{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Make It Real","title":"Why Context Matters More Than AI Models with Jennifer Hamel | IDC","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/a0e922a6\"></iframe>","width":"100%","height":180,"duration":1686,"description":"\nHaving the right data and AI models doesn't always translate into business results. What if the missing piece is understanding how your business actually works?\nIn this episode, Shirley Macbeth sits down with Jennifer Hamel, Research Vice President of Enterprise Data and AI Services at IDC, to explore why business context is essential to successful enterprise AI. Jennifer shares insights from IDC's research on what separates organizations generating measurable AI value from those still stuck in experimentation.\nThey discuss how organizations can turn fragmented data and institutional knowledge into reliable AI capabilities. Jennifer explains how knowledge graphs, ontologies, and semantic layers help AI agents make better decisions, why capturing employee expertise matters, and how human oversight must evolve as AI becomes more autonomous. They also explore the importance of governance, cross-functional collaboration, and the right expertise in scaling AI and delivering measurable business outcomes.\nKey takeaways:\nWhy business context is essential for reliable, scalable enterprise AI\nHow knowledge graphs, ontologies, and semantic layers improve AI decision-making\nWhy capturing tribal knowledge and unstructured data is critical to AI success\nHow human-in-the-loop and human-on-the-loop approaches are changing work\nWhy employee involvement and cross-functional collaboration matter for AI adoption\nHow governance, domain expertise, and operating models support AI at scale\nWhere organizations should start to move beyond AI pilots and deliver measurable business value\n\nHighlights:\n(00:00) Introducing Jennifer Hamel\n(01:54) What context really means for AI\n(04:30) How knowledge graphs and semantic layers connect data\n(08:56) Unlocking unstructured data and tribal knowledge\n(11:08) Why employees are essential to AI transformation\n(12:54) Human-in-the-loop vs. human-on-the-loop\n(16:10) Overcoming organizational barriers to AI adoption\n(18:52) Combining technical expertise...","thumbnail_url":"https://img.transistorcdn.com/so5OTSq46YfRugk-cTEuZVYVmQtV6JqyaqiLzdGUNSQ/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8zODBj/NDFlYTA2NWMyYmQ5/NWFiZDQ4MzllYjQ4/ODMyYS5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}