The AI in Business Podcast

As enterprises move agentic AI from controlled pilots into production customer-facing workflows, the gaps in data continuity, governance, and human-agent coordination become the deciding factors in whether AI scales or stalls. In this episode, Shri Nandan, VP of AI Experiences at Comcast, examines why customer experience has become the real stress-test for enterprise AI — and what it takes to scale with customer trust intact. The conversation covers the three data foundations required for context continuity in production, practical principles for human-AI orchestration, and why cross-team governance — a single North Star across CX, IT, and operations — is what separates the organizations that scale from those that fragment. This episode is sponsored by NiCE. Learn how to structure landing pages for higher conversion and how to use self-qualification systems to prioritize high-intent leads. Download our free PDF report, "B2B AI Lead Generation Guide," at emerj.com/aig1

The rising use of general‑purpose models in regulated environments is creating a widening gap between what AI can generate and what fiduciary professionals can safely rely on. In this episode, Steve Hasker, CEO at Thomson Reuters, examines how AI must be trained, validated, and governed to deliver the level of accuracy required in legal, tax, and audit workflows in conversation with host Dan Faggella, Emerj CEO and Head of Research. The discussion highlights the operational demands of vertical AI, the role of expert‑trained agents, and why human oversight remains essential in high‑stakes professional work. Learn how financial institutions are digitizing paper-based records to unlock usable data for AI, and using alternative data like public web and social signals to enhance risk assessment, download our free PDF report, "AI in Financial Services Executive Cheat Sheet" at emerj.com/fcs1

Supply chain organizations still struggle to respond to major disruptions because their core planning systems can't evaluate structural options or network‑level changes at the speed required. In this episode, Joris Wijpkema, Executive Vice President for Solutions and Strategy at Optilogic, joins host Marilie Fouché and examines how a dedicated, high‑compute modeling layer enables teams to run thousands of scenarios in minutes and make faster, better‑aligned decisions. The discussion highlights how leaders can strengthen resilience by unifying data foundations, building trust in modeling before a crisis, and integrating design‑grade optimization directly into planning cycles. This episode is sponsored by Optilogic. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner

Enterprise AI investments frequently succeed at the pilot stage and collapse at scale, not because the technology fails, but because the organizational conditions for adoption were never established. In this episode, Darko Todorovic, CTO at HTEC Group, examines why most AI ROI gaps originate in poor problem definition and inadequate change management, and outlines how senior leaders can build the baselines, KPIs, and organizational readiness needed to measure and sustain real returns. The conversation covers practical guidance on assessing technological and organizational maturity, avoiding POC-to-production pitfalls, and selecting the right AI tools for specific business contexts. This episode is sponsored by HTEC. In this episode we cover how enterprise leaders can measure and prove AI ROI after deployment. To go deeper on this topic and learn how to identify real AI trends by tracking where venture funding is flowing, and by listening to how leading CEOs describe risk and competitive strategy, download our free PDF report, "3 Ways to Discover AI Trends in Any Sector" at emerj.com/ait1

Pharma commercial teams are generating more data than ever, but field intelligence is still arriving too late to change rep behavior before the engagement window closes. In this episode, Damion Nero, Global Head of Statistics at Daiichi Sankyo, joins Emerj editor Yolandi de Weerdt to examine why fragmented data pipelines, not a shortage of data, are the structural root of the gap between commercial insight and field execution. The conversation covers what separates teams that successfully adopt AI from those stuck in the pilot phase, and why starting with routine, high-certainty use cases consistently produces more commercial lift than chasing ambitious automation. This episode is sponsored by ODAIA. Learn how leading organizations approach AI investment more like a venture portfolio, and why interdisciplinary collaboration is critical to defining the right data for AI success. Download our free PDF report, "Beginning with AI," at emerj.com/aik1