app_store_button

google_play_button

DK - Details page - Device banner - 894x1036

Lyt når som helst, hvor som helst 

Daniel Faggella

The AI in Business Podcast is for non-technical business leaders who need to find AI opportunities, align AI capabilities with strategy, and deliver ROI.

Each week, Emerj research staff and journalists interview top AI executives from Fortune 2000 firms and unicorn startups - uncovering trends, use-cases, and best practices for practical AI adoption.

Visit our advertising page to learn more about reaching our executive audience of Fortune 2000 AI adopters: https://emerj.com/advertise

The AI in Business Podcast

Generative AI is entering clinical workflows just as healthcare institutions grapple with black-box outputs, unclear regulation, and the need for provable accuracy. In this episode, Rhett Alden, CTO at Elsevier, joins Emerj's Yolandi de Weerdt to articulate how claim-level validation and transparent sourcing are becoming prerequisites for clinical trust in AI. The conversation covers emerging AI governance boards modeled on clinical trial review structures, the limits of current US regulation, and why final clinical responsibility remains with the physician.
 
 Learn the strategies Emerj uses to help leading AI brands and startups connect with their ideal enterprise AI buyers: emerj.com/AD1

Responsible Generative AI in Healthcare and What Leaders Need to Know for 2026 - with Rhett Alden of Elsevier Health

For AI systems built into vehicles, robots, and industrial equipment, being smart isn't enough — the difference between success and failure often comes down to whether real-time performance was designed in from the start or added on afterward. In this episode, Drew Barbier, Vice President, IP Business Unit at MIPS, breaks down why starting with the software workload, rather than the hardware, produces measurably better outcomes in real-time compute design. The conversation covers a real-world example of a three-to-five-times performance gain from workload-first design, what changes on a team's side when real-time becomes a starting requirement instead of an afterthought, and how leaders can tell within six months whether their approach is working.
 
 This episode is sponsored by MIPS.
 
 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

Building AI Into Systems That Can't Afford to Be Late - with Drew Barbier of MIPS

Enterprise sales teams routinely let the majority of inbound leads go untouched simply because there isn't enough team bandwidth to work them all. In this episode, Vanessa Tabbert, VP of Agentic Transformation and Sales Development at Salesforce, breaks down how her own team deployed an AI SDR agent to recover leads that would otherwise go cold, without replacing the humans who convert the best ones. The conversation covers how to identify a low-risk first use case, why an AI agent should be coached and measured like a team member rather than launched and left alone, and how the same approach scales down to a small SMB sales team.
 
 This episode is sponsored by Salesforce. ​ To learn the exact strategies we use to help leading AI brands and startups connect with their ideal enterprise AI buyers, visit: emerj.com/AD1

AI-Powered Revenue Operations: The Future of Sales for SMBs - with Vanessa Tabbert of Salesforce

Large B2B operations keep running order entry, invoicing, and other repetitive back-office workflows by hand, years after most companies started investing heavily in AI. In this episode, Chris Bradley, Chief Marketing Officer and Head of AI Transformation at Veritiv, breaks down why legacy systems have kept agentic AI out of these workflows, and what changed once Veritiv began automating a process handling 1.7 million orders a year. The conversation covers the audit-trail controls needed to trust an agent with an end-to-end task, how a supervising AI agent checks another agent's work, and how to pick a first automation target based on headcount concentration rather than project size. ​ If you offer AI products or services into the enterprise, you need to find enterprise leaders with relevance and readiness. Emerj attracts VP+ enterprise audiences who are already convinced that they need to move beyond traditional IT. To learn the exact strategies we use to help leading AI brands and startups connect with their ideal enterprise AI buyers, visit: emerj.com/AD1

Where Agentic AI Pays Off in the B2B Back Office - with Chris Bradley of Veritiv

Industrial environments run on a different set of constraints than the typical enterprise office — physical risk, standalone factory sites, and workflows where a fragmented handoff can cost time, quality, or worse. ​ In this episode, Scot Burdette, Global CIO of Measurement & Analytics at ABB, examines why industrial AI has to be built around knowledge capture, human-in-the-loop oversight, and frontline usability, and shares how ABB's own tools are helping a retiring generation's expertise transfer to the workers replacing them, with Emerj host Marilie Fouché. ​ He outlines the practical shift underway, from siloed, tribal knowledge toward a shared operational data layer, and from pilots that prove a concept to the design and implementation work that changes how a factory runs. ​ This episode is sponsored by Poka. To learn the exact strategies we use to help leading AI brands and startups connect with their ideal enterprise AI buyers, visit: emerj.com/AD1

The Real‑World Conditions That Shape Industrial AI - with Scot Burdette of ABB

Job titles routinely undercount what employees can actually do, especially in fast-moving technical roles. In this episode, Cory Hymel, Head of Research at Andela, explores why mapping skills instead of roles gives leaders a far more accurate picture of workforce capability and AI readiness. The conversation covers how continuous skills assessment, rather than one-time training, keeps pace with a technical skill half-life that's now down to two or three years. This episode is sponsored by Andela. Learn how select AI vendors reach Fortune 500 decision-makers through Emerj's research and media platforms. Download our media kit at emerj.com/AD1

Closing the Skills Intelligence Gap in the AI Era - with Cory Hymel of Andela

A quarter of enterprise teams have gotten a single AI channel into full production — the rest are stuck somewhere behind it. In this episode, Arun Chandra, Chief Operating Officer at NiCE, explores why that gap persists and what closes it. The conversation covers getting data, knowledge, and organizational context ready for scale, building the financial case for AI investment with the CFO, and how open protocols like MCP are reshaping enterprise architecture decisions. This episode is sponsored by NiCE Cognigy. Learn how leading organizations approach AI investment more like a venture portfolio, and why interdisciplinary collaboration is critical to defining the right data for AI success. Download our free PDF report, "Beginning with AI," at emerj.com/aik1

Scaling Agentic Automation With Open Architecture - with Arun Chandra of NICE

The service environment is straining under rising equipment complexity and a rapidly shrinking technician workforce, making patient‑critical uptime harder to guarantee. In this episode, Michael Goldman, Senior Director of Business Operations and Transformation at Patterson Dental, examines how AI can preserve service continuity by capturing institutional knowledge, supporting technician workflows, and enabling earlier, more accurate equipment diagnostics — in conversation with host Yolandi de Weerdt. Learn how leading brands and AI startups connect with enterprise AI buyer audiences at scale, download our media kit at emerj.com/AD1

AI for Patient Critical Uptime in a Shrinking Technician Workforce - with Michael Goldman

Enterprise engineering teams often spend more time triaging recurring incidents than building the features customers are asking for. In this episode, Dave Glick, Senior Vice President of Growth Technology at Walmart, explores how his teams are using AI agents to catch and fix small, recurring issues before they turn into support tickets. The conversation covers the internal tools Walmart built to scale this work, the governance model that keeps experimentation safe, and why closing the distance between engineers and the people using their tools speeds up every iteration. ​ This episode is sponsored by BigPanda. If you offer AI products or services into the enterprise, you need to find enterprise leaders with relevance, and readiness. Emerj attracts VP+ enterprise audiences who are already convinced that they need to move beyond traditional IT. To learn the exact strategies we use to help leading AI brands and startups connect with their ideal enterprise AI buyers, visit: emerj.com/AD1

Intelligent Operations at Enterprise Scale - with Dave Glick of Walmart

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

How Leaders Build for the Next Era of Compute - with Sam Grove of MIPS

One facet of business that nearly any industry has in common is the need to stay on top of news in their respective market, including competitor strategies or understanding changes in news related to the field. Media monitoring is a domain that machine learning (ML) is well suited for, with it's ability to coax out headlines, contextual information, and financial data from the seemingly endless stream of social, blog, and other information on the web today. Signal is a company that uses ML specifically for these purposes. In this episode, we speak with Signal Media's Chief Data Scientist and Co-founder Dr. Miguel Martinez, who dives into real business use cases illustrating the use of machine learning for media monitoring across industries.

Machine Learning for Media Monitoring - with Signal Chief Data Scientist

Lyt når som helst, hvor som helst

Other podcasts you might like ...