Jocelyn Goldfein Managing Director Zetta Venture Partners Rudina Seseri Founder & Managing Partner Glasswing Ventures

2. What does AI success look like in practice? Route optimization systems saving millions of gallons of fuel per year. Content r ecommendation e ngines retaining $Billions in top-line revenue. GenAI assistants handling most customer service chats, the work of hundreds of agents.

3. While most enterprises are experimenting with AI, few have developed best practices at scale 73% of organizations using AI have made no changes to their data strategy for production use cases 1 lack an enterprise roadmap for GenAI 2 p lan to outsource or buy AI talent externally 3 57% 62% Sources: 1 Harvard Business Review (2024), 2 McKinsey (2024). 3 Adecco Group (2024)

4. …b ut it is extremely difficult to retrofit into existing systems The advantages of AI are undeniable…

5. With thousands of AI startups in the market, it takes more than tech to stand out 1 Source: Pitchbook data

6. Don’t throw out the SaaS playbook: Attach to KPIs with budget Fit into existing workflows Clearly communicate value New AI considerations: AI products evolve over time Performance metrics and errors need to fit use case Building a moat requires investments in data infrastructure

7. When it comes to commercial applications of AI, the buck stops with business value

8. VCs are looking beyond quick wins Differentiated technology or unique ensemble of existing algorithms Long-term data moat – at deployment or over time Domain understanding of the vertical, dependent on founder execution Addressing a high-value area : can the problem already be solved by traditional SaaS?

9. AI is moving up the chain, transforming the business core 1 Source: MIT Technology Review (2024)

10. AI is the future of enterprises, but most solutions are superficial An intentional AI strategy is necessary to solve critical challenges and unlock real value

11. Key Takeaways

12. THANK YOU!