Artificial Intelligence in Enterprise

 

JANUARY: AI in Enterprise - FinTech Edition

 

Wednesday, January 20, 2021

11:00am - 12:00pm EST

 

Apply to attend here: http://bit.ly/ai-enterprise-fintech

 

Financial Services (FinServ) companies have been in the forefront of designing and implementing AI projects in asset management, banking, and insurance.  Companies are aggressively evaluating a broad array of digital transformation technologies in core business processes like online account opening, risk management, underwriting, algorithmic trading and portfolio management, core support practices, customer-facing and relationship management, hiring and other activities.

In this session, Greg Woolf (FiVerity) and Saroop Bharwani (Senso.ai) will discuss how machine learning is transforming two different fragmentation situations in FinServ.  These two entrepreneurs will (1) describe their personal, business, and technical journeys that preceded both of their emerging companies; (2) set forth the reasons their enterprise customers are adopting their AI/ML, expectations and results; and (3) share their thoughts on the technology and business road that lies ahead in the coming years.
 
Greg Woolf ImageGreg Woolf brings more than 20 years of experience as an entrepreneur and business leader in FinTech companies with state-of-the-art technology solutions. Greg has multiple degrees in Computer Science, Math and Finance, and an Advanced Machine Learning certification from Stanford University. In 2017, Greg founded the Boston AI Think Tank – a group of senior executives from prominent global financial institutions and government agencies to explore how AI can improve financial crime detection. He also advised the U.S. Congress on how AI can improve financial crime detection, a strategy that was included in a 2019 Bill to modernize Anti-Money Laundering. At FiVerity, Greg created a software platform that uses AI, machine learning and digital identity management to detect emerging forms of cyber fraud and deliver actionable threat intelligence. Initially the company is focused on Synthetic Identity Fraud (SIF) – the fastest-growing financial crime in the U.S. payments system, where fraudsters create fake identities from compromised consumer data on the dark web to infiltrate FinServ companies and commit loan fraud and other financial crimes. He was awarded IT-CEO of the Year by AI Global Magazine and FinTech Innovation Winner by the Financial Information Management Association.
 
Saroop Bharwani ImageSaroop Bharwani, a serial tech entrepreneur, spent over a decade building product and growth teams across global 100 enterprises and high-growth startups before founding Senso, a fintech AI company which enhances revenue operations for banks and lenders by proactively engaging clients via digital channels to optimize conversion, channel usage, and profitability.  Senso develops and markets an end-to-end AI platform that makes it easy for financial institutions to seamlessly embed predictive intelligence based on fragmented and unstructured data. This transformation results in personalized, connected and meaningful interactions between banks and banking customers.
 

Wednesday, January 20, 2021

11:00am - 12:00pm EST

Apply to attend here: http://bit.ly/ai-enterprise-fintech

 

 

FEBRUARY: AI in Enterprise with Mohamed El-Geish (Cisco)

 

Wednesday, February 17, 2021

11:00am - 12:00pm EST

 

Apply to attend here: http://bit.ly/ai-enterprise-elgeish 

 
Mohamed El-Geish Image

Mohamed El-Geish is the Director of AI for Cisco's Contact Center solutions that sits in the Collaboration group. In 2019, Cisco acquired Voicea, where El-Geish was a co-founder and Chief Architect and worked on Automatic Speech Recognition (ASR) and Natural Language Processing (NLP) developing the company's AI assistant. Earlier in his career, El-Geish worked at LinkedIn and Microsoft. El-Geish co-authored Computing with Data and served as a teaching assistant at Stanford University for machine learning and deep learning courses.

For Cisco, AI has become an appealing technology in customer service, specifically, in the customer contact center. Contact centers handle large volumes of inbound and outbound interactions, and make interaction channels (voice, email, text messaging, social media, etc.) as efficient and optimized as possible. Mohamed will address AI's subfields including speech recognition, natural language processing, virtual assistants, forecasting, computer vision, etc. and their applications in the enterprise.

For El-Geish, AI holds the prospects of augmented intelligence and has far-reaching potential for economic prosperity and welfare in a plethora of business domains. Join the AI in Enterprise session this February to learn more about his and Cisco’s use cases and projects.

 

Applying AI & MI in Business 
 

Caroline Sherman

As a strategy and product leader for data-driven businesses, Caroline Sherman consults and advises on how to identify and launch new products and revenue lines, as well as build the teams to deliver them in rapidly changing environments. Drawing on her experience in fintech companies (including Quantopian and InsightSquared), the U.S. Department of Treasury, and Goldman Sachs, she has identified what businesses need in order to implement successful data and AI initiatives. In the final AI in Enterprise event of the year, Prof. Karim Lakhani sat down with Caroline Sherman to explore how examining and defining the intent of using AI in your enterprise is critical for both strategic and tactical AI/ML initiatives.
 
Access the podcast or video recording through our Innovation Science Guide. 
 
 

Upcoming Sessions for 2021

More details to come!

 

   


The AI in Enterprise Series

 
Enterprise firms across the globe are increasingly turning to AI-driven technologies to achieve key business goals. While potential benefits are significant, many firms underestimate the fundamental change necessary to successfully integrate AI into the enterprise. Successful adoption programs need to be developed to fit the particular needs of each organization—from its data strategy, project management, and product development to its engagement with the cloud, customers, and partners.
In November 2019, the Laboratory for Innovation Science (LISH), HBS Digital Initiative, and the Harvard School of Engineering and Applied Sciences (SEAS) launched AI in Enterprise,  an invitation-only series for selected executives to learn how to manage expectations and assimilate the knowledge and tools they need to implement a successful transition to AI in larger, more established organizations.

In contrast to other discussions on AI, this series aims to provide key insights on how enterprise firms are thinking critically and strategically about AI integration. Drawing on the LISH’s extensive experience over the past decade running programs that develop algorithm and AI-based solutions with partners across industries—as well as subject matter expertise from Harvard Business School faculty and partners—this series will provide a uniquely enterprise-focused forum for understanding artificial intelligence.

Watch highlights from the November 2019 event:

 

 

Moderators

 

Karim LakhaniKarim R. Lakhani is the founder and co-director of the Laboratory for Innovation Science at Harvard, the principal investigator of the NASA Tournament Laboratory at the Harvard Institute for Quantitative Social Science, and the faculty co-founder of the Harvard Business School Digital Initiative. He specializes in technology management and innovation. His research examines crowd-based innovation models and the digital transformation of companies and industries. 

Marco Iansiti ImageMarco Iansiti is an expert on digital innovation and transformation, with a special focus on strategy, business models, and new product development in high technology industries. His research studied innovation and operations in both firms and firm networks. He examined the strategy, business models, and innovation processes of a variety of organizations including Microsoft, Facebook, IBM, Hewlett Packard, Wal*Mart, AT&T, Dell, Amazon, and Google, among many others.

In their book, Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World, Lakhani and Iansiti show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have constrained business growth for hundreds of years. 

Doug LevinDoug Levin is XIR at the Laboratory for Innovation Sciences at Harvard and best known as the sole founder and first CEO of Black Duck Software. He is an advisor to an array of young companies in the cybersecurity and AI/machine learning segments, including Accuknox, Nirmata, StormForge, Prescient Devices, Stynt, Tolemi and Wabbi. He serves as a board director for DJ MicroLaminates, FiVerity and ReversingLabs. Levin is a frequent guest lecturer at the MIT Sloan School of Management and Harvard Business School where he speaks on a range of topics, including finance, technology and markets, and entrepreneurship. Levin received his bachelor’s degree from the University of North Carolina at Chapel Hill, earned an advanced degree in International Economics from the College d’Europe in Bruges, Belgium and a Clean Technology fellowship.

 

Publications

Hannah Mayer. Working Paper. “AI in Enterprise: AI Product Management.” Edited by Jin H. Paik, Jenny Hoffman, and Steven Randazzo.Abstract

While there are dispersed resources to learn more about artificial intelligence, there remains a need to cultivate a community of practitioners for cyclical exposure and knowledge sharing of best practices in the enterprise. That is why Laboratory for Innovation Science at Harvard launched the AI in the Enterprise series, which exposes managers and executives to interesting applications of AI and the decisions behind developing such tools. 

Moderated by HBS Professor and co-author of Competing in the Age of AI, Karim R. Lakhani, the July virtual session featured Peter Skomoroch from DataWrangling and formerly at LinkedIn. Together, they discussed what differentiates AI product management from managing other tech products and how to adapt to the uncertainty in the AI product lifecycle.

Hannah Mayer. Working Paper. “Data Science is the New Accounting.” Edited by Jin H. Paik and Jenny Hoffman.Abstract

In the October session of the AI in Enterprise series, HBS Professor and co-author of Competing in the Age of AI, Karim R. Lakhani and Roger Magoulas (Data Science Advisor) delved into O'Reilly's most recent survey of AI adoption in larger companies. The discussion explored common risk factors, techniques, tools, as well as the data governance and data conditioning that large companies are using to build and scale their AI practices. 

 

Read Hannah Mayer's recap of the event to learn more about what senior managers in enterprises need to know about AI - particularly, if they want to adopt at scale. 

 

Hannah Mayer. Working Paper. “AI in Enterprise: In Tech We Trust.. Maybe Too Much?Edited by Jin H. Paik and Jenny Hoffman.Abstract

While there are dispersed resources to learn more about artificial intelligence, there remains a need to cultivate a community of practitioners for cyclical exposure and knowledge sharing of best practices in the enterprise. That is why Laboratory for Innovation Science at Harvard launched the AI in the Enterprise series, which exposes managers and executives to interesting applications of AI and the decisions behind developing such tools. 

In the September session of the AI in Enterprise series, HBS Professor and co-author of Competing in the Age of AI, Karim R. Lakhani spoke with Latanya Sweeney about algorithmic bias, data privacy, and the way forward for enterprises adopting AI. They explored how AI and ML can impact society in unexpected ways and what senior enterprise leaders can do to avoid negative externalities. Professor of the Practice of Government and Technology at the Harvard Kennedy School and in the Harvard Faculty of Arts and Sciences, director and founder of the Data Privacy Lab, and former Chief Technology Officer at the U.S. Federal Trade Commission, Latanya Sweeney pioneered the field known as data privacy and launched the emerging area known as algorithmic fairness.

Hannah Mayer, Jin H. Paik, Timothy DeStefano, and Jenny Hoffman. Working Paper. “From Craft to Commodity: The Evolution of AI in Pharma and Beyond”.Abstract

While there are dispersed resources to learn more about artificial intelligence, there remains a need to cultivate a community of practitioners for cyclical exposure and knowledge sharing of best practices in the enterprise. That is why Laboratory for Innovation Science at Harvard launched the AI in the Enterprise series, which exposes managers and executives to interesting applications of AI and the decisions behind developing such tools. 

Moderated by HBS Professor and co-author of Competing in the Age of AI, Karim R. Lakhani, the August virtual session featured Reza Olfati-Saber, an experienced academic researcher currently managing teams of data scientists and life scientists across the globe for Sanofi. Together, they discussed the evolution of AI in life science experimentation and how it may become the determining factor for R&D success in pharma and other industries.

Jin H. Paik, Steven Randazzo, and Jenny Hoffman. Working Paper. “AI in the Enterprise: How Do I Get Started?”.Abstract

While there are dispersed resources to learn more about artificial intelligence, there remains a need to cultivate a community of practitioners for cyclical exposure and knowledge sharing of best practices in the enterprise. That is why Laboratory for Innovation Science at Harvard launched the AI in the Enterprise series, which exposes managers and executives to interesting applications of AI and the decisions behind developing such tools. 

Moderated by HBS Professor and co-author of Competing in the Age of AI, Karim R. Lakhani, the most recent virtual session with over 240 attendees featured Rob May, General Partner at PJC, an early-stage venture capital firm, and founder of Inside AI, a premier source for information on AI, robotics and neurotechnology. Together, they discussed why we have seen a rise in interest in AI, what managers should consider when wading into the AI waters, and what steps they can take when it is time to do so.