Stay ConnectedThe 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.
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Copyright: © Daniel Faggella, 2014
Computer vision implementations in manufacturing never advance beyond the pilot phase — not because the technology fails, but because deployment is treated as a software problem rather than an operational one. In this episode, Jeff Witt, Digital Transformation Leader at a Fortune 500 global leader in building materials and fiberglass composites, examines the architectural, organizational, and change management decisions that determine whether a vision AI initiative reaches production and scales. The conversation covers how to build a reusable data architecture for vision data, why shifting ownership from IT to business units accelerates deployment, and what a platform mindset — versus a point solution approach — looks like in a multi-site manufacturing environment. This episode is sponsored by Roboflow. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
The growing use of AI‑driven modeling in clinical development is exposing how limited traditional, single‑study dose selection and patient assessment methods have been for complex oncology programs. In this episode, Shefali Kakar, Global Head of PK Sciences and Oncology at Novartis, examines how deeper data integration across phases enables more precise dose decisions, clearer safety interpretation, and a more consistent understanding of patient variability alongside host Matthew DeMello. She outlines how longitudinal analysis, exposure–response modeling, and covariate evaluation are helping teams reduce unnecessary sub‑studies, tailor dosing for diverse patient groups, and strengthen cross‑functional decision‑making throughout development. According to Nielsen, 91% of podcast listening happens alone, creating a focused, distraction-light environment well suited for complex B2B messaging. Learn how leading brands and AI startups connect with enterprise AI buyer audiences at scale by downloading our media kit at go.emerj.com/partner
The pressure on financial services AI leaders to show board-level results has intensified — yet the pace of vendor pitches, shifting tooling stacks, and stalled pilots has made action feel riskier than waiting. In this episode, Art Shectman, CEO and Founder at Elephant Ventures, breaks down why the instinct to evaluate everything before building anything is the primary obstacle to production, and what a realistic first step actually looks like inside a regulated enterprise. The conversation covers how to identify the right initial workflow, how to structure a time-boxed sprint toward a minimum viable production deployment, and how to present early AI wins to boards that have stopped trusting strategy decks. This episode is sponsored by Elephant Ventures. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
The reason enterprise AI programmes stall is not the technology — it is the sequence in which decisions are made before and after the pilot succeeds. In this episode, Ronny Fehling, Chief AI Transformation Officer at HTEC, examines why AI initiatives lose momentum at the production threshold and what organisational conditions determine whether they make it through. The discussion covers production slices, decision gates with kill-switch authority, use case discipline, and why top-down AI mandates tend to reproduce the same failure modes regardless of budget. This episode is sponsored by HTEC. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
Deepfake voice fraud is not bypassing enterprise security technology, it is beating the workflows agents rely on to make trust decisions in real time. In this episode, Jon-Rav Shende, Global CTO for Data and AI at Thales Group, outlines where enterprise voice channels are most exposed, why identity, urgency, and business action converging in a single call represents the highest risk point, and what a practical four-step response framework looks like for regulated organisations. The discussion covers how to map risky voice journeys, define escalation decision points, build the evidence chains auditors and cyber insurers will require, and deploy AI as a risk signal layer without automating high-risk actions beyond appropriate controls. This episode is sponsored by Modulate. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
A growing share of pharmaceutical innovation is now constrained not by scientific imagination, but by the infrastructure required to support AI at scale. In this episode of the AI in Business podcast, Thomas Fuchs, Chief AI Officer at Eli Lilly & Company, joins Matthew DeMello to explore how Lilly's new AI supercomputing platform is reshaping scientific discovery and enterprise operations. The conversation examines how large-scale computing enables more advanced models, secure and usable data environments, and faster scientific iteration across the organization. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
Boards are pushing CIOs to commit to AI strategies built on contracts written for an entirely different era of enterprise software. In this episode, John Belden, Chief of Research and Strategy at UpperEdge, breaks down the six dimensions of uncertainty CIOs now face when weighing major AI and ERP commitments, and explains why the next five years are about flexibility, not productivity. The conversation covers the case for tighter SI accountability around adaptability, the practical role of contractually-protected optionality, and the difference between performance theater and the kind of continuous learning that keeps a transformation honest. This episode is sponsored by UpperEdge. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
Context defines accurate, reliable AI decision‑making, forcing enterprises to confront the fragmentation that prevents systems from accessing the information those decisions depend on. In this episode, Ravi Marwaha, Chief Operating Officer & Chief Technology Product Officer at Arango, examines how AI breaks down when it is asked to reason across disconnected architectures that cannot supply a unified, critical context. The discussion highlights how leaders can isolate the information that drives real decisions, structure access so AI can use it at the moment of action, and establish governance as agent‑generated outcomes move into production. This episode is sponsored by Arango. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
A significant share of manufacturing knowledge still lives in the heads of retiring workers, and the window to capture it is closing as operations push toward AI-enabled ways of working. In this episode, Anand Gnanamoorthy, Director of Corporate Strategy and AI at Ingersoll Rand, examines how manufacturers can digitize tribal knowledge, structured operational data, and decades of unstructured archives before that context disappears. The discussion covers separating data, insights, and decision-making across AI deployments; tapping messy, unstructured data without over-cleaning it; anchoring use cases to the frontline worker rather than the process; and treating every AI project as permanently in pilot mode. This episode is sponsored by Poka. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
Enterprise service leaders are realizing that deploying AI for simple productivity gains fails to resolve the underlying issues that cause repeat truck rolls and high costs. In this episode, Niken Patel, CEO and Co-Founder at Neuron7.ai, unpacks why moving beyond basic automation requires a deterministic intelligence layer to make fragmented data ready for complex resolution decision-making. The discussion focuses on benchmarking industry performance, educating core teams on AI readiness, and establishing a data foundation that enables a transition from reactive repairs to predictive service models. This episode is sponsored by Neuron7.ai Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
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