The AI in Business Podcast

A single misstep in a new customer service channel can undo months of trust-building work.
 
In this episode, Paul Cuglietta, Customer Services Director at Simplyhealth, explores how disciplined testing, governance, and stakeholder sign-off shape agentic AI rollouts inside a regulated, high-trust environment.
The conversation covers matching automation to the way customers speak across channels, building a long-term AI vision tied to company purpose, and getting buy-in through comparable case studies.


This episode is sponsored by NiCE Cognigy.
 
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

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

Drug discovery teams are running short of new ideas to test, and AI models that simulate how cells respond to drugs only pay off once leaders know when those predictions can be trusted with experiments, timelines, and budget.
 
In this episode, Daniel Veres, Co-Founder and Chief Scientific Officer at Turbine, and Giorgio Gaglia, Head of Systems and Disease Biology at Sanofi, examine with host Yolandi de Weerdt how testing models on data they have never seen shows which R&D decisions their predictions can reliably inform.
 
The discussion offers R&D leaders a practical way to judge when a model's predictions are ready to inform which experiments to run, where in the pipeline to start, and how much risk to accept.
 
This episode is sponsored by Turbine.
 
Learn how these conversations drive pipeline for other AI brands — download our media kit at emerj.com/AD1

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.
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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

Finance teams face immense pressure to operate faster, but rushing to automate over fragmented systems only compounds errors downstream. Ciprian Porutiu, SVP of Strategic Initiatives at Marsh, joins host Yolandi de Weerdt to explain why establishing a common language and federated data domains matters far more than forcing everything into a single centralized database. He shares practical approaches for managing phased rollouts, involving cross-functional users early in system design, and connecting underlying data governance directly to strategic business performance.
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This episode is sponsored by Fynapse. 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