Me, Myself, and AI MIT Sloan Management Review and Boston Consulting Group (BCG)

Ellen Nielsen, Chevron’s first chief data officer, sees data as the common thread throughout a career that has spanned systems, digital data, procurement, and supply chain. In her current role, she applies what she’s learned to Chevron’s wide-ranging AI and machine learning initiatives, including the use of robots and computer vision to inspect tanks, digital twins to simulate operations, and sensors to monitor equipment in refineries.
On this episode, Ellen shares examples of the integrated energy company's use cases for machine learning and generative AI, and she describes the company’s citizen development program, which puts safe, secured AI and machine learning tools in the hands of employees throughout Chevron. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Ellen Nielsen is the chief data officer at Chevron, where she focuses on creating a data-oriented culture partnered with value-chain thinking. A multidisciplinary leader, Nielsen has over 30 years of global experience as an executive in IT, digital, data, procurement, and supply chain. She has worked with industry leaders in oil and gas, fast-moving consumer goods, automotive, manufacturing, retail, and banking and insurance.
Nielsen is a regular speaker at industry events and has received numerous awards and recognitions, including being named to CDO Magazine’s 2023 Global Data Power Women list. She was also ranked fifth on the 2023 DataIQ 100 list of the most influential people in data in the United States.
She also serves on a variety of boards, including PIDX (Petroleum Industry Data Exchange) International and Women Leaders in Data & AI.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

Miqdad Jaffer brings a background in engineering to his role as director of product for digital marketplace platform Shopify. Users might recognize the commerce platform as one that enables a fast and secure online checkout experience. On the merchant side, Shopify enables business owners to set up e-commerce sites where they can list and sell their products.
 Using generative AI, the platform also now offers merchants the ability to complete administrative tasks much more quickly, including writing product descriptions and customizing their sites. As Miqdad explains, a key to enhancing Shopify’s offerings with generative AI technology is ensuring that users always remain in control. He shares Shopify’s approach to doing this while incorporating cutting-edge tools to help entrepreneurs start, operate, and grow their businesses more efficiently. Read the episode transcript here.
Guest bio:
Miqdad Jaffer is the director of product for Shopify, where he is responsible for the oversight and development of the company’s AI-powered offerings. He joined the company in 2018 and has overseen the launch of Shopify Magic, its suite of AI-powered tools, and Shop.AI, an AI-powered shopping assistant. Before joining Shopify, Jaffer was the director of product management for the mobile consumer marketplace app Flipp. He has more than 15 years of product development and oversight experience.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

As an associate professor at Harvard Business School and cofounder of the Customer Intelligence Lab at the school’s Digital Data Design Institute, Ayelet Israeli’s work is focused on how data and technology can inform marketing strategy, as well as how generative AI can be a useful tool in eliminating algorithmic bias. One of the products of her recent work is a paper she coauthored with two Microsoft economists and researchers on how generative AI could be used to simulate focus groups and surveys to determine customer preferences.
Ayelet joins Sam and Shervin to discuss the opportunities and limitations of generative AI in market research. She details how the research was conducted and how artificial intelligence technology could help marketers reduce the time, cost, and complexity associated with traditional customer research methods. Read the episode transcript here.
Guest bio:
Ayelet Israeli is the Marvin Bower Associate Professor of Business Administration in Harvard Business School’s Marketing Unit. She is also the cofounder of the school’s Customer Intelligence Lab at the Digital Data Design Institute. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their internal data, customer data, and market data to improve outcomes. Her research interests include retail, pricing strategy, channel management, marketing analytics, and algorithmic bias. Israeli has a Ph.D. in marketing from the Kellogg School of Management at Northwestern University.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

A former startup employee herself, Shilpa Prasad knows the level of commitment and effort required to begin a new venture. That’s what led her to join LG Nova, electronics manufacturer LG’s innovation incubator, as an entrepreneur in residence. In her role, Shilpa identifies promising startups — particularly those working with AI — and coaches and nurtures entrepreneurs while keeping a close eye on the products that might one day find their way into LG’s ecosystem.
On this episode, Shilpa explains how keeping a finger on the pulse of startups helps LG Electronics stay open to innovation and new business opportunities. She also discusses why artificial intelligence is at the forefront of her work with startups, and the promising future she sees for using augmented reality and AI technologies to change how skills training is delivered. Read the episode transcript here.
Guest bio:
Shilpa Prasad is an experienced leader in the startup ecosystem with a strong passion for entrepreneurship and corporate startup engagement/innovation. She brings over 15 years of global experience in corporate startup strategy and venture-building to her role as entrepreneur in residence at LG Nova, where she is helping the company identify market trends and build partnerships. 
Prasad has been instrumental in driving innovation for various open innovation projects across corporations, governments, and accelerators and in establishing new partnerships across the global startup ecosystem. An experienced founder, she has also contributed her time to mentoring and advising startups.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

Starting a career with the ambition of becoming a medical doctor and ending up a technical leader for a major automaker might seem an unlikely path, but for Anders Sjögren, who leads data and AI innovation projects for Volvo Cars, it was a perfect trajectory.
On this episode, Anders joins Sam and Shervin to explain the ways the carmaker uses data and artificial intelligence to inform manufacturing — ensuring that parts are made consistently and as efficiently as possible — as well as driver experience and safety. He also outlines some specific ways smart technology keeps drivers alert and aware of conditions around them and describes Volvo’s approach to technology-driven innovation. Read the episode transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bio:
Anders Sjögren is senior technical leader for Volvo Cars. He focuses on strategy, research, innovation, and transformation, with the key objective of ensuring that the automaker understands and executes within the continuously emerging areas of data, analytics, and artificial intelligence. Application areas include creating AI-enabled intelligent customer functionality and using AI to reform Volvo’s operations and development activities. Sjögren has an academic background in mathematical statistics (large-scale and computational aspects) and an industrial background in data-centric methods development and software product development.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.

At Amnesty Tech, a division of human rights organization Amnesty International, Damini Satija and Matt Mahmoudi leverage their expertise in technology and public policy to examine the use of AI in the public sector and its impact on citizens worldwide.
In Part 1 of Matt and Damini’s conversation with Sam and Shervin, they described scenarios in which AI tools can put human rights at risk and how their work is helping to expose those risks and protect people from the technology’s misuse. In this episode, they resume their conversation and dig deeper into the ways AI regulations can limit the negative use of AI at scale. Matt and Damini also caution us about what a dystopian future might hold and point to specific ways leaders in the corporate world can help limit the harms of AI. Read this episode's transcript here.
Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.
Stay in touch with us by joining our LinkedIn group, AI for Leaders at mitsmr.com/AIforLeaders or by following Me, Myself, and AI on LinkedIn.
Guest bios:
Matt Mahmoudi is a lecturer, researcher, and organizer. He’s been leading Amnesty International’s research and advocacy efforts on banning facial recognition technologies and exposing their uses against racialized communities, from New York City to the occupied Palestinian territories. He was the inaugural recipient of the Jo Cox Ph.D. scholarship at the University of Cambridge, where he studied digital urban infrastructures as new frontiers for racial capitalism and remains an affiliated lecturer in sociology. His work has appeared in the journals The Sociological Review and International Political Sociology and the book Digital Witness (Oxford University Press, 2020). His forthcoming book is Migrants in the Digital Periphery: New Urban Frontiers of Control (University of California Press, 2023).
Damini Satija is a human rights and public policy expert working on data and artificial intelligence, with a focus on algorithmic discrimination, welfare automation, government surveillance, and tech equity. She is head of the Algorithmic Accountability Lab and a deputy director at Amnesty Tech. She previously worked as an adviser to the U.K. government on data and AI ethics and represented the U.K. as a policy expert on AI and human rights at the Council of Europe. She has a master’s degree in public administration from Columbia University’s School of International and Public Affairs.
We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials.