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Lyt når som helst, hvor som helst 

Daniel Faggella

The AI in Financial Services is for non-technical financial services leaders looking to find AI opportunities, build an AI strategy, and deliver ROI.

Each week, Emerj AI Research team (and CEO Daniel Faggella) interview leaders from global financial services firms and unicorn AI startups to get to the heart of AI ROI - uncovering what's working and what's not working for FinServ leaders.

Visit our advertising page to learn more about reaching our executive audience of AI adopters in the world's largest banking and insurance firms: https://emerj.com/advertise

AI in Financial Services Podcast

Enterprise AI investment keeps stalling before it reaches measurable business impact, and the reason is rarely the technology itself. In this episode, Sam Mantle, CEO at Lingaro, unpacks why data quality and ownership, not model capability, determine whether a pilot scales into something a CFO will call a win. The conversation covers how to diagnose a pilot headed for "pilot purgatory," a real-world example of using AI to resolve data-quality issues at scale, and the one practical step leaders can take this week to move from AI experimentation to impact. ​ This episode is sponsored by Lingaro. ​ In this episode, we cover why enterprise AI pilots stall before delivering measurable business impact, and what it takes to build the data foundation that lets AI scale.
 
 Learn how venture funding and CEO perspectives can reveal real AI trends. Download the free report, "3 Ways to Discover AI Trends in Any Sector," at emerj.com/ait2

How Leaders Close the Execution Gap in Modern AI Deployment - with Sam Mantle of Lingaro

A growing share of AI‑for‑CX guidance assumes a generic enterprise environment, but this episode surfaces the deeper operational friction that emerges when automation meets high‑stakes, highly regulated customer interactions. In this episode, Shri Nandan, VP of AI Products and Experiences at Comcast, examines how regulatory constraints, fragmented data ownership, and emotionally or legally sensitive workflows reshape what AI can realistically deliver in healthcare and financial services alongside host Yolandi de Weerdt. She highlights the practical shifts required for leaders to scale AI safely and effectively — from establishing tight governance and unified data foundations to designing agent systems that know when to escalate and when to automate. Learn how these conversations drive pipeline for AI brands - download our media kit at http://emerj.com/AD2

Precision CX in Regulated Industries - with Shri Nandan of Comcast

AI is breaking down the traditional separation between technology leadership and people leadership, forcing enterprises to rethink how work is structured and how employees adopt new systems. In this episode, Guillaume Lardeux, Head of Transformation and Office of the CEO at Genesys, and Eva Majercsik, Chief People Officer at Genesys, examine how AI-driven workflow redesign requires shared ownership across functions, as discussed with host Marilie Fouché. They highlight the practical shifts involved — mapping current processes, identifying friction points, rebuilding workflows where humans and AI operate together, and supporting adoption through cultural alignment and iterative experimentation. Learn the strategies we use to help leading AI brands and startups connect with their ideal enterprise AI buyers, visit: emerj.com/AD2

The Leadership Alignment Required to Turn AI Into Enterprise Value - with Guillaume Lardeux and Eva Majercsik of Genesys

Enterprises rushing agentic AI into production are running it through approval gates, batch windows, and audit systems built for human speed — and the gap is where most operational risk lives. In this episode, Chris Caldwell, President and CEO at Concentrix Corporation, examines how machine-scale transactions break processes designed for human pace and why bounded digital delegates outperform unrestricted digital twins in the enterprise. The discussion covers compliance bots that check other bots, the cost reality of poorly tuned agentic agents, and what leaders need to stop doing if they want a defensible AI roadmap. Learn how to evaluate AI vendors by assessing leadership expertise, and why funding benchmarks can signal product maturity and stability, download our free PDF report, "5 Ways to Select the Right AI Vendor," at emerj.com/aiv2.

AI Assistants and Preparedness Among Enterprises - with Chris Caldwell of Concentrix

A fundamental shift is emerging as AI moves core financial operations away from traditional web interfaces and into AI‑native cloud‑desktop environments, redefining how CFO teams execute and manage workflows. In this episode, Henry Ward, founder and CEO at Carta, examines how this transition changes the CFO operating model alongside host Daniel Faggella, highlighting why AI‑literate finance leaders gain leverage by orchestrating reporting, close processes, and analysis directly through agent‑driven systems. The discussion outlines how reusable AI skills, shared operational source files, and automated coordination reshape month‑end close, reporting agility, and cross‑team execution for modern finance organizations. To go deeper on this topic and 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/fcs2

The AI Driven Finance Stack for High Growth Financial Services - with Henry Ward of Carta

AI programs in financial services don't fail at the model; they fail at the seam between pilot and production, where data, integration discipline, and ownership decide whether anything reaches scale. In this episode, Jeremy Caine, Technology Strategy and Solution Leader at IBM, unpacks why banks and insurers get stuck in pilot purgatory and what an AI-native future state actually looks like in a regulated environment. The conversation covers a data product strategy that surfaces the data that matters for the use case, the industrialized software delivery lifecycle required to move AI into production, a platform-led architecture built on open foundations and automation, and the operating model shifts senior leaders need to make to convert AI investment into durable business capability. Learn how brands work with Emerj and other Emerj Media options at http://go.emerj.com/partner

How the AI-Native Bank Stops Adding Pilots and Starts Industrializing - with Jeremy Caine of IBM

Stabilizing the operational environment around underwriting judgment is the shift that enables decisions to move into the market with greater speed, consistency, and control. In this episode, Barbara Stacer, Vice President, Head of Small Commercial Underwriting and Underwriting Operations at Utica National Insurance Group, examines how governed versioning, traceable approvals, and embedded documentation close the execution gap that slows pricing changes after they leave actuarial. She outlines the practical steps leaders can take to reduce queue time, strengthen auditability, and ensure pricing updates reach production when they matter most. Learn how brands work with Emerj and other Emerj Media options at https://go.emerj.com/partner1

AI‑Ready Underwriting Operations While Maintaining Decision Consistency - with Barbara Stacer of Utica National Insurance Group

AI infrastructure projects are failing not because the technology underdelivers, but because organizations 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 organizational 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.

Turning Infrastructure from Bottleneck to Business Enabler for AI - With Juan Orlandini of Insight

Architectural decision‑making in large enterprises can break down when system knowledge is fragmented, slowing delivery and creating inconsistent outcomes across teams. In this episode, Amar Akshat, Senior Vice President of Architecture at PaySafe, examines how codified organizational memory and deterministic guardrails enable intelligent systems to accelerate development without sacrificing control. He highlights the shift toward machine‑readable decision records, intent‑driven interfaces, and standardized design patterns that help enterprises reduce drift, strengthen compliance, and move faster with greater confidence. Learn how brands work with Emerj and other Emerj Media options at http://go.emerj.com/partner

How Intelligent Systems Accelerate Enterprise Decisions - with Amar Akshat of Paysafe

Regulated industries are facing mounting pressure to adopt AI while maintaining absolute accuracy, data protection, and clear human accountability. In this episode, Steve Hasker, CEO at Thomson Reuters, joins Emerj's Matthew DeMello to examine how these demands are reshaping expectations for model reliability, data isolation, and the future of high‑stakes regulatory work. The discussion highlights the need for transparent guardrails, expert‑trained systems, and new approaches to handling large‑scale filings without compromising oversight. Want to share your AI adoption story with executive peers? Click go.emerj.com/expert1 for more information and to be a potential future guest on Emerj's flagship 'AI in Business' podcast! Learn how brands work with Emerj and other Emerj Media options at go.emerj.com/partner

How AI Is Reshaping Regulated Professional Workflows - with Steve Hasker of Thomson Reuters

Our guest this week, Madhu, works at one of the top 10 Australian banks. He has a lot of experience applying AI in customer service. Madhu speaks about how to grow an AI team, when to hire data scientists, when to hire someone to lead those data scientists, and what kinds of talent needs to be there to help guide data scientists. 
 
If you're interested in learning more about our AI Opportunity Landscape work in the financial services industry, watch our video at emerj.com/fs1.

Scaling a Data Science Team the Right Way

Lyt når som helst, hvor som helst

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