The AI in Business Podcast

Daniel Faggella
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Apr 24, 2024 • 23min

Tracing AI and Natural Language Processing's Journey to the Mainstream - with Matt Berseth of NLP Logix

Matt Berseth, Co-founder of NLP Logix, discusses the evolution of AI in the last decade, the importance of natural language processing in various industries, challenges in tech adoption, and the future integration of AI in software development.
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Apr 23, 2024 • 24min

Solving Human Resource and Client Services Challenges with AI - with Bill Armstrong of Moss Adams

Bill Armstrong, Chief Innovation Officer at Moss Adams, discusses the impact of AI on HR practices and the future of human resources. Topics include hurdles in AI adoption, adapting HR to AI, enhancing training processes with Generative AI, and critical thinking in education and accounting.
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35 snips
Apr 17, 2024 • 38min

Guidance for Procurement Leaders in Recovering Supply Chains - with Edmund Zagorin of Arkestro and Len DeCandia of Johnson & Johnson

Edmund Zagorin of Arkestro and Len DeCandia of Johnson & Johnson discuss procurement challenges, talent acquisition, data accuracy, and the impact of global geopolitical challenges on supply chains. They emphasize the transformative potential of AI in procurement, predictive maintenance, and the importance of storytelling for AI adoption.
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Apr 16, 2024 • 20min

Tires and Data Collection for Autonomous Vehicles - with Chris Helsel of Goodyear

Chris Helsel from Goodyear discusses the impact of self-driving cars on industries. Topics include tire intelligence for autonomous driving safety, challenges of interconnected autonomous vehicles, and revolutionizing box truck deliveries with real-time tire data insights.
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9 snips
Apr 14, 2024 • 25min

GenAI for CX, Cybersecurity, Fraud Detection, and Marketing Workflows in Insurance - with Dr. John Almasan of TIAA

Dr. John Almasan from TIAA explores AI in insurance focusing on governance, talent, and innovation. Topics include customer experience, fraud detection, and marketing workflows. They discuss generative AI for risk management and personalized client services in the insurance sector.
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Apr 9, 2024 • 21min

AI for Supply Chain Challenges in Life Sciences - with Shreyas Becker of Sanofi

Shreyas Becker from Sanofi discusses using AI to tackle supply chain challenges in life sciences. Topics include real-world evidence delivery, sharing sensorial data with big tech, and how data drives problem-solving. The podcast sheds light on the complexities of bio manufacturing, standardization challenges, key quality metrics, and AI's impact on efficiency in life sciences.
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Apr 3, 2024 • 31min

Overcoming Cultural and Technological Hurdles for AI Integration in Life Sciences - with Daniel Ferrante of Deloitte

Daniel Ferrante, AI Leader at Deloitte, discusses challenges in AI adoption for pharmaceutical firms, focusing on cultural shifts, data monetization, and team alignment. They explore the future of phenotypical drug discovery amidst COVID-19, emphasizing the critical role of data analysis in healthcare insights.
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37 snips
Apr 2, 2024 • 30min

Transforming a Legacy Enterprise Culture to a Data-Based Enterprise Culture - with Bikalpa Neupane of Takeda Pharmaceuticals

Bikalpa Neupane, Head of AI at Takeda, discusses transitioning from legacy to data-centric culture in AI economy. Challenges for large enterprises with open-source AI tools. Navigating AI landscape for small firms. Importance of data sharing, talent, and industry diversity.
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5 snips
Mar 26, 2024 • 24min

IT for Financial Services in the Age of GenAI - with Craig Mackereth of Rimini Street

Craig Mackereth from Rimini Street discusses challenges facing financial leaders in adopting AI, including the need for tailored approaches, maximizing ROI in AI projects, embracing failures, and mastering current technologies before delving into generative AI.
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12 snips
Mar 20, 2024 • 20min

Essentials of Deploying Large Language Models in the Enterprise - with Anton Kornienko and Ben Webster of NLP Logix

Anton and Ben from NLP Logix discuss how to turn large language models into business value. They debunk misconceptions, highlight the role of data curation and balance, and stress the importance of human oversight for accuracy in generative AI.

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