The AI in Business Podcast

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

Enterprise AI agents fail consistently in production, not because of model limitations, but because they lack a live, temporally aware context layer grounded in the actual current state of the business. In this episode, Ravi Marwaha, Chief Operating Officer & Chief Technology Product Officer at Arango, explores how treating context as infrastructure—rather than a data pipeline problem—enables agents to reason accurately, explain their decisions, and deliver measurable outcomes across customer support, semiconductor engineering, and clinical trial site selection. The discussion covers five practical frameworks for CIOs and chief data officers on building real-time, explainable context layers on top of existing enterprise systems, without ripping and replacing current infrastructure. This episode is sponsored by Arango. To learn how to improve landing page conversion and use self-qualification systems to identify high-intent leads, download Emerj's free PDF report, "B2B AI Lead Generation Guide," at emerj.com/aig2

Enterprise leaders face a growing gap between rapid AI advancement and the fragmented data and processes that limit their ability to operationalize it. In this episode, Guillermo Vazquez, Chief Architect in the Business Transformation Services for SAP America, examines with host Nick Gersch how harmonized data, standardized processes, and clear identification of differentiating workflows form the groundwork for effective AI‑enabled ERP. He highlights the practical sequence for building this foundation so future AI‑driven adaptation becomes seamless rather than disruptive. For AI brands trying to reach senior decision-makers, podcasts are one of the few channels that earn 20+ minutes of focused attention from VP+ leaders. Emerj reaches 1,000,000 listeners annually — see how other AI brands are driving pipeline: emerj.com/AD1

Regulatory volatility, scientific‑grade context requirements, and entrenched legacy processes are creating a level of operational complexity in pharma that makes even high‑value AI initiatives difficult to move from concept to production. In this episode, Art Shectman, CEO at Elephant Ventures, examines with host Marilie Fouché how leaders can cut through that complexity by isolating a single, clearly defined workflow slice and rebuilding it for near‑term, dependable deployment rather than long‑range architectural perfection. The discussion highlights how removing outdated process assumptions, selecting an atomic workflow with organizational alignment, and aiming for a contained operational win enable pharma teams to build momentum and scale AI responsibly in highly regulated environments. Learn how consultants are winning business with evidence-based AI ROI and building long-term capabilities instead of chasing short-term gains. Download our free PDF report, "3 Keys to Thriving in the Coming Era of Automation," at emerj.com/cok1

Individual AI productivity gains are already here, but they are uneven, and they are not the main event. In this episode, Tim Sears, Chief AI Officer at HTEC, argues that the real transformation in software development will arrive when AI becomes a catalyst for teamwork rather than an enhancer of individual performance. The conversation examines why software development is the clearest available model for how AI will eventually reshape every business function, how the developer role is being elevated from syntax and grunt work toward architecture, security, and client judgment, why the traditional build-versus-buy decision is being replaced by a build-versus-build reality, and what it will mean when perfection in enterprise software becomes the expected standard rather than the exception. For senior leaders trying to move from supporting AI in principle to actually delivering change, Sears offers a direct and practitioner-grounded view of what needs to change in teams, in expectations, and in the way business processes are understood and redesigned. AI is moving fast — new tools, new research, new use cases every week. Emerj synthesizes what matters most, so senior leaders and practitioners can stay ahead without getting buried. Join 85,000+ subscribers and get the most useful AI business insights delivered to your inbox. Visit: http://emerj.com/ad1