Episodes
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Today’s guest is Kai Schrimpf, Global Head of Transaction Monitoring at UBS. UBS is a financial services organization doing more than $35 billion in annual revenue based in Zurich and Basel, Switzerland. In this episode, we dive into compliance in the banking and financial services space. There are three distinct topic areas in today’s episode. First, Kai provides a big-picture perspective on the state of compliance in banking and financial services today and current workflows that could be leveled up. Secondly, he discusses specific use-cases and describes areas where he sees data ‘wake up’ in terms of its value for keeping firms in line with regulatory standards. Lastly, Kai shares some business advice for enterprise leaders and speaks about what business leaders should know before adopting artificial intelligence in a financial services organization. This episode is part of a series sponsored by Smarsh. In this series, we’re focusing on bringing on global experts in compliance to get varied perspectives on where AI and data are adding value today.
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Today’s guest is Neil Sahota, CEO of ACSI Labs and Chief Innovation Officer at the UC Irvine School of Law. Neil previously worked with IBM for 12 years as a Master Inventor focused on developing new patents with a particular emphasis on big data and analytics. In this episode, we are focused on the legal space. In the first part of this episode, Neil dives into specific use-cases that highlight where AI is impacting law today. He discusses several applications that lawyers, law firms, and legal departments at large enterprises use today with high traction. In the second part of this episode, Neil shares his perspective of the areas in the legal world that he believes are most likely to be disrupted by AI in the next five years. Regardless of industry, Neil provides critical insights about what the future might hold for certain kinds of processes and workflows that are most likely to be automated.
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In this episode, we’re focusing on compliance considerations in the insurance world. Our guest this week is Pardeep Bassi. He is currently Global Proposition Leader of Data Science for WTW, or Willis Towers Watson, a publicly traded financial services firm based in the United Kingdom. This week Pardeep covers two different topics with us. First, he discusses some areas where regulation intersects with AI applications in insurance and what the potential data risks for elements such as transparency, personal data use, etc., are. Secondly, Pardeep dives into how leaders might consider these regulatory rules in their adoption strategy. Not only to meet regulatory compliance rules but also to potentially use AI to address them. This episode is brought to you by Smarsh and is part of a broader series on AI applications for compliance and communications intelligence. To learn more about how to reach Emerj’s global executive audience with Emerj Media, visit emerj.com/ad1.
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Today’s guest is Marshall Choy, Senior Vice President of Product at SambaNova Systems. This episode is part of our AI is Here series, where we’ve talked about the current impact of AI across industries with practitioners and leaders across the United States and Europe. In this episode, we’re focusing on AI adoption trends and what successful AI adopters are doing that others aren’t. Marshall discusses the trends he’s noticed in enterprises adopting AI well from a team perspective, a technology perspective, and a decision-making perspective. He also speaks about some of the differences between the American and European AI ecosystems and what European business leaders may potentially want to consider. This episode is brought to you by SambaNova Systems. To learn more about the AI is Here initiative and to learn more about how you might reach Emerj’s global audience, visit emerj.com/ad1.
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Today’s guest is Aakash Indurkhya, Co-Head of AI at Virtualitics. Virtualitics is a venture-backed firm based in Pasadena, California. In this episode, we discuss what it means to explore our data and identify where the gaps in our data quality or potentially the gaps in essential data fields are. Aakash speaks to us this week about not only what exploration, that is to say, why it’s valuable conceptually – when dealing with tremendous volumes of data, what does exploration accomplish, and where specifically, better exploration can lead to better results? He dives into two specific use-cases, one in drug development and one in retail. While these are vastly different worlds, these use-cases focus on exploring data well to train an AI model and deliver the desired results in the enterprise. Aakash provides an excellent conceptual overview from a C-suite vantage point of the role. Virtualitics sponsor this episode. To learn more about reaching Emerj’s global executive audience and sponsored opportunities, visit emerj.com/ad1.
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Today’s guest is Mark Russinovich, CTO of Microsoft Azure. In this episode, we focus on large language models, and Mark speaks with us about two distinct topics. First, he discusses actual, in-the-field applications of large language models today. Mark goes over several of them, but one use-case with Carmax is particularly useful for natural language generation in an enterprise use-case. Secondly, Mark talks about what he would recommend for enterprise leaders who would like to look at their own business and identify where they can apply the value of large language models within their enterprise and the particular workflows that might be optimal for LLMs. This episode is sponsored by Kisaco Research. This year, the Kisaco Research AI Hardware Summit takes place from September 13th through September 15th at the Santa Clara Marriott in California. Mark is among many distinguished speakers, including infrastructure and AI leaders at Meta, Wells Fargo, Salesforce, and more.
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Today’s guest is Brandon Carl, EVP of Product Strategy at Smarsh. Smarsh is a substantial player in the compliance domain in financial services, and in this episode, we’re focusing on AI applications in compliance for the industry. Brandon discusses three critical points in this interview. First, he discusses what kind of communications data may serve as financial crime signals or, in other words, what varieties of communications data we should pay attention to. The second point Brandon focuses on is how we can use that data to unlock value and detect financial crime with AI. Lastly, he speaks about how leaders can find the low-hanging fruit in their own communications data. This episode is the first of a sponsored series here on The AI in Business Podcast by Smarsh. Be sure to tune in on Thursdays to gain more insights about compliance and communications intelligence with new episodes of this series.
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Our guest today is Richard Schak, Senior Technical Account Manager, and Fraud Product Strategy Consultant at Datavisor. In this week’s episode, Richard discusses two key topics: how payment processing fraud is detected with AI and what these workflows look like before and after AI is applied. Richard also shares a specific perspective about where data and algorithms fit into the mix and emphasizes the importance of “lighthouse projects,” or the early projects that can be used to prove potential ROI to get leadership to approve larger projects and enable enterprises to level up fraud detection as a capability. This episode is brought to you by Datavisor. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.
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Today we are focusing on the domain of data collection and quality. Our guest is Christian Rozsenich, Managing Director of Clickworker. In this episode, we talk about a few topics broadly applicable to any industry. The first is the general challenges and importance of data quality and data harmony for AI projects. Christian details the kinds of issues enterprises are running up against and how they can diagnose their own data needs. The next topic we highlight is real-world use-cases of computer vision and computer voice. Christian explains how data is collected and processed for crowdsourcing applications and more. This episode is sponsored by Clickworker. To learn more about Emerj Media and how to reach our global executive audience, be sure to visit emerj.com/ad1.
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Today’s guest is Caroline Gorski, Chief Executive Officer for R2 Factory at Rolls-Royce. As the world’s second-largest aircraft engine maker, Rolls-Royce makes all kinds of large and heavy machinery that require numerous parts. In today’s episode, we explore the questions of how to source those necessary parts and leverage AI to achieve greater transparency in our supply chain. Caroline discusses where AI is making a dent in the industry today. She also provides a glimpse into the future with her perspectives on how companies will deal with supplies and how outside data sources might affect the supply chain and, consequently, estimated arrival dates for various parts from vendors around the world. This episode is part of our AI is Here series sponsored by SambaNova Systems. Find out more about sponsored content and how to engage with the Emerj audience at emerj.com/ad1.
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Today, we’re diving into AI and its applications in the energy sector. Our guest is Andrey Konchenko, Senior Product Manager at DroneDeploy. Andrey previously spent fifteen years at Schlumberger, a gigantic firm with 100k+ employees in the energy sector, and he now works on drones, robotics, and computer vision at DroneDeploy. We discuss three main topics in today’s episode. First, what has made artificial intelligence relevant for business leaders in the energy sector now? Second, we explore individual use-cases for ground robotics, flying robotics, and some novel computer vision applications. Lastly, Andrey provides adoption advice for leaders who are considering this technology in the energy space. This episode is brought to you by DroneDeploy. To learn more about reaching Emerj’s global audience, visit emerj.com/ad1.
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In this week’s episode, we’re discussing a topic that applies across industries for AI projects: where is the data coming from? Our guest is Dora Boussias, Senior Director for Data Strategy and Architecture at Stryker. Stryker is a $17B per year company in the medical device space. She discusses the process of building out a data strategy with a key emphasis on the right questions to ask, such as: how can we organize and focus our vision and efforts to be able to unlock the data that’s likely to be the most valuable for today’s projects and for the future of AI projects as well? The opinions in this episode are the guest's personal opinions and do not represent Stryker's opinions in any way. If you’re interested in accessing Emerj’s best practices and frameworks for AI ROI, AI strategy for building AI roadmaps, and our full library of AI use-cases, you can learn more at emerj.com/p1.
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This is another episode in our AI is Here series. We’ve covered all sorts of industries in this recent series, from financial services to oil and gas, but we’ve yet to touch on defense. Our guest today is Jared Dunnmon. Jared is a Ph.D. from Stanford in Artificial Intelligence and is now the Technical Director of AI and Machine Learning for the Defense Innovation Unit (DIU). In this episode, we explore two key themes: individual use-cases and capabilities that are becoming important and the adoption of AI in the defense industry today. Jared highlights how we can find patterns in data in the world and the must-knows in the enterprise to get AI off the ground. This AI is Here episode is brought to you by SambaNova Systems. To learn more about Emerj Media and how to engage with the Emerj audience, visit emerj.com/ad1.
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Today we’re discussing the topic of leveling up software tools with AI capabilities. Our guest is Matt Berseth. Matt is the CIO and one of the co-founders of NLP Logix, an AI services firm. A few weeks ago, Matt joined us to discuss the analogy of pizza vs. lasagna or what it means for AI to go from playing at the surface to become part of a software solution. In this episode, Matt gives examples of this transformation happening in the real world. Matt discusses where existing software solutions have been leveled up in terms of what they can deliver for value to both the end-user and the organization leveraging it in the public and private sectors. This episode is brought to you by NLP Logix. If you’re interested in learning more about reaching Emerj’s global audience, visit emerj.com/ad1.
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Today’s episode is the fifth and final part of our series on building an enterprise AI strategy. Our guest is Richard Benjamins, Chief AI & Data Strategist at Telefónica and author of “Data-Driven Company.” Telefónica is a $40B firm and one of the largest in the telco space in the EU. In this episode, Richard emphasizes the importance of how we collect and handle data at an enterprise level in a way that enables us to support strategy-building. He also shares his opinion on including ethics and governance as part of the strategy-building process and discusses using smaller projects to construct bigger-picture momentum to finalize a strategy. If your company is getting started with AI, download our free guide, “Beginning with AI: 3 Critical Insights for Non-Technical Executives,” at emerj.com/beg1 to learn more about the practical steps for initial AI adoption.
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Today is episode four of five in our series, where we’re focusing on enterprise AI strategy. Our guest today is Adam Bonnifield. Adam is the CEO of Konux, an AI firm based in Germany. One of the key takeaways Adam emphasizes in this episode is that strategy is as much about what you’re not going to do as what you are going to do. He frames the processing of brainstorming about strategy and identifying opportunities in a way that focuses on the things that truly matter. Another critical point Adam makes is the benefit of addressing your enterprise’s existing problems rather than a novel application when it comes to strategy. Adam describes what this looked like within Airbus with lessons that are transferable to any other enterprise. Finally, we discuss the Trinity Model for AI ROI, a tool within Emerj Plus. To learn more about Emerj’s frameworks for AI readiness, ROI and strategy, visit emerj.com/p1.
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Today we dive back into our series on AI strategy and have two more days of episodes coming this week. Today’s guest is Sankar Narayanan, Chief Practice Officer at Fractal. Fractal is a unicorn company working on AI-related projects across industries and is well-known for its work in CPG and several other sectors. In this episode, Sankar explores three critical topics in great depth: finding the correct problems, having a long-term mindset, and building with the user in mind. In particular, being able to consider a less successful project and work backward to create a new process with a much larger likelihood of a user taking it, running with it, and converting it into ROI is one of the most salient points for this interview. He also emphasizes that it’s not about whether the algorithm works or we have the data but whether someone will use it. To access Emerj’s frameworks for ROI, strategy, and more, visit Emerj Plus: emerj.com/p1.
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Today’s guest is Anand Mahurkar, CEO and Founder of Findability Sciences. Based in Boston, Findability Sciences has done a lot of work in the ERP space across different sectors. In this episode, Anand discusses some of the challenges of data access and multiple use-cases for how current ERP data can provide predictive value for estimating demand and customizing prices for different products. Anand also unpacks the importance of ERP and where it’s going in the future. This episode is brought to you by Findability Sciences. If you’re interested in learning more about reaching Emerj’s global audience through our podcast, email, and more, visit emerj.com/ad1.
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This is episode two of five in our series on AI strategy, and today, our guest is Bret Greenstein, Partner at PwC. Bret has worked at many of the largest consulting companies in the world, and he now leads AI efforts at PwC. This special series focuses on building an enterprise AI strategy to align departments and efforts with striving for a long-term and near-term ROI. One of the main themes Bret discusses in this episode is the importance of executive fluency for assessing and building skills. Brett also gives his perspective on balancing a variety of small, disjointed AI projects distinct from business operations and connecting them so that strategy can come to life. Visit emerj.com/beg1 to learn more about the practical steps for AI deployment for non-technical professionals.
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This week we are diving into the topic of AI strategy with a new series devoted to exploring how to build an enterprise-wide AI strategy and align company efforts to optimize long-term ROI while still seeing an immediate return with leaders at top companies. To start the series, we welcome back David Carmona. David is the General Manager for Artificial Intelligence and Innovation at Microsoft. In this episode, David speaks about how Microsoft didn’t get its AI strategy quite right initially and what they learned from their approach. The critical takeaway he shares is educating leadership to bring everyone to a level of solid conceptual understanding of AI. He explains how this educational element became a crucial underpinning for how they turned things around and built a strategy that can help inform where they are going as a company. If you’re interested in unlocking our AI best practice guides, frameworks for AI ROI, and more resources, visit emerj.com/p1.
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