Ermir Qeli, Head of Data Science in AI at Swiss Re, discusses challenges with unstructured data in insurance tech stacks. He shares insights on scaling systems, generative AI use cases, and fraud detection evolution in the insurance sector. The significance of incorporating unstructured data and visual data in improving fraud detection and customer service is highlighted, along with innovative use cases of video assessment in bicycle insurance claims.

Carm Taglienti, Chief Data Officer at Insight, emphasizes the importance of keeping humans in the loop for AI development. Topics include building trust in AI, human-centric company cultures, and driving productivity gains. The discussion covers AI integration in workflows, creating a culture of lifelong learning, merging human expertise with AI, and navigating the cultural shift towards AI in enterprises.

Tomas Ohlson from Einride discusses how electric and autonomous vehicles are revolutionizing logistics, reducing diesel usage, and enhancing supply chain efficiencies. They delve into the importance of data optimization, human judgment in supervision, and the need for a balanced automation approach in freight workflows.

Rupam Baijal, Director of Procurement at Algoma Steel, discusses legacy data challenges in extractive industries and the need for digital transformation. He highlights the expertise gap between data science vendors and heavy industry subject matter experts. The conversation explores the obstacles in dealing with outdated data systems and the potential solutions, including AI integration. Additionally, the podcast delves into the complexities of legacy tech stacks, data governance, and the role of AI in enhancing heavy industry operations and decision-making.

Jeff Otto, CMO of Riskified, discusses the rise of first-party fraud and chargebacks in e-commerce, highlighting the challenges faced by businesses. The conversation delves into the importance of technology like AI for fraud prevention and customer experience enhancement. Strategies for navigating e-commerce fraud, chargebacks, and identity verification are explored, emphasizing the need for efficient processes and data-driven approaches.

Dr. Milind Sawant discusses AI deployment challenges in healthcare, emphasizing data quality and expert feedback. He explores the impact of AI on diagnostics workflows and the future of these industries. The episode highlights pitfalls in AI implementation, the importance of expertise and infrastructure, and leveraging Bayesian statistics in medical diagnostics.

IBM Fellow, Ranjan Sinha discusses driving responsible AI through operations, emphasizing end-to-end lifecycle tracking, automated processes, and scalability. Topics include managing biases, data quality challenges, empowering employees for equitable AI outcomes, developers using AI tools for productivity, and evolution of AI in enterprises.

Edwin Pahk of Aquant discusses the importance of tribal knowledge in AI adoption for service industries. He emphasizes personalization in B2B workflows and how AI can enhance work-life experiences. The podcast explores challenges in implementing AI, the value of soft skills in future hires, and the significance of diverse backgrounds in AI adoption.

Hossein Zahed of Capital One discusses the hidden ROI of generative AI in financial services, emphasizing the importance of technology beyond customer-facing applications. The conversation explores the challenges and benefits of integrating new technologies in the financial sector, Capital One's approach to tech innovation, and the strategic problem-solving and technology implementation in financial companies.

Tom Hayes and Gareth Dabbs from IQVIA discuss leveraging AI for personalized patient experiences and targeting healthcare providers effectively. They cover optimizing omnichannel marketing for compliance and building trust in caretaker support systems through personalized insights. The podcast explores challenges in implementing AI in healthcare and financial services, evolving AI models, enhancing patient engagement in pharmaceutical research, and utilizing AI to predict rare diseases for improved patient outcomes.