KNOWLEDGE PORTAL

What Most Industries Are Still Missing About Generative AI

Summary

Introducing: Notes from the Hill

 

Perspectives from Rob Buller, Founder of Cyberhill Partners

 

At Cyberhill, we’ve always believed that solving the hard problems—whether in cybersecurity, AI, or enterprise architecture—starts with asking better questions.

 

Notes from the Hill is where we dig into those questions.

 

Authored by our founder and technology strategist Rob Buller, this blog explores what’s really going on behind the buzzwords—across AI, cybersecurity, data governance, and the architecture that powers modern enterprises. You’ll find thoughts on what we’re seeing in the field, what’s working (and what’s not), and how organizations can get ahead of what’s coming next.

 

These notes are short, sharp, and built for leaders who don’t have time for fluff. Whether you’re a CISO, CIO, enterprise architect, or transformation lead—this series is for you.

What Most Industries Are Still Missing About Generative AI

Industry giants—Google, Amazon, Apple, Microsoft, Netflix, and Tesla—aren’t just deploying generative AI. They’re profiting from it.

These companies are operating with a different kind of infrastructure. Behind the scenes, their AI strategies are deeply embedded into how they operate, generate revenue, and engage with customers. They’re not just running large language models—they’ve built ontologies, knowledge graphs, context engines, and strong data governance frameworks. It’s not accidental that they move faster or make smarter decisions at scale. It’s structural.

Meanwhile, in sectors like government, healthcare, hospitality, and retail banking, we’re not seeing the same story. The use of generative AI remains isolated—pilots here, experiments there—but it hasn’t reached operational scale. And that’s where the opportunity lies.

So, what’s missing?

The flashiest part of AI is the output—but the heavy lifting happens before that. When I meet with teams trying to scale AI, the same core gaps come up over and over again.

These are the systems Big Tech has quietly invested in for years:

  • Ontologies – to create shared language and meaning across data systems
  • Knowledge graphs – to unify information from different sources and surface relationships
  • Context engines – to keep outputs relevant, timely, and business-aware
  • Data governance – to ensure trust, consistency, and compliance
  • Connectors – to actually make this work across existing systems and workflows

These are foundational. But in a lot of sectors, they’re still being treated like optional add-ons—or worse, afterthoughts.

A simple example with billion-dollar implications

A bank’s AI model spots a $556/month auto loan. It recommends selling the car via Bluebook, netting the customer $2,500, and rolling them into a new, better loan—right through that same bank. Multiply that by a million customers.

That’s not just insight. That’s billions in potential loan originations.

This is the kind of downstream value generative AI can unlock—if the right systems are in place.

The opportunity ahead

Most sectors—public and private—are still figuring this out. The technology’s available. The strategies are known. What’s missing is the structure to support it.

And that’s where we focus at Cyberhill—helping organizations build the architecture for AI that doesn’t just run, but returns value.

Generative AI isn’t the goal—it’s a tool. The real work is what we do with it.

You might also be interested in
Cyberhill Named Global Best Companies to Watch in 2025, The Silicon Review
Cyberhill is recognized by The Silicon Review as a Global Best Company to Watch in 2025 for its leadership in secure, scalable, and smart enterprise AI solutions.
LEARN MORE
Ontologies: The Keystone of Enterprise AI
Rob Buller, Founder of Cyberhill Partners, explains why ontologies are the keystone to scalable, future-ready AI strategies.
LEARN MORE
How Ontologies and Knowledge Graphs Power the Future
Unlocking Trustworthy AI: How Ontologies and Knowledge Graphs Power the Future of Intelligent Enterprises
A white paper by Cyberhill Partners exploring how ontologies and knowledge graphs unlock trustworthy enterprise AI. Learn how semantic infrastructure drives explainability, accuracy, and business value.
LEARN MORE