AI in Action

IBM
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AI in Action explores what it takes to put artificial intelligence into action across a rapidly evolving business and tech landscape. Each episode focuses on responsible AI implementation and real-world business challenges, examined through a practical use case lens.

  1. 2月24日

    Foundation models accelerate space and climate science

    On AI in Action, IBM researcher Campbell Watson explains how foundation models are accelerating discovery across Earth and space science. Moving beyond traditional numerical methods, his team applies concepts from large language models to multimodal satellite data to build powerful, open-source AI systems.   In collaboration with NASA and the European Space Agency, they have developed foundation models for Earth observation, weather and heliophysics. They are using AI for sustainability use cases, such as flood detection, biodiversity monitoring and solar flare forecasting.   Designed for hybrid cloud environments and even deployed in orbit, these models point toward a future where AI and quantum computing unlock deeper planetary insights.

    39 分鐘

  2. 2月10日

    Turning AI into business impact through data and strategy

    In the latest episode of AI in Action, Bernard Marr shares his perspective on how AI is changing the way we work and why AI literacy is becoming essential for every organization. He explains that real AI-driven business growth starts with a clear strategy. To make AI work at scale, companies need strong data foundations, modern data architecture and solid data management practices. Many organizations still struggle with siloed systems, weak governance and low data literacy, which hurts their competitive edge. Bernard encourages leaders to connect business intelligence with AI goals, rethink existing processes and give teams space to experiment. From agentic AI to quantum computing, he reminds us that change is happening fast and that a thoughtful, strategic approach to AI is key to building future-ready organizations. 0:00 Intro 03:47 What AI really means for companies in 2026 06:47 Scaling AI starts with strategy 10:42 Leading the cultural shift to AI 13:17 Competitive advantage starts with AI awareness 18:14 The real barriers to scaling AI 28:33 What enterprises can learn from AI startups 30:58 Top trends for data and AI leaders 34:24 Overcoming data and governance challenges 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/BdpEkq

    38 分鐘
  3. Thoughtful AI integration at the Recording Academy

    1月27日

    Thoughtful AI integration at the Recording Academy

    The Recording Academy is thoughtfully integrating generative AI to improve efficiency, accuracy and fan engagement across the GRAMMYs. David Gregory, CIO of the Recording Academy, describes using AI solutions, machine learning and large language models to streamline the GRAMMY Awards submission and voting process while preserving human oversight and strong AI governance.   Fan-facing tools like GRAMMY IQ, an AI-powered chatbot, enhance grammy.com through interactive trivia and historical insights. Collaborating with IBM and others, the Recording Academy is exploring AI agents and advanced analytics across archives, membership platforms and operations. Their overall vision is to drive innovation balanced with responsibility, creativity and trust. 0:00 Intro 05:01 How GRAMMY IQ elevates the fan experience 06:43 Beyond GRAMMY IQ: The future of AI at the GRAMMYs 12:10 Leading the AI initiatives with caution and clarity 17:43 Driving member value with AI and digital transformation 21:54 Operationalizing AI across the Recording Academy 25:08 What every CIO should know about getting started with AI 27:14 What’s next for AI at the Recording Academy 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.

    28 分鐘

  4. 1月13日

    How IBM uses data and AI to modernize procurement

    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

    35 分鐘
  5. Making enterprise content actionable with AI

    30/12/2025

    Making enterprise content actionable with AI

    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.

    33 分鐘

  6. 16/12/2025

    How UFC uses AI to turn data into real-time insights

    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.

    36 分鐘

  7. 02/12/2025

    Bringing smarter, accessible wealth management through agentic AI

    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

    43 分鐘

  8. 18/11/2025

    The power of AI starts with better data

    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 #DataStrategy #EnterpriseAI #AIforBusiness #DataLeadership #BusinessIntelligence #AgenticAI #DataDrivenBusiness #DataManagement #MadisonFaulkner #DavidLevy

    35 分鐘
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預告

關於

AI in Action explores what it takes to put artificial intelligence into action across a rapidly evolving business and tech landscape. Each episode focuses on responsible AI implementation and real-world business challenges, examined through a practical use case lens.

資料

  • 創作者
    IBM
  • 活躍年份
    2024年 - 2026年
  • 單集
    43
  • 分級
    兒童適宜
  • 版權
    © IBM
  • 節目網站
    AI in Action

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