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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 research staff and journalists 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

The AI in Business Podcast

As agentic AI becomes a defining force in enterprise innovation, infrastructure has moved from a back-office concern to the beating heart of business transformation. On today's episode of the 'AI in Business' podcast, Ranjan Sinha, IBM Fellow, Vice President, and Chief Technology Officer for watsonx and IBM Research, joins Emerj Editorial Director Matthew DeMello to discuss the future of scalable AI infrastructure — from neuromorphic and quantum processing to open-source AI platforms built for trust and governance. Ranjan explains how enterprises are transitioning from isolated experiments to mission-critical AI applications, revealing why today's Fortune 500 leaders must reimagine compute, governance, and data pipelines to sustain automation and reliability at scale. He details IBM's breakthroughs in specialized processors, including the NorthPole neuromorphic chip and the company's roadmap for fault-tolerant quantum computing by 2029. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the 'AI in Business' podcast! If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show! Watch Matthew and Ranjan's conversation on our new YouTube Channel: youtube.com/@EmerjAIResearch.

Architecting Enterprise AI for Generative and Agentic Systems - with Ranjan Sinha of IBM

Today's guest is Scott Bradley, VP of AI and Innovation at Novartis. As the eighth largest pharmaceutical company in the world by revenue, Novartis' medicines reach millions of people worldwide. Their focus on the discovery and development of novel, breakthrough treatments sees them reimagining not just the delivery of said treatments, but the practice of medicine at large. Scott joins Emerj Editorial Director Matthew DeMello to examine how artificial intelligence is transforming trial design, operations, and patient engagement — while also reshaping industry trust and accountability. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the 'AI in Business' podcast!

Rethinking Clinical Trial Operations with AI and Remote Monitoring - with Scott Bradley of Novartis

Today's guest is Xiong Liu, Director of Data Science and AI at Novartis. Novartis is among the world's leading pharmaceutical companies, pioneering data and advanced analytics in the pursuit of new medicines and patient outcomes. Xiong joins Emerj Editorial Director Matthew DeMello to examine how generative AI and foundation models are transforming R&D, clinical workflows, and research collaboration across the life sciences. The discussion highlights how domain-specific data strategies, improved data quality, and shared benchmarks are accelerating discovery and operationalizing AI for measurable ROI in biopharma. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the 'AI in Business' podcast! If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

Building AI-Ready Cultures in Life Sciences R&D - with Xiong Liu of Novartis

Today's guest is Mathias Cousin, Managing Director at Deloitte. With extensive experience in R&D transformation and regulated industry data strategy, Mathias joins Emerj Editorial Director Matthew DeMello to unpack what it really takes for enterprise leaders to deliver ROI from AI and data initiatives. Mathias also shares actionable guidance on building effective "string of pearls" use cases, investing in data quality and AI-native talent, and adopting practical change management to embed AI in workflows for measurable gains in efficiency and long-term competitive edge. This episode is sponsored by Deloitte. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the 'AI in Business' podcast!

Rethinking How Life Sciences Organizations Approach AI - Mathias Cousin of Deloitte

Today's guest is Sandro Venturini, Executive Director and Consultant at UBS. Specializing in cross-border fund structuring and regulatory strategy, he holds years of experience guiding financial institutions through complex launches across jurisdictions for the world's largest private bank. Sandro joins Emerj Editorial Director Matthew DeMello on the show today to explore the role of AI in reducing legal and business costs, ensuring alignment across stakeholders, and creating a single source of truth for fund launches. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the 'AI in Business' podcast!

Streamlining Fund Compliance with AI-Ready Data - Sandro Venturini of UBS

Today's guest is Christo Siebrits, Senior Associate and General Counsel at AbbVie. With over 20 years of experience in global pharmaceutical legal and compliance leadership, Siebrits leads AbbVie's AI initiatives and provides strategic guidance on AI-related legal and regulatory matters. Christo joins Emerj Editorial Director Matthew DeMello to discuss how enterprise legal teams can adopt generative AI safely, balance internal versus external data use, and implement human-in-the-loop workflows to manage risk. Siebrits also shares practical strategies for matter-centric processes, measuring AI-driven efficiencies, and making informed decisions on AI investments across internal and external legal operations. We'd like to note for our audience that the views expressed by Christo on today's program do not reflect those of AbbVie or its leadership. Have a story about AI adoption you're ready to share with fellow enterprise leaders? Visit emerj.com/expert2 to explore the opportunity to be a featured guest on the 'AI in Business podcast'. This episode is sponsored by Clarivate. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.

From Tool Sprawl to Defensible Value in AI for Legal - with Christo Siebrits of AbbVie

When finance leaders push for measurable savings and supply chain leaders prioritize continuity and resilience, technology adoption often gets caught in the middle. Procurement teams, operating with risk-averse cultures and outdated tools, face growing complexity while pressure mounts from both sides of the business. In this episode of the AI in Business podcast, Rob DeSantis — CEO and Co-founder of Arkestro, Co-founder of Ariba, and early LinkedIn executive — explains to Emerj CEO and Head of Research Daniel Faggella why AI represents more than incremental change for procurement. Instead of simply digitizing old workflows, AI enables re-imagined processes that deliver step-function value, often translating into 20 to 30 percent savings directly impacting earnings per share. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the 'AI in Business' podcast! If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show! This episode is sponsored by Arkestro. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.

Enabling Strategic Procurement with AI, From Frustration to Foresight - with Rob DeSantis of Arkestro

On this episode of the AI in Business podcast, Emerj Editorial Director Matthew DeMello speaks with Ben Ninio, Principal in Strategy at Deloitte, about how enterprises are rethinking the fundamentals of scientific discovery in the AI era. Ben explains why language itself has become the "hack" for unifying frameworks across R&D domains—from pharmaceuticals to agriculture to industrial chemistry—allowing organizations to move beyond the limits of brute-force computation. He illustrates how large language models and knowledge graphs can help identify new molecular, biological, and cross-domain insights that were previously impossible to surface. This episode is sponsored by Deloitte. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1. Want to share your AI adoption story with executive peers? Click emerj.com/expert2 for more information and to be a potential future guest on the 'AI in Business' podcast! If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show! This episode is sponsored by Deloitte. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.

Connecting the Dots Across Discovery - with Ben Ninio of Deloitte

Today's guest is Steve Taczala, VP of Service Operations at Impact Networking. Impact Networking is a managed service provider founded in 1999, with more than 20 US offices, supporting organizations in IT, cybersecurity, and applying AI to business operations. Taczala brings extensive experience in managing MSP service operations and improving IT workflows. Steve joins Emerj Editorial Director Matthew DeMello to discuss how enterprise teams can reduce ticket noise, prioritize actionable incidents, and prepare service desks for AI-driven operations. Steve also shares practical strategies for staging platform migrations, implementing intelligent ticket routing, and using AI to enhance team efficiency and the overall customer experience. This episode is sponsored by Xurrent. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.

Fixing Ticket Noise with AI in Enterprise MSP Operations - with Steve Taczala of Impact Networking

Today's guest is Sunitha Rao, SVP and General Manager for Hybrid Cloud Business at Hitachi Vantara. Hitachi Vantara is a wholly owned subsidiary of Hitachi, Ltd. that provides data infrastructure foundations that help leading innovators manage and leverage their data at scale. Through data storage, infrastructure systems, cloud management, and digital expertise, the company helps customers build the foundation for sustainable business growth. Sunitha joins Emerj Editorial Director Matthew DeMello on the show to break down how enterprises across industries can modernize their data infrastructure, scale AI deployments, and align IT investments with their sustainability goals. This episode is sponsored by Hitachi Vantara. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.

Data Volume, Quality, and Model Degradation for AI at Scale - with Sunitha Rao of Hitachi Vantara

Unlike the field of self-driving cars, the fields of construction, mining, agriculture, and other classes of "heavy industry" involve a huge variety of equipment and use-cases that go beyond traveling from A to B. The heavy industry leaders of today are no farther behind automakers in their understanding that AI and automation will be essential for the future of their companies. In this episode, guest Dr. Sam Kherat discusses the areas in heavy industry where AI is currently playing a role in heavy industry, what type of capabilities and functions are automatable, and at what level. He also shines a light on how AI might affect the future of the industry within the next 2-3 years, and in what ways we can expect large equipment to become more autonomous.

The Future of AI in Heavy Industry

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