Tuesday, March 23

Day 1: The Business (12:00 p.m. - 5:00 p.m.)

What are the challenges that must be met to successfully implement AI in an organization? While AI is - on the surface - a computing technology, its successful implementation depends on people, strategies, and a clear definition of the problem space.

The Age of Implementation
AI is hard. While there are some great success stories, most are struggling. Is the promise of AI paying off or do we need to start rethinking our approach to the problem?


Essential Elements
Why do some organizations succeed while others struggle? We’ll break down examples of successful AI implementations in healthcare, finance, and retail and extract the essential elements that lead to success.


How do we make AI happen? For those with strong in-house capabilities, it’s about the process. For those without the expertise, it’s about finding the help and getting AI as a service.

Wednesday, March 24

Day 2: The Lab (12:00 p.m. - 5:00 p.m.)

At its core, AI is an engineering problem. With smarter algorithms and more powerful chips, AI can deliver incredible insights at greater speeds and lower energy costs. Successful implementation requires an understanding of the fundamental engineering challenges of AI hardware and software.

Inside the Leading Labs
What’s going on in the labs of AI giants like Microsoft, IBM, and others? What are their latest projects? Where are they headed? We’ve invited their leaders to answer your questions.


The Algorithms
Algorithms are the brains of AI. The smarter the algorithm, the more accurate the model, the better the insights. We explore the software side of AI.


The Chips
AI is a hungry beast, demanding massive amounts of compute and energy. What innovations in AI hardware are on the horizon that might turbo-charge our algorithms and tame our energy consumption?

Thursday, March 25

Day 3: Life (12:00 p.m. - 5:00 p.m.)

AI is infusing its way into our lives in ever more meaningful ways. What does that mean for the way we eat, commute and work? And while progress has been substantial, it hasn’t always been equal. We discuss what safeguards need to be put in place to ensure AI treats all equally.

If we are going to build AI for the future, how do we make sure it works equally for all? What policies are needed? What practices need to become standard? And what just simply needs to stop?


On a daily basis, AI gets us from point A to B, selecting the music we play along the way and - for some - even parking the car when we get there. What are the next areas in which AI is going to fundamentally change the way we live?


Whether you live to work or work to live, the fact is: you work. What possibilities lie ahead, as AI begins to re-engineer the workplace? What does an AI-augmented workforce look like, and just how much more can it achieve?