

The AI in Business Podcast
Daniel Faggella
The AI in Business Podcast is for non-technical business leaders who need to find AI opportunities, align AI capabilities with strategy, and deliver ROI.
Each week, Emerj AI Research CEO Daniel Faggella and team interview top AI executives from Fortune 2000 firms and unicorn startups - uncovering trends, use-cases, and best practices for practical AI adoption.
Visit our advertising page to learn more about reaching our executive audience of Fortune 2000 AI adopters: https://emerj.com/advertise
Each week, Emerj AI Research CEO Daniel Faggella and team interview top AI executives from Fortune 2000 firms and unicorn startups - uncovering trends, use-cases, and best practices for practical AI adoption.
Visit our advertising page to learn more about reaching our executive audience of Fortune 2000 AI adopters: https://emerj.com/advertise
Episodes
Mentioned books

Jun 5, 2024 • 18min
Developing Enterprise AI for Humans - with Carm Taglienti of Insight
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.

Jun 4, 2024 • 14min
Decreasing Diesel and Social Risk in Logistics - with Tomas Ohlson of Einride
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.

May 30, 2024 • 19min
Data Governance and Legacy Tech Stack Challenges in Heavy Industry - with Rupam Baijal of Algoma Steel
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 The conversation explores the obstacles in dealing with outdated data systems and the potential solutions, including AI integration.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.

May 29, 2024 • 27min
Fighting First Party Fraud and Chargebacks in e-Commerce - with Jeff Otto of Riskified
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.

8 snips
May 28, 2024 • 17min
Deploying AI in Healthcare and Life Sciences with Dr. Milind Sawant of Siemens Healthineers
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.

May 25, 2024 • 18min
Fostering Responsible AI Outcomes through Operations and Developer Workflows - with Ranjan Sinha of IBM
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.

23 snips
May 23, 2024 • 31min
The Importance of Tribal Knowledge for the Success of AI Adoptions - with Edwin Pahk of Aquant
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.

May 22, 2024 • 14min
Driving Innovation and Clean Data in Finserv Information Flows - with Hossein Zahed of Capital One
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.

4 snips
May 21, 2024 • 26min
Targeting Providers through Omnichannel Marketing and Patient Personalization - with Tom Hayes and Gareth Dabbs of IQVIA
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.

May 15, 2024 • 14min
Setting Strong Foundations for Modernization in the Era of Everything AI - with Carm Taglienti of Insight
Carm Taglienti, Chief Data Officer at Insight, discusses strategies for AI adoption, selecting the right tools, and driving digital transformation efficiently. Topics include agile methods in digital transformation, defining technology ROI, leveraging data for decision-making, and transitioning to robust AI systems in enterprises.