Based on the guest lecture I will be doing this fall with MIT, I would like to present real world cases and frameworks for AI strategies with implementation roadmaps.
AI is revolutionizing many industries, including energy, consumer products and services, automotive, financial services, national security, healthcare, and advertising. But too often, business and IT leaders take a limited view of AI, focusing almost exclusively on machine learning (ML) methods. But AI technologies are, in fact, key enablers to complex systems. They require not only ML technologies, but also trustworthy data sensors and sources, appropriate data conditioning processes, responsible governance frameworks, and a balance between human and machine interactions. In short, organizations must evolve into a systems engineering mindset to optimize their AI investments.
In this talk I will give an overview of how to get started, from strategy, to framework and practical tools needed for successful implementation.