The AI in Business Podcast

Today's guest is Dan Keto, President and Co-founder at Easy Metrics, where he focuses on helping warehouse and distribution teams turn fragmented transactional data into a unified "single pane of glass" that supports faster diagnosis of variance and more defensible decision-making. Dan joins Emerj's Matthew DeMello to explore what a solid data foundation looks like in warehouse networks — and why it matters before teams attempt to layer AI on top. He also shares practical takeaways on how enterprises can align stakeholders around a common data language, avoid costly "AI-first" missteps, and use repeatable investigations and alerts to surface real cost drivers. This episode is sponsored by Easy Metrics. 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!

Today's guest is Nishtha Jain, AI Innovation Leader. Nishtha leads enterprise data and AI strategy in the biopharma sector, focusing on aligning advanced analytics and AI systems with real-world clinical, regulatory, and operational workflows.
Nishtha joins Emerj Client Narrative & Content Strategy Lead Nick Gertsch to examine why most enterprise AI pilots fail to scale, how unrealistic expectations and poorly defined use cases undermine ROI, and what it takes to design human-centered AI systems that fit how teams actually work in regulated environments. Nishtha also breaks down practical frameworks for measuring value beyond headcount reduction, including return on employee experience and long-term capability building, along with concrete approaches to faster experimentation, customer-driven use-case prioritization, and building flexible operating models that adapt as technology and market conditions evolve.

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!

Today's guest is Stephen Wolfram, Founder and CEO of Wolfram Research. Wolfram is a pioneering computer scientist and physicist, best known for creating Mathematica and Wolfram|Alpha, and for decades of work on complexity, computation, and the foundations of how systems evolve. Stephen joins Emerj CEO and Head of Research Daniel Faggella to explore how simple computational rules can give rise to complex, unpredictable systems, and what that means for the future of intelligence beyond biological life. The conversation examines concepts like computational irreducibility, adaptive evolution, and "bulk orchestration" at the molecular and digital level, framing how AI systems, biological organisms, and even physical processes can be understood as part of a broader computational universe. Stephen also shares practical perspectives on how these ideas translate into real-world AI development, including why coarse, outcome-driven objectives often outperform overly rigid design in machine learning, how enterprises can think about building systems that evolve rather than simply execute, and what leaders should understand about the limits of predictability, governance, and control as AI becomes more deeply embedded in business workflows. 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!

Today's guest is Naveen Kumar, Head of AI Governance at TD Bank. With extensive experience in AI risk management and governance, he provides actionable strategies for secure AI scaling in regulated environments. Naveen joins Emerj Editorial Director Matthew DeMello to discuss foundational challenges blocking AI adoption in banking, including data leakage, prompt injection, shadow AI, and hallucinations. Naveen also shares practical takeaways, such as role-based AI guardrails for data access, safe sandboxes for experimentation, hybrid deployments to protect sensitive data, and treating AI agents as de-risked employees with human oversight for compliance and ROI. 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!

Today's guest is Dean Alms, Chief Product Officer at Aravo. Aravo is an enterprise software company focused on third-party risk management and compliance platforms that help organizations manage vendor, supplier, and partner ecosystems across regulatory, operational, and reputational risk domains. Dean joins Emerj Editorial Director Matthew DeMello to examine how third-party risk has evolved into a data and AI-driven, board-level visibility and resilience challenge, and how automation is reshaping the way enterprises identify, remediate, and monitor risk at scale. Dean also shares practical workflow changes, including using AI to automate document ingestion and survey validation, generate corrective actions, and enable natural language access to risk data. The discussion highlights how these approaches reduce operational cost, improve data integrity, support continuous monitoring models, and help enterprise leaders protect revenue, reputation, and regulatory posture across complex supplier networks. 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! This episode is sponsored by Aravo. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.