Which organizational strategies are required to innovate in production? | Sébastien Berard, Euronext Which organizational strategies are required to innovate in production? | Sébastien Berard, Euronext
Developing ML-Driven Customer Facing Products at Square | Marsal Gavalda, Square Developing ML-Driven Customer Facing Products at Square | Marsal Gavalda, Square
Becoming an Intelligent Organization in the Age of AI | Jeff McMillan, Morgan Stanley Becoming an Intelligent Organization in the Age of AI | Jeff McMillan, Morgan Stanley
AI + Human Intuition = Differentiated Insights | Jeff McMillan, Morgan Stanley AI + Human Intuition = Differentiated Insights | Jeff McMillan, Morgan Stanley
Transformation data chez Engie GEM | Haga Rabekoto, ENGIE Transformation data chez Engie GEM | Haga Rabekoto, ENGIE
How to Improve and Innovate Tax Collection by Municipalities | Jan Geert Bakker, Gemeente Amsterdam How to Improve and Innovate Tax Collection by Municipalities | Jan Geert Bakker, Gemeente Amsterdam
Ethical Enterprise AI – A Guideline or Compass? | Martin Leijen, Rabobank Ethical Enterprise AI – A Guideline or Compass? | Martin Leijen, Rabobank
The Spirit of the City: Capturing Network-Generated Data for Better Cities | Luca Maria Aiello, Nokia Bell Labs The Spirit of the City: Capturing Network-Generated Data for Better Cities | Luca Maria Aiello, Nokia Bell Labs
The 7 Powers of Machine Learning | Lucas Bernardi, Booking The 7 Powers of Machine Learning | Lucas Bernardi, Booking
A Glance at ADA: Aviva’s Algorithmic Decision Agent | Damian Rumble, Aviva A Glance at ADA: Aviva’s Algorithmic Decision Agent | Damian Rumble, Aviva
From Silos to Self-Service: Data Transformation at GE Aviation | Jon Tudor, GE Aviation From Silos to Self-Service: Data Transformation at GE Aviation | Jon Tudor, GE Aviation
Ethical AI: Inclusivity as a Messy, but Promising Answer | Larry Orimoloye, Dataiku Ethical AI: Inclusivity as a Messy, but Promising Answer | Larry Orimoloye, Dataiku
What’s At Stake With Your Data Projects Operationalization? | Romain Fouache, Dataiku What’s At Stake With Your Data Projects Operationalization? | Romain Fouache, Dataiku
How Mercedes-Benz, Vodafone, and Credit Suisse Super-Sized their Data Initiatives | A Panel How Mercedes-Benz, Vodafone, and Credit Suisse Super-Sized their Data Initiatives | A Panel
Cyber Risk Analytics: The Next Frontier | Paul Guthrie, Envelop Cyber Risk Analytics: The Next Frontier | Paul Guthrie, Envelop
Can We Make AI Likeable? | Florian Douetteau, Dataiku Can We Make AI Likeable? | Florian Douetteau, Dataiku
Panel: Magical Experiences and Greater Well-Being | Panel with Disney, Warner Media, Blue Cross Blue Shield Panel: Magical Experiences and Greater Well-Being | Panel with Disney, Warner Media, Blue Cross Blue Shield
The data science challenges in the European SESAME project | Igor Girard-Carrabin & William Lacheny, ArianeGroup The data science challenges in the European SESAME project | Igor Girard-Carrabin & William Lacheny, ArianeGroup
Le revenue management augmenté par l’IA | Benjamin Lalanne, Groupe Air France Le revenue management augmenté par l’IA | Benjamin Lalanne, Groupe Air France
Augmented Human Intelligence | Walid Mehanna, Daimler Augmented Human Intelligence | Walid Mehanna, Daimler
The AI Experts You Need Are Right Beneath Your Nose | Rachel Thomas, Fast.AI The AI Experts You Need Are Right Beneath Your Nose | Rachel Thomas, Fast.AI
The Data Science Food Chain | Shaun McGirr, Dataiku The Data Science Food Chain | Shaun McGirr, Dataiku
From Us, To Us: An Inclusivity Architecture | Brandeis Marshall, Spelman College From Us, To Us: An Inclusivity Architecture | Brandeis Marshall, Spelman College
AI in the B2B customer journey | José Ramón Sánchez Martos, Telefónica AI in the B2B customer journey | José Ramón Sánchez Martos, Telefónica
