The AI Investment Opportunity

A year ago, it was all demos.
Slick UIs over OpenAI APIs.
Pitch decks with “copilot” slapped on every slide.

And then something shifted.

The demos started getting real.
The LLM wrappers started becoming businesses.
And investors? We started asking harder questions.

• Where’s your data advantage?
  
• What makes your model performance matter?
  
• Are you selling workflow enhancement or actual infrastructure?
  
• Is your product intelligence... or just integration?
  
  

At Growth Warrior Capital, we believe AI is no longer just a category.

It’s the substrate.

It’s the layer touching every tool, every workflow, every human system that matters in the enterprise.

But to invest well in AI right now, you need to look past the hype and into the bones of the businesses being built.

Let’s talk about what we’re seeing—and why we believe the biggest AI wins are still ahead.

Pattern #1: AI Is Eating the Enterprise… But Not All at Once

We’re not looking for ChatGPT-for-X.

We’re looking for companies solving real enterprise problems with AI-enhanced infrastructure.

That looks like:

• Data-rich verticals where the pain is high and the context is messy
  
• Founders with operational depth, not just ML certificates
  
• Workflows where intelligence makes decisions faster, safer or cheaper
  
  

Some of our best-performing investments right now are in spaces like:

• Law enforcement intelligence
  
• Financial compliance
  
• Field operations analytics
  
• Industrial supply chain management
  
  

Not sexy.
Not Twitter-friendly.

But deeply consequential.

Pattern #2: The Moat Is the Data… and the Distribution

Every AI company needs two things:

1. Proprietary data no one else has
   
2. A wedge into behavior or workflow
   
   

If you don’t have those? You’re just another UI layer waiting to be replaced by the next API update.

The best founders we back are:

• Starting with domain-specific use cases
  
• Collecting unique signals from underserved workflows
  
• Using AI not as a feature, but as an engine for decisions
  
  

One portfolio company unlocked a go-to-market motion by embedding into compliance workflows where errors cost millions. Another embedded into frontline worker apps with offline sync—training models on what the cloud never sees.

That’s where the defensibility is.

Pattern #3: Builders Will Beat Tinkerers

We’re over the demo phase.
We’re past the playground.

The next generation of AI companies will be led by:

• Engineers who’ve built at scale
  
• Operators who’ve scaled broken systems
  
• Technical founders with a POV on architecture, not just user experience
  
  

We look for founders who understand:

• The limitations of models
  
• The nuance of deployment
  
• The ROI math for buyers
  
  

If you don’t know the difference between inference latency and training cost, we’re probably not a fit.

If you do—and you’ve seen how a small model trained on deep data can outperform a flashy foundation model—let’s talk.

Our Investment Focus

We’re investing at Seed and Series A in companies building:

• AI-powered systems for the enterprise
  
• Software that replaces static tools with adaptive infrastructure
  
• Products where AI enhances not just the UX, but the outcome
  
  

Our thesis is simple:

The AI winners of this decade won’t be wrappers.
They’ll be re-writers—of the entire stack.

And we’re here for it.

Building something intelligent?
[Submit your deck →]We’re ready to meet the founders shaping the next generation of enterprise productivity.