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.

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.

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. 

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.

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.

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.

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.

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.

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.

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.