The AI in Business Podcast

As enterprises move from single to multi-agent AI deployments, a coordination infrastructure problem is emerging that connectivity protocols alone cannot solve. In this episode, Guillaume de Saint Marc, VP of Engineering at Outshift, examines why agents that can communicate still fail to collaborate — and outlines the semantic alignment, shared memory, and authorization architecture required to address it. The discussion covers specific failure modes in production multi-agent systems, the organizational security and observability decisions that determine whether agentic deployments scale, and how open standards protect enterprises from vendor lock-in as the space evolves.
 
This episode is sponsored by Outshift by Cisco. In this episode, we cover why enterprises scaling multi-agent AI need more than connected agents — they need shared semantic grounding, persistent memory, and fine-grained authorization to enable genuine collaboration. To go deeper on this topic and 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

A widening gap between mature digital compute and the newly awakening physical world is forcing enterprises to rethink how they embed AI into logistics, manufacturing, and other high‑stakes environments where errors carry real operational risk.


In this episode, Drew Henry, Executive Vice President for Physical AI at Arm, joins host Daniel Faggella and examines how leaders are navigating the shift from fixed automation to model‑driven intelligent control, and what it takes to make confident, high‑impact infrastructure decisions amid rapid algorithmic and hardware change.


The discussion highlights how advanced teams ground adoption in concrete operational problems, build competency around new model‑based interfaces, and use simulation and digital twins to de‑risk retooling in power‑ and compute‑constrained environments.


If you want to listen to the same things that other infrastructure and AI leaders in the Fortune 500 are tuned into, then check out the AI infrastructure podcast, it's emerj.com/inf1

A surge in AI adoption is creating a rights gap inside financial institutions, where everyday workflows now generate copyrighted reproductions at a scale existing governance models were never built to manage. In this episode, Roanie Levy, Licensing and Legal Advisor at CCC, joins host Yolandi de Weerdt and examines how AI‑driven content use is outpacing traditional licensing frameworks and why leaders must verify rights before embedding copyrighted material into AI systems. The discussion highlights the operational decisions executives need to make around content governance, rights validation, and cross‑functional controls to prevent downstream legal and workflow disruption. This episode is sponsored by CCC. If you offer AI products or services into the enterprise, you need to find enterprise leaders with relevance and readiness.
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The rapid expansion of AI in financial services is creating a widening gap between enterprise ambition and the operational readiness required to deploy systems that are secure, compliant, and trusted. In this episode, Dr. Oscar A. Rodriguez, Vice President of Data Analytics at Citi, joins Daniel Faggella, Emerj CEO and Head of Research, to describe how leaders build the operating model for safe AI at scale, from aligning stakeholders to embedding governance, accountability, and data quality from the start. The discussion highlights practical decisions around cross‑functional alignment, foundation‑first governance, risk ownership, and preparing for evolving regulatory and security demands. This episode is sponsored by Securiti AI. Download the free "AI in Financial Services Executive Cheat Sheet" at emerj.com/fcs1 to go deeper on how early governance prevents AI failures.

Supply chains are moving from predictable planning cycles to a reality where volatility demands continuous redesign and faster decision‑making. In this episode, Dr. Gopalendu Pal, Director of Operations at Target, and Prasad Mahajan, Senior Director of Customer Engagement at Optilogic, examine how leaders can adapt by tightening the gap between sensing disruption and adjusting operations, as Emerj's Daniel Faggella guides the discussion toward the implications for enterprise decision speed. They outline the practical shifts required — reassessing outdated constraints, strengthening data foundations, and using scenario analysis and human‑guided AI to evaluate operational options with greater accuracy and responsiveness. This episode is sponsored by Optilogic. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner