Stop Treating Gen AI Like a Calculator! 🧮❌

Are you measuring your AI by the wrong metrics? 🛑

Most enterprises make the fatal mistake of treating Generative AI like a glorified calculator. They expect a deterministic, 100% accurate tool where the square root is always the square root. But Gen AI doesn't work on certainty—it thrives on probability.

In this clip, we break down why chasing 100% accuracy is stalling your digital transformation, and why your business value framework needs an immediate rewrite.

📈 The 70% Rule: The Billion-Dollar Amazon Blueprint
Look at how the world’s most advanced cloud and retail infrastructures deploy machine learning:
- The Investment: Amazon invested billions of dollars into its product recommendation systems.
- The Reality: The system is only 70% right at predicting what a customer will buy.
- The Impact: It remains in production because it is vastly superior to any legacy alternative and drives over $10 billion in incremental revenue.

☁️ Enterprise & Public Sector Takeaway
Whether you are deploying large language models (LLMs) on Google Cloud, building secure architecture for the Google Cloud Public Sector, or scaling internal enterprise tools, success isn't defined by technical perfection. It is defined by business impact.

Stop waiting for flawless data. If a probabilistic system outperforms your manual alternative and moves the bottom line, it belongs in production. Shift your KPIs from technical metrics to organizational value and unlock true scale.
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Q - Do you find that the non-deterministic part of gen AI confuses people? - Jeff Frick
A - What's the comparison? What are we measuring against? - Aaron Vermeersch

Enterprises will say, I need my AI to be 100% right. You don't, you don't even need it to be 90%. - Aaron Vermeersch

You don't measure AI whether or not it should be in prod on the technical metrics, but the business impact. If I'm 70% right but you and I are making $10 billion more a year, I think we're going to put it in prod. - Aaron Vermeersch
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I don't have to outrun the bear. I just have to outrun you.

What's the compare? What's the objective? Increase X by Y probably doesn't require perfection.

Start from outcomes. Measure against the alternatives.

Be rigorous in your processes, and disciplined where it matters most.

But I bet you can find plenty of easy friction points just laying around, waiting to be smoothed, reduced, automated, or perhaps even processed away.

Thanks for the conversation. Loved the framing - validated in the field with customers.

Full length conversation
What it really takes to scale AI in the enterprise | Google Cloud Next 2026
Aaron Vermeersch sits down with Jeff Frick
https://youtu.be/d1NdmMYr9ys?si=oPUIKmwa3T9q_ajg&t=97

🏷️ #GenerativeAI #GoogleCloud #GoogleCloudPublicSector #EnterpriseAI #DataAnalytics #MachineLearning #CloudComputing #AIStrategy #DigitalTransformation #AmazonWebServices #TechLeadership #AIROI

Видео Stop Treating Gen AI Like a Calculator! 🧮❌ канала Turn the Lens with Jeff Frick