The AI in Business Podcast

Consolidating hardware into fewer, more capable chips looks like an unambiguous win — until the complexity those separate components used to handle resurfaces in the software binding everything back together.
 
In this episode, Sam Grove, Head of Software and Tools Business at MIPS, examines why hardware and software teams can't keep building in sequence, and why MIPS bet its roadmap on the open RISC-V standard instead of defending a proprietary instruction set, with host Yolandi de Weerdt.
 
The conversation also covers how tools like MIPS Atlas Explorer help engineering teams see where hardware acceleration pays off before silicon gets committed, and why the real risk in overhauling a build process is rarely the technology — it's bringing already-productive teams along with the change.
 
This episode is sponsored by MIPS.
 
Learn how these conversations drive pipeline for other AI brands — download our media kit at 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

Virtual cell models promise faster, cheaper early-stage drug discovery. However, the industry still lacks a shared way to judge which of these models can actually be trusted on a given problem.
 
In this episode, Kristóf Szalay, CTO and Co-Founder of Turbine, and Gerold Csendes, Scientist at Turbine, set out what virtual cell models can and can't do today, in conversation with host Marilie Fouché. They cover why benchmarking remains fragmented across the field, how pharma teams build confidence in a model before trusting it with real R&D decisions, and how compressing the feedback loop between experiments can cut months out of the discovery process.
 
This episode is sponsored by Turbine.
 
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

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

Most retail AI pilots stall waiting on a years-long project to centralize and clean data before any agent can go live.
 
In this episode, Chris Slovak, Global Field CTO at Unframe, makes the case for a different path: letting agents pull context directly from ERPs, CRMs, and point-of-sale systems as needed, in conversation with host Marilie Fouché. He walks through concrete results from that approach, including an inventory intelligence deployment that saved tens of thousands of dollars in time and data costs, and a deployment cycle that shrank from nine months to two weeks.
 
This episode is sponsored by Unframe.
 
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