Everybody says they're data-driven.

But according to a Harvard Business Review study, only 7% of enterprises believe their data is actually ready for AI. Not agents. Not advanced machine learning. Just AI.

Everyone wants the outcome. Far fewer have done the years of work required to make AI useful in the first place.

But Matt Pappas has.

As Chief Data Officer at Kiewit, he's spent more than 15 years building production machine learning systems that influence billion-dollar decisions, risk assessments, and project forecasts. His team deployed its first company-wide production algorithm in 2017, years before most organizations had even formalized a data strategy.

This isn't a conversation about chasing the next breakthrough. It's about what "AI-ready" actually means, why data science remains a craft, how Kiewit uses machine learning to make better decisions, and why Matt believes technology should solve business problems instead of going looking for them.

The companies pulling ahead aren't necessarily the ones with the newest models. They're the ones who started taking data seriously long before everyone else had to.

The AI Proving Ground Podcast leverages the deep AI technical and business expertise from within World Wide Technology's one-of-a-kind AI Proving Ground, which provides unrivaled access to the world's leading AI technologies. This unique lab environment accelerates your ability to learn about, test, train and implement AI solutions. 

Learn more about WWT's AI Proving Ground.

The AI Proving Ground is a composable lab environment that features the latest high-performance infrastructure and reference architectures from the world's leading AI companies, such as NVIDIA, Cisco, Dell, F5, AMD, Intel and others.

Developed within our Advanced Technology Center (ATC), this one-of-a-kind lab environment empowers IT teams to evaluate and test AI infrastructure, software and solutions for efficacy, scalability and flexibility — all under one roof. The AI Proving Ground provides visibility into data flows across the entire development pipeline, enabling more informed decision-making while safeguarding production environments.