The AI in Business Podcast

Legacy enterprises are facing a decisive shift from stalled pilots and fragmented data toward agentic systems that reshape customer experience, operations, and net‑new revenue.   Matt Renner, President and Chief Revenue Officer at Google Cloud, examines how leaders can move beyond early AI failures to build modern data foundations, orchestrate heterogeneous agents, and accelerate transformation in...

The rapid expansion of AI‑driven knowledge work is exposing a growing tension: teams are moving faster across more surface areas, but their context is fragmented across tools, personal systems, and ad‑hoc workflows.   In this episode, Tsavo Knott, CEO and co‑founder at Pieces, examines how the shift toward AI‑native individual contributors requires a unified substrate for capturing and retrieving...

Visual AI gets stuck not because the technology fails, but because enterprises cannot move it from controlled environments into the variability of daily operations. In this episode, Brian Ton, Senior Laboratory Manager at Florida Crystals Corporation, examines why building operational trust in visual AI requires more than a successful pilot — and what actually determines whether a deployment becom...

A growing reliance on data‑driven systems is creating tension for enterprise leaders between operational efficiency and the human judgment required for high‑risk, high‑reward decisions. In this episode, Kun He, Lead Scientific Advisor at Bayer, examines how AI improves agricultural decision‑making while still leaving critical gaps that only human intuition and risk tolerance can fill, in conversat...

A growing share of enterprise work now depends on systems that can support both human and AI agents, exposing bottlenecks in coordination, governance, and cross‑functional process design. In this episode, Debanjan Saha, Chief Executive Officer at DataRobot, examines how enterprises can rebuild their operational architecture to support digital employees at scale in conversation with host Daniel Fag...

Enterprise IT teams are drowning in alert volume as cloud, microservices, and CI/CD pipelines outpace what human operators can process. In this episode, Assaf Resnick, CEO and Founder at BigPanda, examines how agentic AI can shift IT operations from reactive troubleshooting to a prevention-first model built on an enterprise IT knowledge graph. The conversation covers how to build and own that know...

As financial institutions move beyond AI experimentation, the primary bottleneck is no longer capability; it is governance. In this episode, Yoav Naveh, Co-Founder and Co-CEO at Reindeer AI, examines how enterprises can operationalize agentic AI inside regulated financial workflows, including the two-loop oversight model that keeps agents compliant, self-correcting, and continuously improving. The...

Enterprise AI adoption is moving faster than security and governance frameworks can follow,  forcing organizations to make difficult trade-offs between competitive urgency and operational risk. In this episode, Jason Loomis, CISO at Freshworks, examines why most enterprises have not yet resolved the tension between AI deployment speed and security maturity, and outlines a sequenced approach; begin...

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 ad...

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...

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 lea...

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...

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...

Enterprise AI initiatives consistently break down in document-heavy environments, not because the underlying models are inadequate, but because fragmented data silos, page-break context loss, and uncoordinated extraction tools erode the semantic layer AI needs to reason accurately. In this episode, Sumedh Chaudhary, CTO US Industry Market at IBM, breaks down why a multi-agent architecture is the o...

Significant enterprise investment in AI-driven customer service is producing inconsistent outcomes — and the gap between deployment ambition and measurable business value remains striking. In this episode, Shri Nandan, VP of AI Products and Experiences at Comcast, examines why organizational culture and readiness are the primary determinant of whether AI in CX delivers results that move the needle...

Retailers managing pricing, marketing, and inventory through separate teams with separate data are losing margin not to market volatility, but to decisions that were never designed to work together. In this episode, Felix Hoffmann, CEO at 7Learnings, examines how predictive, unified commercial decision-making replaces reactive, rules-based approaches — and why most retailers underestimate how much...

Enterprise software costs are rising while vendor performance often isn't, and AI has fundamentally changed what enterprises can credibly threaten to build in-house. In this episode, David Cost, Chief Digital Officer at Rainbow Apparel, explores how enterprise leaders can restructure vendor contracts to maintain exit leverage, eliminate auto-renewal traps, and use AI-enabled build alternatives as...

Finance teams are being asked to influence outcomes in real time while operating on architectures built for delayed, aggregated, and heavily reconciled data. In this episode, Alex Curran, CEO at Aptitude Software, examines how finance functions can move toward real‑time, event‑level visibility and discusses this shift with host Dan Faggella. She highlights the practical changes required for CFOs —...

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 scal...

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 Fagge...

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 thou...

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...

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 commercia...

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 agen...

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...