What You Should Build With AI?

What You Should Build With AI—An Analysis of 400+ AI Startups Backed by Y Combinator

“Be careful what you let become critical to you. Try to get yourself into situations where the most urgent problems are ones you want to think about.”
— Paul Graham

The Search for Good Use Cases in AI

If you’re wrestling with the question, “What should I create with AI that stands a strong chance for success?”, this article offers a data-driven perspective. By looking into Y Combinator (YC)—widely viewed as a leading indicator in the startup ecosystem—this deep dive sheds light on what kind of AI-focused ventures attract investments and why.

Advertisement

Y Combinator’s impressive track record in spotting and nurturing successful startups has reshaped entire industries. Their portfolio stands as a potent signal for emerging technologies and disruptive solutions. Given artificial intelligence’s transformative possibilities, I decided to dig into YC’s AI-centered companies to uncover:

1. Hot industries and sectors for AI startups
2. Which AI use cases and applications investors find appealing
3. The backgrounds of successful AI founders
4. Additional themes such as AI Safety, accessibility, explainability, and more (detailed in the original post)

I gathered and analyzed information on 417 AI-oriented companies from Y Combinator’s 2023 and 2024 cohorts.

Objectives of This Analysis

• Which industries are drawing the most AI innovation?
• What AI apps are grabbing investor attention?
• Which founder traits are common in YC-backed AI startups?
• Practical insights to help you decide what to build with AI.

Note: Y Combinator invests $500,000 for a small equity stake in each accepted startup. Over three months, founders receive mentorship and resources to accelerate product and user growth. By analyzing YC’s AI startups, we get a valuable window into emerging AI trends.

Data Collection

I obtained information from YC’s Startup Directory for the 2023 and 2024 Summer and Winter cohorts. After filtering for AI-focused ventures, I cleaned the data and categorized each startup by sector, verifying tags from company descriptions to capture their core focus.

In total: 417 AI startups were identified, with details such as:

• Founders and their backgrounds
• Startup URLs
• Sector/category tags
• Descriptions of company focus

For those seeking the complete dataset or a curated subset, you can find it at [the link in the original article] or via the newsletter mentioned.

Snapshot: 417 AI-Focused Startups

Where Is AI Innovating the Most?

Leading industry intersections with AI (approximate percentages):

1. Healthcare/Biotech (10.8%) — 45 companies
   • Example: Elythea, applying machine learning to lower maternal mortality
2. Fintech (9.1%) — 38 companies
   • Example: Arcimus, AI-based premium audits for insurance
3. Developer Tools (8.9%) — 37 companies
   • Example: Sudocode, offering AI services for dev teams
4. Sales/Marketing (8.2%) — 34 companies
   • Example: MicaAI, helping streamline sales processes
5. Education (4.3%) — 18 companies
   • Example: Studdy, an AI-driven tutor

B2B vs. B2C

• B2B: ~338 startups (81.1%)
  • Examples:
    • GigaML: On-premise large language model deployments
    • Constructable: AI assistant for construction workflows
    • AiSDR: AI-driven sales outreach platform
    • Corgea: Automated fixes for vulnerable code in enterprise software
• B2C: ~79 startups (18.9%)
  • Examples:
    • Rex: AI-powered personal fitness and nutrition advice
    • PocketPod: AI-generated podcasts customized by user interests
    • Shortbread: “Netflix for comics” leveraging AI
    • Roame: AI-based travel planning and booking

Key Takeaways

1. Enterprise Solutions Dominate: Around 80% focus on B2B offerings, highlighting strong investor confidence in business-facing AI products.
2. Consumer Sector Is Underserved: Fewer than one in five AI startups target a mass consumer audience—potentially indicating a gap for promising consumer-focused applications.
3. Technical Backgrounds: Many founders have deeply technical expertise (74.8%, based on the original dataset), which likely steers them toward solving specialized B2B problems.

Concluding Thoughts

Y Combinator’s AI cohort reveals that enterprise solutions remain the prevailing path for AI startups, especially in domains like healthcare/biotech, finance, and developer tools. These categories demonstrate robust investor interest due to the immediate value AI can add in automating tasks, improving decision-making, or creating data-driven insights.

While B2C AI startups are comparatively fewer, that scarcity might indicate openings for consumer-related applications—if founders can effectively tackle user acquisition, monetization, and product-market fit challenges.

Overall, if you’re wondering “What should I build with AI?” the data suggests looking toward sectors with demonstrated B2B traction or exploring underrepresented consumer niches. In either case, a strong technical edge and an intimate understanding of your target market’s pain points appear crucial for success.