Artificial Intelligence Master Class

Exponential Opportunities. Existential Risks. Master the AI-Driven Future.

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2-Week Online Learning

Online / Remote

Week 1

March 06-13

Wednesday - Wednesday

Week 2

March 14-20

Thursday - Wednesday

3-Day Live Workshop

Live / New York

Week 3

March 22-24

Friday - Sunday

Master the AI-Driven Future

Become a more effective leader at navigating your organization through the coming wave of AI-driven change.

Gain the tools and knowledge to leverage AI’s exponential opportunities and avoid its existential risks.

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The Class

Format

Hybrid (online + classroom)

3 weeks of Online Learning & 3 days of live workshop at NYU’s New York campus.

Participants

Board members and C-level executives.

Teaching style

Highly interactive combining action learning, live cases, lectures, and classroom discussion, with bite-sized self-learning elements.

Content

Acquire the tools and knowledge to master the AI-driven future. The class leads you systematically - and jargon-free - through AI in business, always with an eye on ‘How to use it on Monday’.

Dates

Online: Mar 06– Mar 21 2024
In Person (NYC): Mar 22 to Mar 24, 2024

Faculty

World-class faculty who combine rich experience in teaching and coaching executives, with in-depth knowledge of AI and business.

Panels

Day 1 and Day 2 of the in-person workshop culminate in panel discussions. The panelists are leading industry practitioners and include some of the world’s most experienced and knowledgeable AI experts.

Outcome

Be prepared for what’s just starting to unfold: the Age of AI.

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In the AI Masterclass you will learn...

Strategy

Align your Al strategy and portfolio to your company and data strategy

Industry Dynamics

Understand how Al will disrupt your organization and industry

Regulation

Anticipate regulatory trends and develop scenarios how to adapt

Costs & Revenue

Use Al to drive down costs and increase revenue

Innovation

Innovate faster and more efficiently

Digital Transformation

Connect Al strategy to your company-wide digital transformation

Risks

Anticipate and manage risks

Success factors

Determine critical success factors and pitfalls for Al projects

Ethics and Governance

Define your personal position on Al governance and ethics

Roadmap

Develop an AI- roadmap for your company

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Panel Members

Ram Nagappan

Chief Information Officer, BNYMellon Pershing

More than 30 years of information technology experience, driven by Purpose, known for Creativity, an Empathetic leader, and a Strategic Influencer across the Corporate world and our Communities.

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JoAnn C. Stonier

Chief Data Officer, Mastercard

JoAnn C. Stonier serves as Chief Data Officer for Mastercard, leading the organization’s data innovation efforts while navigating current and future data risks. She oversees the curation, quality, governance and management of the company’s extensive data assets.

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Amy D. Grubb, Ph.D

Digital Transformation Advisor, FBI

Amy D. Grubb, Ph.D., is an internationally acclaimed speaker who has presented numerous keynote addresses and workshops on leadership, organizational culture, change, performance, working with others, and storytelling. She has worked directly for three C-level functions (CHRO, CFO, CIO) for the past 15 years and has been with the FBI for over two decades.

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Dr. Seth Dobrin

Founder and CEO, Qantm AI

Dr. Seth Dobrin is a globally recognized expert in AI. He is the Founder and CEO of the Qantm AI. Previously, he was President of the Responsible AI Institute and Global Chief AI Officer of IBM, where he led the company's AI strategy.

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John Nicastro

Chief Data Officer, Major League Soccer

John Nicastro is a technology & corporate executive currently serving as Chief Data Officer at Major League Soccer. In his role, John oversees the League’s data and AI strategy, as well as all Fan technology, including digital products, marketing, and advertising platforms.

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Cindi Howson

Chief Data Strategy Officer, ThoughtSpot

Cindi Howson is the Chief Data Strategy Officer at ThoughtSpot and host of the award-winning The Data Chief podcast. Cindi is an analytics and BI thought leader and expert with a flair for bridging business needs with technology.

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Nick Elprin

CEO & Co-founder, Domino Data Lab

Nick Elprin is the CEO and co-founder of Domino Data Lab, provider of the enterprise AI platform that powers model-driven companies such as Allstate, Bristol Myers Squibb, Dell and Lockheed Martin.

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Matt Turck

Partner, FirstMark

Matt Turck is a Partner at FirstMark, where he focuses on early-stage investments in enterprise software and cloud, with a particular predilection for data infrastructure, ML, and AI.

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Florian Douetteau

Co-founder & CEO, Dataiku

Florian Douetteau is the co-founder and CEO of Dataiku, an AI software company that aims to make data analysis and machine learning more accessible. Florian was born in France, where he also pursued his education in Computer Science at ENS Paris.

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Ricky Ray Butler

CEO, BENlabs/TubeBuddy

Ricky Ray Butler is an 18-year digital entertainment veteran and a pioneer in using AI technology to reshape the entertainment and media landscape. In 2008, he founded Plaid Social Labs, which was later acquired by BENlabs.

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Participant profile

Board members and C-level executives of listed and large private organizations as well as government agencies and NGOs.

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Program Structure and Schedule

2 Week Online Learning

Online / Remote

Week 1

March 06-13

Wednesday - Wednesday

Week 2

March 14-20

Thursday - Wednesday

3 Day Live Workshop

Live / New York

Week 3

Mar 22-24

Friday - Sunday

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Faculty

Ed Watal

Founder and Principal, INTELLIBUS

Ed Watal is the founder and principal of Intellibus, an IT strategy consultancy with 65 transformation consultants based in Reston, Virginia. He regularly serves as a board advisor to the world's largest financial institutions. C-level executives rely on him for IT strategy.

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Jepson Taylor

Chief AI Strategist, Dataiku

Jepson Taylor has over 18 years of machine-learning experience. After studying chemical engineering, Taylor worked for Intel/Micron in applied semiconductor building process control and fault models. After that, he worked as a quant at a hedge fund on a 600 GPU cluster.

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