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Today’s guest is Ian Wilson, Managing Director at Strategy 4 AI, a strategy and consulting firm based in Cambridge in the UK. He discusses two crucial topics in this particular episode. First, where can AI actually step in, interact with a customer, and not make it worse but potentially improve? Ian talks about some of those use-cases and how to identify them within a financial services institution. The second main topic Ian discusses is some of the challenges and how to identify where humans may offer a better experience and where it might make more sense to keep them in the loop, and what it will take to overcome that moving forward. Ian will soon join us on our other podcast called “The AI in Financial Services Podcast,” where we specifically focus on use-cases in that industry. Be sure to subscribe to your preferred podcast platform to hear his insights, perspective, and more in that upcoming episode.
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Today’s episode is part of our new sponsored series called “AI is Here,” where we will speak with AI experts across industries and ask them where AI is impacting their industry today and what that means for the future. In this first episode, we’re exploring the energy sector by speaking to an AI expert at one of the world’s largest energy firms: Shell. Today’s guest is Dan Jeavons, VP of Computational Science, Digital Innovation, and IT. In this episode, Dan speaks about leveraging AI to simulate the operations of an energy firm to achieve better business and sustainability outcomes. He also paints a picture of the world we’re headed into, one with a more distributed energy ecosystem where the environment is an even more important consideration for energy firms. This special episode is brought to you by SambaNova Systems. SambaNova believes that AI is here, and we’ve partnered with them to bring you AI trends and impacts affecting different industries today in this new Wednesday series. Find out more about sponsored content and how to engage with the Emerj audience at emerj.com/ad1.
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Today’s guest is Matt Berseth, Co-Founder and CIO of NLP Logix. NLP Logix is a fast-growing AI services firm based in Florida that serves both the public and private sectors. In this episode, we’re exploring the transition from light involvement in data and data science to much more deep participation, where there are a lot of transferable lessons in adoption ideas. We also discuss the lasagna vs. pizza analogy from an excellent past interview. Matt describes how we can take the data leveraged by that product and use it to help the users save time, give them more convenience, or open up more capabilities. He also articulates the gradual process of working at the surface level, learning lessons, and rebuilding some of the core components of a product. This episode is brought to you by NLP Logix. To learn more about Emerj Media and how we help AI services firms reach a global audience, be sure to visit emerj.com/ad1.
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Today’s episode is part of our ongoing AI Success Factors series, where we cover one enterprise AI use-case with a measurable ROI and discuss what made it successful every Monday. Today, we’re going to explore the topic of maintaining railways. Our guest this week is Adam Bonnifield, CEO of Konux. Konux applies its AI technology to the rail space, and in this episode, Adam shares his perspective on a unique use-case between Konux and Network Rail, a large railway firm in the United Kingdom. Adam walks us through why achieving ground truth data was so critical for this project and what it looked like to work together with Network Rail to make those key distinctions in terms of computer vision and imagery that would define the success of the project. Discover more AI use-cases, best practice guides, white papers, frameworks, and more at emerj.com/p1.
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Today’s guest is Ed d’Archimbaud, Co-Founder and CTO of Kili Technology, based in Paris, France. He has previously worked with large financial institutions such as BNP Paribas, which he speaks about in this episode. We focus on two main topics in this episode: first, we discuss some paperwork-heavy workflows tied to compliance and how AI can provide a solution. The second main topic is data-centric AI and what it looks like to put it into action. Towards the end of this episode, Ed shares how he believes subject-matter experts will be critical to the future of democratizing the technology and winning long-term adoption in the financial services industry and elsewhere. This episode is brought to you by Kili Technology. If you’d like to learn more about reaching Emerj’s global executive audience, visit emerj.com/ad1.
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Today’s guest is Michael Berger, Head of Insure AI at Munich Re. In this episode, Michael brings to bear his perspective as someone with technical experience in the industry and as the leader of Insure AI at one of the world’s largest insurance firms. Michael provides a sense of the risks inherent to large AI deployments, from legal risks to physical threats and more. He also discusses how monitoring and pricing risk from an insurance policy standpoint can be updated and act almost as a living document based on the adopting and changing application itself. If you’d like to discover more financial services use-cases, be sure to subscribe to our other show, The AI in Financial Services Podcast, on your preferred podcast platform and find more use-cases on topics such as banking, insurance, wealth management, and much more.
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Today in our latest AI Success Factors series episode, we are focusing on the world of heavy industry while highlighting lessons that can be applied any and everywhere. Our guest this week and Chris Joynt, AIoT Co-innovation Leader for the Solutions Group at PTC. PTC is a software firm based in the Boston area. In this episode, Chris discusses what it takes to measure ROI across several different dimensions. He also emphasizes the importance of feature engineering, what it is from a conceptual point of view, and how to use subject-matter experts to handle feature engineering and bring out elements of the data that can support enterprise leaders in their decisions. This episode is sponsored by PTC. If you’d like to learn more about reaching Emerj’s global executive audience through our podcasts, newsletters, and more, visit emerj.com/ad1.
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Today’s guest is Stefan Boronea, Co-Founder and CTO of Proportunity. Based in London, Proportunity is a company that has raised over $170M. In this episode, we dive into the topic of where machine learning can add value in terms of accurately predicting the price of homes both now and in the future. Stefan highlights the kind of data and features that are important to understand the price of a home in the present and the future. Another critical idea he shares is about the future of the market when both buyers and sellers have access to vastly more accurate data on estimating and forecasting prices. He discusses these ideas from the standpoint of buying and selling houses and gives a perspective on how they may impact larger assets. If you’re interested in unlocking our AI best practice guides, frameworks for AI ROI, and specific resources for enterprise leaders, visit emerj.com/p1.
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This week’s guest on our ongoing AI Success Factors series is Gero Gunkel of Zurich Insurance. Until recently, he was the Global Head of Artificial Intelligence for Zurich Insurance, and he is now the COO of Zurich’s Customer Active Management or ZCAM. In today’s episode, Gero discusses one particular use-case in helping to handle the extreme volumes of customer support inquiries that Zurich receives during certain seasons. There are two main takeaways: first, where to find the low-hanging fruit for customer experience applications for AI, and second, how to “think big and start small” from an actionable steps level in a way that achieves a measurable ROI. If you are in the financial services industry or interested in more related use-cases, be sure to subscribe to our other program called “The AI in Financial Services Podcast” on your preferred podcast platform to gain industry insights from enterprise leaders.
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Today’s guest is Pamela Negosanti, the Head of Sector Strategies for Financial Services at Expert.AI. In today’s episode, Pamela speaks to us about the policy review process for cyber insurance. There are two main stand-out points: first, how a new technology shift and further regulation make AI almost a requirement for a particular business workflow, and second, some concrete workflow advice for applying artificial intelligence to contracts and text documents. There’s an evident business value here and a very clear before and after picture of where AI helps to augment the expertise of human experts who are doing policy reviews. This episode is brought to you by Expert.AI. If you’re interested in reaching Emerj’s global executive audience through sponsored podcasts, content, co-branded research, and more, visit emerj.com/ad1 to learn more about Emerj’s Media Services for enterprise AI vendors.
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Welcome back to our AI Success Factors series, where we publish a short episode every Monday highlighting one AI use-case and the most important factor that leads it to a positive ROI. Today’s guest is Emily Bremner, SVP of Product at Signal AI. Based in London, Signal AI is a company that has raised over $100M and is working on leveraging AI to pull in and make sense of various external data streams. In this episode, Emily discusses Signal AI’s long-term work with Deloitte, detailing how they’ve partnered with them and measured success. She also shares how in addition to leveraging the technology for their own decisions, their key use-case is using this streamlined information to support and retain relationships with clients. If you’re interested in unlocking our AI best practice guides, frameworks for AI ROI, and specific resources for AI consultants, visit emerj.com/p1.
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Today’s guest is Roey Mechrez, CEO and Co-Founder of BeyondMinds. BeyondMinds is an AI company based in London. Recorded live in London, this episode highlights the topic of data-centric AI. Roey provides a clear definition of this concept and discusses what it implies for the future of enterprise AI projects. He also speaks about the specific ideas that non-technical business leaders need to understand to identify suitable projects and manage them to achieve a return on investment. Roey is also a valued Emerj Plus member. If you’re interested in unlocking our AI best practice guides, frameworks for AI ROI, and specific resources for AI consultants, visit emerj.com/p1.
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This week’s Success Factors series episode highlights a use-case of construction and AI. In today’s episode, we speak about one of the UK’s most prominent building and construction companies that used artificial intelligence to better estimate their cost with greater confidence and credibility than their competitors and make a case for why they should win the job. Our guest is the Co-Founder and CEO of a London-based company called nPlan, Dev Amratia. Every Monday, we publish a short episode as part of our ongoing AI Success Factors series, highlighting one specific AI use-case and what made it successful. Discover more AI use-cases, best practice guides, white papers, frameworks, and more by joining Emerj Plus at emerj.com/p1.
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Today’s guest is Sunil Tahilramani, Director of Artificial Intelligence at UiPath. Valued at about $40B, UiPath is one of the robotics processing automation world leaders. In today’s episode, Sunil discusses what the journey from RPA to AI looks like. He details some of the use-cases where AI might be able to add value where RPA can’t and how to get from regular automated workflows to more robust workflows that enable more capability with AI. If you’re interested in Emerj’s best practices and frameworks for AI ROI, AI strategy, and our entire library of AI use-cases from financial services to banking, wealth management, and beyond, you can learn more at emerj.com/p1.
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Today’s episode is part of our ongoing AI Success Factors series. Every Monday, we publish 15-minute episodes that focus on an enterprise success story where we discuss one particular factor that made the project successful. Today’s guest is Nikunj Mehta, CEO, and Founder of Falkonry. Falkonry is an AI service firm based in the Bay Area, focusing primarily on heavy industry. In today’s episode, Nikunj highlights the extreme importance of subject-matter expertise when it comes to knowing when to pull in a champion to lead a project to success. Nikunj discusses these core themes in the context of a specific client success story in the steel manufacturing space. To access Emerj’s frameworks for AI readiness, ROI, and strategy, visit Emerj Plus at emerj.com/p1.
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Today’s guest is Amaresh Tripathy, Senior Vice President and Global Business Lead for Analytics at Genpact. Genpact has some 80,000 employees, and Amaresh leads a global team of nearly 8,000 analytics experts covering everything from data engineering, machine learning, data insights, and more. This episode focuses on data fabrics and what separates the idea of a data fabric from a data lake, and how enterprise leaders can make sure that this fabric translates immediately to use-cases that add value with near-term ROI and building long-term capability. Amaresh also clarifies the concept of data fabric and ties it to use-cases applicable in business with real examples from some of Genpact’s clients. Join Emerj Plus at emerj.com/p1 to discover more AI use-cases, best practice guides, whitepapers, frameworks, and more.
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This is our series on AI success factors where we cover one specific enterprise AI project that was a success, highlighting the problem, impact, and what made it a success every Monday. One of our five guests in our recent week-long series on AI ROI was Gopalan Oppiliappan, the Head of the AI Centre of Excellence for Intel. In that episode, he discussed framework thinking for making decisions about AI projects to achieve greater success. In today’s episode, Gopalan shares how he puts those frameworks in action with a specific success story about inventory management at Intel. He gives a real example of crawl, walk, run and how it made a positive financial impact at Intel. He also discusses a key strategy for measuring and determining economic impact. If you enjoyed today’s episode, be sure to go back to listen to Gopalan’s recent episode and the rest of the insight-packed series on AI ROI.
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Today’s guest is Ash Fontana, Special Advisor at Zetta Venture Partners based in the Bay Area. After recently publishing his book, “The AI-First Company,” Ash joins us again on the show to discuss some of the core transferable lessons he’s learned. Our topic for this episode is advantage. Ash discusses a way of thinking about building momentum around data and gaining long-term advantage as a result. This episode is one of two episodes Ash recently recorded with us. If you enjoyed today’s episode, be sure to tune in to his second episode on The AI Consulting Podcast to gain insight on how services companies can turn into AI product companies.
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Today’s guest is Dr. Charles Martin, Founder of Calculation Consulting. Charles has worked on real enterprise deployments with companies like eBay, BlackRock, and exciting startups like Aardvark, which Google acquired. Today’s episode is part of our ongoing Monday series highlighting one key factor for one specific successful enterprise deployment. In today’s episode, Charles discusses a project with Walmart focusing on the use-case of product recommendations in different languages and geo-regions. The main success factor he speaks about is the champion who brings the project through to success. He specifically describes the qualities and behaviors of a good champion. Stay tuned until the end of this episode to learn more about our resources to help AI champions in the enterprise.
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Today is episode five out of five of this week’s special series on Achieving ROI with Early AI Projects. We’ve heard from leaders from Intel, Oracle, and other big names, and today, we’re wrapping this series up with someone from the startup world. Our guest is Nikunj Mehta, Founder and CEO of Falkonry. Falkonry is an AI services business focused on heavy industry and manufacturing based in the Bay Area. In this episode, Nikunj describes a portfolio approach to find several related AI projects and capabilities that are likely to turn into a win. He also discusses why an enterprise’s most important objectives are not always the best fit for early AI projects. Stay tuned until the end of this episode to learn about the AI ROI reports that we’re making available for a limited period.
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