
Hosted by Emerj AI Research · EN

The shift from guarded, siloed data access to fully agentic, end‑to‑end AI workflows is forcing enterprises to rethink how accuracy, access control, and security must operate when anyone can query sensitive information through natural language. In this episode, Anahita Tafvizi, Chief Data & AI Officer at Snowflake, joins Daniel Faggella, Emerj CEO and Head of Research, to examine how robust governance, role‑based access control, and embedded data teams enable trustworthy AI agents that automate high‑value workflows across finance, sales, HR, and other regulated functions. The discussion highlights practical decisions around securing new points of entry, standardizing metrics, and designing repeatable agentic workflows that move enterprises from systems of record to systems of action. To listen to the conversations other infrastructure and AI leaders in the Fortune 500 are tuned into, subscribe to the AI infrastructure podcast at emerj.com/inf1

Legacy enterprises are being forced to rethink how they modernize data, infrastructure, and operating models as agentic systems begin reshaping workflows once defined entirely by humans. In this episode, Matt Renner, President and Chief Revenue Officer at Google Cloud, joins host Daniel Faggella and examines how AI maturity, data modernization, and agent orchestration are becoming the new backbone of enterprise transformation. The discussion highlights practical shifts in executive fluency, data strategy, orchestration platforms, and the processes required to move from isolated pilots to scalable agentic operations. To learn how leading brands and AI startups connect with enterprise AI buyer audiences at scale, download our media kit at http://emerj.com/AD4

Uptime expectations in energy and infrastructure environments are tightening, while the skilled‑trades gap and rising asset complexity are making traditional, date‑based maintenance models increasingly unsustainable. In this episode, Joe Lang, Vice President of Service Technology and Innovation at Comfort Systems USA, examines how real‑time equipment data, technician‑centric tooling, and disciplined asset organization are becoming essential to operating reliably in zero‑tolerance environments — in conversation with host Yolandi de Weerdt. He highlights the practical shifts required to move from reactive to prescriptive maintenance, including structuring asset data, capturing accurate field information, and properly resourcing modernization efforts across distributed service teams. This episode is sponsored by Aquant. 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/ait4

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 Faggella Emerj CEO and Head of Research. He highlights the practical shifts required — from identity and access control to auditability, simulation, and cross‑system orchestration — that enable agents to take on back‑office and cross‑functional work reliably and safely. Learn how to identify 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/ait4

AI is moving into the physical economy, and enterprises are now confronting the infrastructure decisions required to support model‑driven systems in logistics, manufacturing, transportation, and other asset‑heavy environments. In this episode, Drew Henry, Executive Vice President for Physical AI at Arm Holdings, joins Emerj CEO Daniel Faggella to examine how leaders can redesign compute and hardware architectures for safety‑critical operations where power, reliability, and integration constraints are non‑negotiable. The discussion focuses on upgrading legacy automation, selecting the right compute for varied AI workloads, and using large‑scale simulation to validate changes before retooling physical systems. Emerj reaches over a million senior operators and AI decision‑makers each year — see how leading AI brands turn that attention into qualified pipeline at emerj.com/AD1

Enterprise leaders are confronting a shift in which infrastructure now encompasses hardware, data platforms, governance, privacy, and the broader foundation required to support AI. In this launch episode of the Enterprise AI Infrastructure Podcast, Daniel Faggella, CEO and Head of Research at Emerj Artificial Intelligence Research, examines how this expanded definition of infrastructure is reshaping what it means to build the modern enterprise in conversation with the host. The discussion highlights the practical implications across hardware choices, data foundations, governance requirements, and the emerging rules of work between people and AI.

AI infrastructure projects are failing not because the technology underdelivers, but because organisations commit capital before establishing the business case. In this episode, Juan Orlandini, CTO at Insight, examines why enterprise AI programs stall and outlines how leaders can apply decades of established IT investment discipline to evaluate, validate, and scale AI initiatives with measurable outcomes in mind. The conversation covers organisational change management across employee adoption segments, the application of FinOps principles to AI infrastructure spending, and a minimum viable proof of concept approach for validating AI investments before scaling. Learn how brands work with Emerj and other Emerj Media options at http://go.emerj.com/partner