AI in Action

In this AI in Action episode, David Levy speaks with Lorie Meola about how IBM is transforming procurement through AI adoption and data management. Lorie explains how focusing on good-enough enterprise data, supported by data transparency and data visualization, leads to faster insights and better decisions.

She shares how agentic AI helps teams move away from manual work and focus on higher-value outcomes. The conversation also highlights the cultural change required for digital transformation, including leadership support and iteration. The episode shows how modern procurement can drive efficiency, insight and business impact across the enterprise.

Inside IBM's Client Zero journey: https://ibm.biz/BdbW4b

In this AI in Action episode, David Levy talks with Yashodha Bhavnani, Head of AI at Box, about how enterprises can turn massive volumes of unstructured data into high-value intelligence.

Yashodha explains how Box is embedding AI into its content platform for easier data management without compromising security or governance. She shares real-world examples of enterprise content management and explains how agentic AI powers smarter workflows.

The conversation also covers the role of IBM watsonx® in Box AI and what it takes to bring AI from experimentation into production.

Explore the partnership → https://ibm.biz/BdbTR7

In this AI in Action episode, David Levy talks with Alon Cohen about how the UFC has turned its deep history of data into clear, meaningful insights. Alon shares how the team has moved from basic number tracking to smart systems powered by machine learning, computer vision and NLP. Thanks to better data management and processing, the team can measure speed, power and even fighter intent with far more accuracy.

He explains why combat sports are challenging in terms of AI and data analysis, and how IBM watsonx® helps deliver real-time insights to fans and commentators. The episode also covers why building good AI takes patience, steady improvement and the careful judgment of people who truly understand the sport.

0:00 Intro
04:11 Understanding MMA athletes and the culture
07:17 Identifying the opportunity for statistical analysis in UFC
09:28 The challenges of AI with real-time fight data
16:24 How the UFC uses IBM watsonx® to power UFC Insights
21:34 What data reaches UFC commentators
25:14 How IBM and UFC built and trained the models
31:08 How UFC measures the success of AI-driven fan experiences
34:02 Advice for businesses advancing with AI

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

Can agentic AI solve the scalability challenge in wealth management while expanding access to underserved communities?

Ramona Ortega believes it can, but only with the right foundation. She explains how WealthBuild has moved from basic chatbots to RAG and now to agentic workflows that can deliver accurate and personalized guidance at scale. In her opinion, the real blockers aren’t algorithms but messy data, governance gaps and enterprise-grade security.

Since traditional financial services can’t reach many everyday consumers, she partners with community banks to close the gap. For her, the future lies where AI, APIs and blockchain meet, opening the door to accessible and democratized financial advice.

Explore the podcast → https://ibm.biz/BdbuaR

Explore the podcast → https://ibm.biz/Bdbbwt

Every company is sitting on a mountain of data, but only a few know what to do with it. In this episode of AI in Action, Madison Faulkner talks with David Levy about turning data chaos into clarity. She explores how agentic AI depends on strong data management and data governance, and why unstructured data and big data only create value when they’re organized with purpose. In other words, the real competitive edge isn’t the AI itself; it’s the data behind it. Because in the end, intelligent systems are only as powerful as the data that trains them.

0:00 Intro
1:35 Madison Faulkner’s journey
2:40 The birth of data science
4:00 Bridging Silicon Valley hype with real-world industries
8:40 Structuring unstructured data for agentic AI
12:00 Automation, knowledge graphs and agentic sourcing
16:40 Tactical and organizational failures in data strategy
20:30 Data as code: The next wave of infrastructure
24:00 Rethinking data foundations for agentic AI
30:12 Turning data governance into a real business advantage
33:45 Final takeaways: Clarity over chaos in the AI era

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.

AI news is moving fast. Keep your business ahead with updates about AI advancements, strategies and expert perspectives → https://ibm.biz/Bdbbw6

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