Insights

The Governance-First Approach to Closing the AI Gap

Author: Sharon Loh

If you talk to leaders, you’ll hear the same story. Excitement about AI isn’t the problem. Turning that excitement into something secure, measurable, and sustainable is. 

Many companies find themselves in a kind of perfect storm: rising financial pressure, mounting complexity, and real uncertainty about where to even start. Pilots get launched without governance, security, or change management in place, and momentum stalls before value ever shows up. 

A governance-first approach helps organizations move from scattered AI experiments to a focused, business-first roadmap. 

In this video, Patrick Tang, our VP of Strategic Partnerships, walks through the biggest barriers companies face in AI adoption, how his team helps customers work through them, and where AI adoption is headed next to deliver real, measurable business outcomes. 

Timestamps 

00:22 Patrick’s background and current role 

02:36 Challenges in AI adoption 

06:03 Key steps to address these challenges 

09:53 Key trends shaping AI adoption in the year ahead 

12:49 Three key takeaways for customers thinking about AI adoption 

What Worked for Patrick’s Team 

• Start with an AI Readiness Diagnostic. Every engagement opens with an examination of strategy, governance, talent, data, and technology foundations, before any tool gets selected. 

• Identify quick wins with a value-impact matrix. Use cases like document retrieval automation, claims processing, or customer inquiries are prioritized to show ROI within 90 to 120 days, building early momentum and executive confidence. 

• Right-size the model to the task. Not every use case needs a large, expensive LLM. Smaller, fine-tuned models often perform better and cost far less, backed by FinOps practices like token optimization and transparent per-query costing. 

Insights from Patrick 

“The biggest challenge enterprises face today is not excitement about AI. It’s the struggle to turn that excitement into secure, measurable, and sustainable value.”

“AI only works when the foundation is strong. That’s why we take a governance-first, value-driven approach that makes AI predictable, measurable, and genuinely useful. Governance creates safety, and safety accelerates innovation.”

“For businesses adopting AI, the real differentiator is discipline and not hype. Success should be measured not by model accuracy, but by outcomes like time saved, cost avoided, or workflows automated.”

Ready to turn your AI project into measurable business impact? We can help. Let’s connect.