Join us at our next event - Inside: Union Square Ventures (Tomorrow - June 12)
A few weeks ago at our NY Vertical AI Summit, leaders from venture capital, enterprise innovation, and early-stage startups shared their perspectives on how generative AI is transforming industry-specific software. Here are the standout insights from the event:
1. Vertical AI is Expanding Software’s Reach
Somak Chattopadhyay (Armory Square Ventures)
LLMs are unlocking new use cases in regulated and language-heavy industries, massively expanding TAM beyond traditional SaaS. Unlike early vertical SaaS, vertical AI taps into core language-based workflows, enabling transformation in areas like healthcare, legal, and financial services.
2. Build vs. Buy: GenAI Changes the Game
Legacy “build vs. buy” decisions matter less; differentiation now comes from how closely teams align themselves with AI capabilities. Even off-the-shelf solutions can drive competitive advantage if organizations deeply understand and integrate AI into their workflows.
3. AI Adoption: Focus on Use Cases
Tony Jones (Creative AI Academy)
Many organizations jump into AI without clear goals. Adoption only succeeds when teams start by defining the problem they’re solving before choosing tools or training models.
4. Evolve Beyond Traditional Metrics to Benchmark AI
We need new ways to evaluate AI—not as a tool, but as a dynamic job function with performance benchmarks. AI should be assessed like a human hire, based on its ability to handle nondeterministic workflows and generate novel outputs.
5. Workflow, Data, and Compliance Moats
Defensibility in vertical AI requires domain-specific data, embedded workflows, and deep regulatory alignment. In industries like life sciences, capturing business logic and maintaining compliance creates strong moats and high switching costs.
6. AI Execution for Complex Workflows Matters
It’s not enough to just generate insights, AI must also guide next steps and enable execution in real business processes. In security and compliance, workflow automation is critical to turning data into decisions and maintaining operational readiness.
7. Choose Value Over Valuation
The right investor adds more than just capital. Founders should prioritize strategic value and long-term fit over chasing the highest valuation, especially at early stages.
8. The AI Funding Landscape is Changing Rapidly
The capital stack is compressing. Startups are hitting revenue, traction, and valuation milestones at earlier stages, which is shifting how and when founders need to think about raising their next round.
9. Responsible Investment and AI Ethics Are Critical
IBM’s approach centers on investing in use cases and not just algorithms, ensuring alignment with internal ethics standards. Every AI deployment is vetted through their ethics board, balancing innovation with responsible governance.
The Vertical AI Summit made it clear: success in this new wave of AI requires domain depth, clear use cases, and responsible execution. As the landscape evolves, founders and investors alike will need to adapt faster than ever.
Upcoming Lynx Collective Events
June 12 - Inside: Union Square Ventures
June 18 - NYC VC Investors - Summer Rooftop Mixer (VCs only)
July 2 - AI Builders Lunch w/Next Wave NYC
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