The AI in Business Podcast

Financial institutions are moving fast on generative AI without a clear answer for who owns, and who is liable for, the content it produces and consumes. In this episode, Stefan Zima, Head of Group Regulatory Compliance and AI Compliance at Raiffeisen Bank International AG, examines how banks can build real accountability and visibility into their AI content practices before regulators or auditors force the issue. The conversation covers cross-border data governance, third-party AI risk, and where research reports, market commentary, and training materials create the most exposure. ​ Learn how leading AI brands like NVIDIA and Google Cloud work with Emerj to reach Fortune 500 AI buyers - download our media kit at: emerj.com/AD1

Enterprise CX teams have poured budget into AI, yet many still can't show measurable returns — frontline staff double-check the tools, and each new bot becomes another disconnected silo. ​ In this episode, John McMullan, Head of Product Marketing and Strategy at Observe.AI, joins host Yolandi de Weerdt to examine why AI adopted without operational discipline falls short, and how a shared interaction intelligence layer can carry context across AI agents, core systems, and human handoffs. ​ McMullan outlines the practical shifts: putting frontline experts, analysts, and engineers on the build team, starting with one small workflow and learning from early failures, testing agents against simulations of real conversations, and getting data clean and connected before scaling. This episode is sponsored by Observe.AI. To learn how to spot real AI trends in any sector, download our free report, "3 Ways to Discover AI Trends in Any Sector," at emerj.com/ait1

An AI agent can function as designed yet produce results an organization cannot verify or safely use. In this episode, Melissa Ramey, Director, AI Transformation – Data Insights and User Experience at Salesforce, joins Emerj's Yolandi de Weerdt to examine who owns agent behavior after deployment and why correcting individual outputs does not fix the underlying workflow. She explains how source evidence, shared definitions, and clear decision boundaries help teams govern agents before expanding their autonomy. To go deeper on AI strategy, including evidence-based AI ROI and building long-term capabilities, download Emerj's free PDF report, "3 Keys to Thriving in the Coming Era of Automation," at emerj.com/cok1

In biopharma R&D, AI investment has overwhelmingly targeted generating more drug candidates, even though the industry has rarely lacked for compounds worth pursuing. In this episode, Mukhtar Ahmed, Director of Project and Portfolio Strategy at Greenstone Biosciences, explores why the harder and more valuable problem is deciding which candidates deserve continued capital and attention. The conversation covers synthesizing fragmented evidence across teams, keeping human judgment and accountability in the loop, and measuring AI's impact across a portfolio rather than a single program. ​ Emerj works with a select group of AI vendors to reach Fortune 500 decision-makers through research, media, and direct access. If you want to be considered, download our media kit at emerj.com/AD1

For large banks, the barrier to AI at scale is rarely the model. It's decades of fragmented systems, inherited through mergers, acquisitions, and new products, where each team trusts its own data and no single view of context exists. Agentic AI doesn't fix that fragmentation; it amplifies it across every user and every prompt. ​ In this episode, Nathaniel Bell, Data Management Director at Wells Fargo, joins host Yolandi de Weerdt, to examine why the real challenge for regulated institutions is scaling trust while automating, why leaders should judge new technology on the business outcome it can prove rather than the demo, and why no process should be automated before it's standardized. ​ Bell outlines the practical shifts underway: from manual attestations and spreadsheets toward automated logs that show what happened in a workflow, from governance as document review toward governance built into workflows as code, and from buying new tools toward changing how teams work once they have them. ​ According to Nielsen, 91% of podcast listening happens alone, indicating deep, undistracted attention — ideal for complex B2B messaging. ​ To learn how leading brands and AI startups connect with enterprise AI buyer audiences at scale, download our media kit at emerj.com/AD1

For consumer goods companies, the gap between the commercial plan agreed at head office and what gets executed on the shelf is one of the costliest disconnects in the business — investment goes out against activity that never happens, and revenue never arrives against activity that does. ​ In this episode, Stephanie Lilley, VP of Transformation for Europe at Reckitt, examines why rigid rep call cycles and fragmented store-level data keep that gap open, and where AI is starting to close it — from image recognition that verifies in-store compliance to dynamic routing that sends field teams to the stores with the highest return — with host Daniel Faggella, Emerj CEO and Head of Research. ​ She outlines the practical shifts underway: from fixed call files toward a mix of core relationship stores and flexible, ROI-driven visits, from full-time field coverage toward crowdsourced compliance checks, and from geography as the deciding factor toward the quality and recency of store-level data. ​ Learn how these conversations drive pipeline for AI brands — download our media kit at emerj.com/AD1

Generative AI is entering clinical workflows just as healthcare institutions grapple with black-box outputs, unclear regulation, and the need for provable accuracy. In this episode, Rhett Alden, CTO at Elsevier, joins Emerj's Yolandi de Weerdt to articulate how claim-level validation and transparent sourcing are becoming prerequisites for clinical trust in AI. The conversation covers emerging AI governance boards modeled on clinical trial review structures, the limits of current US regulation, and why final clinical responsibility remains with the physician. Learn the strategies Emerj uses to help leading AI brands and startups connect with their ideal enterprise AI buyers: emerj.com/AD1

Enterprise sales teams routinely let the majority of inbound leads go untouched simply because there isn't enough team bandwidth to work them all. In this episode, Vanessa Tabbert, VP of Agentic Transformation and Sales Development at Salesforce, breaks down how her own team deployed an AI SDR agent to recover leads that would otherwise go cold, without replacing the humans who convert the best ones. The conversation covers how to identify a low-risk first use case, why an AI agent should be coached and measured like a team member rather than launched and left alone, and how the same approach scales down to a small SMB sales team. This episode is sponsored by Salesforce. ​ To learn the exact strategies we use to help leading AI brands and startups connect with their ideal enterprise AI buyers, visit: emerj.com/AD1

Industrial environments run on a different set of constraints than the typical enterprise office — physical risk, standalone factory sites, and workflows where a fragmented handoff can cost time, quality, or worse. ​ In this episode, Scot Burdette, Global CIO of Measurement & Analytics at ABB, examines why industrial AI has to be built around knowledge capture, human-in-the-loop oversight, and frontline usability, and shares how ABB's own tools are helping a retiring generation's expertise transfer to the workers replacing them, with Emerj host Marilie Fouché. ​ He outlines the practical shift underway, from siloed, tribal knowledge toward a shared operational data layer, and from pilots that prove a concept to the design and implementation work that changes how a factory runs. ​ This episode is sponsored by Poka. To learn the exact strategies we use to help leading AI brands and startups connect with their ideal enterprise AI buyers, visit: emerj.com/AD1

A quarter of enterprise teams have gotten a single AI channel into full production — the rest are stuck somewhere behind it. In this episode, Arun Chandra, Chief Operating Officer at NiCE, explores why that gap persists and what closes it. The conversation covers getting data, knowledge, and organizational context ready for scale, building the financial case for AI investment with the CFO, and how open protocols like MCP are reshaping enterprise architecture decisions. This episode is sponsored by NiCE Cognigy. 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 engineering teams often spend more time triaging recurring incidents than building the features customers are asking for. In this episode, Dave Glick, Senior Vice President of Growth Technology at Walmart, explores how his teams are using AI agents to catch and fix small, recurring issues before they turn into support tickets. The conversation covers the internal tools Walmart built to scale this work, the governance model that keeps experimentation safe, and why closing the distance between engineers and the people using their tools speeds up every iteration. ​ This episode is sponsored by BigPanda. If you offer AI products or services into the enterprise, you need to find enterprise leaders with relevance, and readiness. Emerj attracts VP+ enterprise audiences who are already convinced that they need to move beyond traditional IT. To learn the exact strategies we use to help leading AI brands and startups connect with their ideal enterprise AI buyers, visit: emerj.com/AD1

Enterprise leaders face a growing gap between AI ambition and the fragmented data, legacy systems, and cultural friction that prevent pilots from becoming scalable value. In this episode, Julian Tang, Chief Operations Officer for the Innovation Office at BlackRock, examines how unified data foundations, modernized infrastructure, and transparent governance enable organizations to move from reactive experimentation to intentional, enterprise‑wide AI deployment, in conversation with host Matthew DeMello. He highlights the practical shifts required to reduce friction, build trust in AI systems, and create repeatable playbooks that let teams scale responsibly and with confidence. 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

The rise of non‑invasive BCIs and the privacy, security, and human‑relevance questions they introduce is becoming a central concern as this technology moves toward practical use. In this episode, Paolo Ardoino, CEO at Tether, examines how lightweight on‑device models, silent‑speech inputs, and anonymized brain‑wave data can turn low‑bandwidth neural signals into real‑world actions, in conversation with host Daniel Faggella, Emerj CEO and Head of Research. The discussion focuses on emerging consumer use cases, long‑term cognitive augmentation, and the safeguards needed to keep these systems private and safe. Emerj works with a select group of AI vendors to reach Fortune 500 decision makers through research, media, and direct access. If you want to be considered, download our media kit at emerj.com/AD1