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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 a legitimate negotiating tool. The conversation examines the cost-benefit calculus of build versus buy in the AI era, red flags in service-level agreements, and how to negotiate exits from underperforming contracts. This episode is sponsored by UpperEdge. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
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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 — from capturing every financial event at the transaction level to enabling continuous reconciliation and full lineage — so finance can surface exceptions immediately and support decisions as they unfold. This episode is sponsored by Aptitude Software. Learn how financial institutions are digitizing paper-based records to unlock usable data for AI, and using alternative data like public web and social signals to enhance risk assessment. Download our free PDF report, "AI in Financial Services Executive Cheat Sheet" at emerj.com/fcs1
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Saknas det avsnitt?
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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 scale with customer trust intact. The conversation covers the three data foundations required for context continuity in production, practical principles for human-AI orchestration, and why cross-team governance — a single North Star across CX, IT, and operations — is what separates the organizations that scale from those that fragment. This episode is sponsored by NiCE. 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
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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 Faggella, Emerj CEO and Head of Research. The discussion highlights the operational demands of vertical AI, the role of expert‑trained agents, and why human oversight remains essential in high‑stakes professional work. Learn how financial institutions are digitizing paper-based records to unlock usable data for AI, and using alternative data like public web and social signals to enhance risk assessment, download our free PDF report, "AI in Financial Services Executive Cheat Sheet" at emerj.com/fcs1
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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 thousands of scenarios in minutes and make faster, better‑aligned decisions. The discussion highlights how leaders can strengthen resilience by unifying data foundations, building trust in modeling before a crisis, and integrating design‑grade optimization directly into planning cycles. This episode is sponsored by Optilogic. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
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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 baselines, KPIs, and organizational readiness needed to measure and sustain real returns. The conversation covers practical guidance on assessing technological and organizational maturity, avoiding POC-to-production pitfalls, and selecting the right AI tools for specific business contexts. This episode is sponsored by HTEC. In this episode we cover how enterprise leaders can measure and prove AI ROI after deployment. To go deeper on this topic and 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
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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 commercial insight and field execution. The conversation covers what separates teams that successfully adopt AI from those stuck in the pilot phase, and why starting with routine, high-certainty use cases consistently produces more commercial lift than chasing ambitious automation. This episode is sponsored by ODAIA. 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
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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 agents to reason accurately, explain their decisions, and deliver measurable outcomes across customer support, semiconductor engineering, and clinical trial site selection. The discussion covers five practical frameworks for CIOs and chief data officers on building real-time, explainable context layers on top of existing enterprise systems, without ripping and replacing current infrastructure. This episode is sponsored by Arango. To learn how to improve landing page conversion and use self-qualification systems to identify high-intent leads, download Emerj's free PDF report, "B2B AI Lead Generation Guide," at emerj.com/aig2
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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 groundwork for effective AI‑enabled ERP. He highlights the practical sequence for building this foundation so future AI‑driven adaptation becomes seamless rather than disruptive. For AI brands trying to reach senior decision-makers, podcasts are one of the few channels that earn 20+ minutes of focused attention from VP+ leaders. Emerj reaches 1,000,000 listeners annually — see how other AI brands are driving pipeline: emerj.com/AD1
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Regulatory volatility, scientific‑grade context requirements, and entrenched legacy processes are creating a level of operational complexity in pharma that makes even high‑value AI initiatives difficult to move from concept to production. In this episode, Art Shectman, CEO at Elephant Ventures, examines with host Marilie Fouché how leaders can cut through that complexity by isolating a single, clearly defined workflow slice and rebuilding it for near‑term, dependable deployment rather than long‑range architectural perfection. The discussion highlights how removing outdated process assumptions, selecting an atomic workflow with organizational alignment, and aiming for a contained operational win enable pharma teams to build momentum and scale AI responsibly in highly regulated environments. 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
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Individual AI productivity gains are already here, but they are uneven, and they are not the main event. In this episode, Tim Sears, Chief AI Officer at HTEC, argues that the real transformation in software development will arrive when AI becomes a catalyst for teamwork rather than an enhancer of individual performance. The conversation examines why software development is the clearest available model for how AI will eventually reshape every business function, how the developer role is being elevated from syntax and grunt work toward architecture, security, and client judgment, why the traditional build-versus-buy decision is being replaced by a build-versus-build reality, and what it will mean when perfection in enterprise software becomes the expected standard rather than the exception. For senior leaders trying to move from supporting AI in principle to actually delivering change, Sears offers a direct and practitioner-grounded view of what needs to change in teams, in expectations, and in the way business processes are understood and redesigned. AI is moving fast — new tools, new research, new use cases every week. Emerj synthesizes what matters most, so senior leaders and practitioners can stay ahead without getting buried. Join 85,000+ subscribers and get the most useful AI business insights delivered to your inbox. Visit: http://emerj.com/ad1
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The skilled labor crisis in industrial equipment service is not a future problem; it is eroding operational performance now, as retiring engineers take decades of institutional knowledge with them and incoming technicians cannot fill the gap at speed. In this episode, Mike Hughes, Group Service Director at Peak International Group, outlines how service organizations can close the expertise gap through smarter knowledge capture, targeted AI deployment, and a frontline-first approach to modernization. The conversation covers remote diagnostics, first-time fix performance, the realities of working with imperfect data, and the two or three use cases leaders should prioritize before attempting a broader transformation. This episode is sponsored by Aquant. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
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A widening gap has emerged between the speed of AI innovation and the ability of large enterprises to deploy it responsibly, leading many organizations to repeat avoidable mistakes in scaling. In this episode, Shaje Ganny, Author, Guest Lecturer, TEDx Speaker, and Digital Transformation Director at Procter & Gamble, joins Matthew DeMello to examine how leaders can ground AI adoption in clear business value and human-centered operational design. The discussion highlights practical considerations for evaluating AI through its impact on the company, the consumer, and the surrounding workforce community, and the executive education and policy foundations required to move from pilots to reliable enterprise deployment. 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 http://emerj.com/AD1
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The rapid shift from seat‑based licensing to hybrid and consumption‑based AI pricing has made technology spend significantly harder for enterprises to predict and control. In this episode, Adam Mansfield, Practice Leader at UpperEdge, examines how these new pricing models create financial exposure for buyers and why clear forecasting, transparency, and leverage are increasingly difficult to secure in negotiations with major vendors, in conversation with host Marilie Fouché. He highlights the practical steps leaders must take now — from auditing current usage and identifying under‑leveraged spend to engaging vendors early and using the broader. This episode is sponsored by UpperEdge. To go deeper into vendor negotiations and learn how to assess AI providers by leadership credibility and funding signals, download our free report, "5 Ways to Select the Right AI Vendor," at emerj.com/aiv3
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Enterprise AI initiatives treat design as a finishing step. Carsten Wierwille, Chief Product & Design Officer at HTEC, argues that this is a strategic mistake, and one that explains why so many AI investments produce tools that work technically but fail to change how people actually work. In this episode, Wierwille examines why enterprises keep building AI because they can rather than because they understand the problem, how the shift to AI-assisted ideation has moved the bottleneck from creation to review, and why the answer is not faster shipping but sharper design clarity at the start. The conversation covers the financial advisor as a model for AI force-multiplication, why the MVP framework breaks down for genuinely novel AI experiences, how design now extends to defining the evaluation criteria for AI output, and what Wierwille calls cognitive design, the practice of thinking about how users will perceive, decide, and trust before anyone writes a line of code. This episode is sponsored by HTEC. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
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Computer vision implementations in manufacturing never advance beyond the pilot phase — not because the technology fails, but because deployment is treated as a software problem rather than an operational one. In this episode, Jeff Witt, Digital Transformation Leader at a Fortune 500 global leader in building materials and fiberglass composites, examines the architectural, organizational, and change management decisions that determine whether a vision AI initiative reaches production and scales. The conversation covers how to build a reusable data architecture for vision data, why shifting ownership from IT to business units accelerates deployment, and what a platform mindset — versus a point solution approach — looks like in a multi-site manufacturing environment. This episode is sponsored by Roboflow. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
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The growing use of AI‑driven modeling in clinical development is exposing how limited traditional, single‑study dose selection and patient assessment methods have been for complex oncology programs. In this episode, Shefali Kakar, Global Head of PK Sciences and Oncology at Novartis, examines how deeper data integration across phases enables more precise dose decisions, clearer safety interpretation, and a more consistent understanding of patient variability alongside host Matthew DeMello. She outlines how longitudinal analysis, exposure–response modeling, and covariate evaluation are helping teams reduce unnecessary sub‑studies, tailor dosing for diverse patient groups, and strengthen cross‑functional decision‑making throughout development. According to Nielsen, 91% of podcast listening happens alone, creating a focused, distraction-light environment well suited for complex B2B messaging.
Learn how leading brands and AI startups connect with enterprise AI buyer audiences at scale by downloading our media kit at go.emerj.com/partner -
The pressure on financial services AI leaders to show board-level results has intensified — yet the pace of vendor pitches, shifting tooling stacks, and stalled pilots has made action feel riskier than waiting. In this episode, Art Shectman, CEO and Founder at Elephant Ventures, breaks down why the instinct to evaluate everything before building anything is the primary obstacle to production, and what a realistic first step actually looks like inside a regulated enterprise. The conversation covers how to identify the right initial workflow, how to structure a time-boxed sprint toward a minimum viable production deployment, and how to present early AI wins to boards that have stopped trusting strategy decks.
This episode is sponsored by Elephant Ventures. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner -
The reason enterprise AI programmes stall is not the technology — it is the sequence in which decisions are made before and after the pilot succeeds. In this episode, Ronny Fehling, Chief AI Transformation Officer at HTEC, examines why AI initiatives lose momentum at the production threshold and what organisational conditions determine whether they make it through. The discussion covers production slices, decision gates with kill-switch authority, use case discipline, and why top-down AI mandates tend to reproduce the same failure modes regardless of budget. This episode is sponsored by HTEC.
Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner -
Deepfake voice fraud is not bypassing enterprise security technology, it is beating the workflows agents rely on to make trust decisions in real time. In this episode, Jon-Rav Shende, Global CTO for Data and AI at Thales Group, outlines where enterprise voice channels are most exposed, why identity, urgency, and business action converging in a single call represents the highest risk point, and what a practical four-step response framework looks like for regulated organisations. The discussion covers how to map risky voice journeys, define escalation decision points, build the evidence chains auditors and cyber insurers will require, and deploy AI as a risk signal layer without automating high-risk actions beyond appropriate controls. This episode is sponsored by Modulate. Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner
- Visa fler
