Scaling Scientific R&D with AI Supercomputing Infrastructure — with Thomas Fuchs of Eli Lilly

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

Energy organizations have made progress in safety, but most still rely on backward‑looking investigations rather than systems that anticipate when risk is rising. In this episode, Patricio Rivera, Former Vice President of HSE International at Oxy, joins host Matthew DeMello and examines how learning from good days and leveraging existing observation data can strengthen an organization's ability to predict and prevent safety‑critical events. He highlights the practical shifts required to extend periods of stable operations, reinforce the controls most likely to fail, and align safety practices with broader business performance expectations. Learn how brands work with Emerj and other Emerj Media options at http://go.emerj.com/partner

AI enthusiasm has outpaced enterprise readiness, leaving many organizations stuck with pilots that work in the lab but fail to deliver meaningful value in production. In this episode, Lawrence Whittle, Chief Strategy Officer at HTEC Group, joins Emerj's Marilie Fouché to examine how the gap between individual users, isolated use cases, and true end‑to‑end sequences prevents companies from moving beyond experimentation. He highlights the practical shifts required — smaller real deployments, tighter scopes, faster iteration cycles, and integrated expertise — to build momentum and translate AI concepts into tangible business results. This episode is sponsored by HTEC. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner

Agentic AI is running into a hard limit: most enterprise systems, security layers, and operational backends aren't yet built to support automated execution at scale.  Alex Tyrrel, SVP and CTO of Health at Wolters Kluwer, joins Emerj's Matthe DeMello to unpack how agentic systems adapt models to domain‑specific tasks and act directly inside regulated environments. He outlines the practical requirements for higher‑velocity automation, including tighter APIs and entitlements, stronger observability and compliance, and backend capacity that can handle machine‑driven throughput. Learn how brands work with Emerj and other Emerj Media options at http://go.emerj.com/partner