Michelle Lee
Futurist, AI Expert and Strategist, Technology Keynote Speaker, Former Vice President AI at Amazon Web Services and Google Executive, Founder & CEO of Obsidian Strategies (“Architects for AI-Driven Strategies”), Member of the MIT Corporation, Board Director, and Former Under Secretary of Commerce
Michelle Lee is an AI keynote speaker, technology and leadership expert, and the founder and CEO of Obsidian Strategies. As the former VP of Amazon’s Machine Learning Solutions Lab, Michelle advised Amazon’s biggest clients on how to implement AI, GenAI, and machine learning into their business. Now, as founder and CEO of Obsidian Strategies (“Architects for AI-Driven Strategies”), Michelle shows business leaders how AI is being applied to increase productivity, enhance customer experiences, and drive revenue across a wide range of industries. Michelle was also an executive at Google during their formative years and she brings unique perspectives based on her time in Silicon Valley.
Michelle is a frequent speaker on AI, innovation, digital transformation, and board governance and has spoken at The World Knowledge Forum, South by Southwest, Fortune’s Most Powerful Women Conference, the Consumer Electronics Show (CES), and the National Association of Corporate Directors.
Michelle has spent her career building and advising some of our country’s most innovative AI/data-driven companies (Amazon and Google), which gives her unique perspectives on the opportunities and applications of Artificial Intelligence and machine learning.
As the CEO and Founder of Obsidian Strategies (“Architects of AI-Driven Strategies”), she helps Fortune companies identify and implement their highest return-on-investment AI opportunities. Previously, she was a senior executive at Amazon and the Vice President of the Machine Learning Solutions Lab at Amazon Web Services (AWS).
At AWS, she led a global team of business consultants and data scientists who worked with clients from a broad range of industries to spot and implement their most fruitful AI/machine learning applications. She also played a key role in addressing policy, regulatory, and ethical risks associated with AI services and applications and was the founding business executive lead for AWS’s responsible AI efforts. Through both her industry and government experiences, Michelle has a unique understanding and ability to balance the opportunities and risks in AI, an area of active interest to regulatory and legislative bodies as well as society.
Michelle is an MIT AI Lab-trained computer scientist and has worked at the MIT AI and Hewlett-Packard Research Laboratories. She has been featured in The Wall Street Journal, Bloomberg, NPR, and the MIT Sloan Management Review. For her expertise, she has testified before Congress about 10 times and received numerous awards for her leadership and professional accomplishments.
Before Amazon, Michelle served as the presidentially-appointed Under Secretary of Commerce and Director of the U.S. Patent and Trademark Office, one of the largest intellectual property offices in the world, where she brought AI and data analytics to the agency to enhance operations. As the head of the 200-year-old U.S. Patent and Trademark Office, she led over 10,000 people to implement an agency-wide AI strategy, increasing the quality, speed, and consistency at which patents were issued.
Prior to public service, she spent her entire career in Silicon Valley, including eight years as an executive at Google during its formative years.
AI: THE ART OF THE POSSIBLE AND PRACTICAL AND 7 LESSONS FOR IMPLEMENTING AI IN YOUR COMPANY
AI is one of the most transformative technologies of our generation. Computers can now create, “see,” “hear,” predict, and perform a wide variety of human tasks. Recent developments in AI (including generative AI, computer vision, machine learning, and robotics) will impact every business and aspect of our lives with both positive and negative effects. As a result, every organization needs to ask itself, what is its AI strategy? Michelle Lee is an MIT AI Lab-trained computer scientist who has spent her career advising some of our country’s most innovative AI/data-driven companies (Amazon and Google), which gives her unique perspectives on the applications of Artificial Intelligence and machine learning.
In this engaging talk, Michelle cuts through the hype and brings the high-level talk down to reality with concrete examples and recommended actions. Audiences will come away with the 7 lessons for AI implementation that can help their companies increase operational efficiencies, enhance customer experiences, and generate new revenue.
REAL IMPLICATIONS OF GENERATIVE AI: THE PROMISE AND PERILS OF AI AND HOW TO PREPARE FOR AN AI-CENTRIC WORLD
AI is powerfully transforming virtually every aspect of our business and personal lives including the way we analyze data, make predictions, generate content, delight our customers, grow revenue and increase operational efficiencies. However, there are challenges to using generative AI for organizations in terms of accuracy, copyright, bias, regulations, and more. Just because something can be achieved by AI doesn’t mean it should. Based upon her unique multi-disciplinary experiences from the top levels of technology, business, law and government, Michelle Lee shares with her audience concrete examples of incredibly powerful business applications of AI, some associated risks, and how to balance the two to lead organizations to leverage responsible, reliable and trustworthy AI applications. For this thought-provoking yet practical talk, Michelle Lee draws upon her experiences as a technologist and AI expert who has spent her career building and advising the most innovative AI/data-driven companies like Amazon and Google, her time as a top-ranked governmental official (Under Secretary of Commerce and Director of the U.S. Patent & Trademark Office) and her experiences as a lawyer and policy maker to examine the practical implications of Generative AI for organizations. Audiences will come away understanding where to lean-in on AI and Generative AI, where not to, and how to leverage AI for competitive advantage.