The Enterprise AI event for data science and IT leaders

RevX London was Thursday, June 13, 2024

Watch the sessions


  • 8:00 – 9:00a

    Check-in and breakfast

  • 9:00 – 9:05a

    Welcome by Domino

    Hemal Kanani Chief Customer Officer, Domino Data Lab

  • 9:05 – 9:35a

    Driving AI value at enterprise scale in 2024

    Thomas Robinson COO, Domino Data Lab

    Enterprises are ramping up AI across all areas. How do you meet high expectations without sacrificing budgets or responsible practices? Hear from Domino executives, industry experts, and thought leaders as they discuss the enterprise's path to AI success.

  • 9:35 – 10:05a

    Cloud for a rainy day: How private cloud AI shines bright for the leading financial institutions

    Paul Nothard Principal Architect, Financial Services Global Industries Group, VMware

    Integrating AI presents significant opportunities and formidable headaches in the ever-evolving regulatory landscape of financial services. VMware by Broadcom’s Paul Nothard will join us to explain how private AI will help you confront the Digital Operational Resilience Act (DORA), drive AI efficiency, broaden your choices, enhance security, and best of all — reduce your steady-state costs. Gain insights into practical strategies ensuring compliance and defending your competitive edge.

  • 10:05 – 10:25a

    The great GenAI compression

    Fernando Lucini Global Data Science & Machine Learning Engineering Lead, Accenture

    Generative AI has changed both the possibilities and the expectations for innovation at every major company today. With GenAI we can radically change how we develop software, engage with customers, deliver new experiences, and leverage human talent. Simultaneously, investors, boards and C-level executives are demanding AI strategies to implement and deliver value faster than any technology that has gone before. Welcome to the Great GenAI Compression.

    In this session Fernando Lucini, Global Lead for Data Science Accenture, will talk about how GenAI has upended the traditional playbook for innovation and technology adoption, how to manage the misperceptions, navigate the pitfalls, and accelerate the journey to long-term AI-driven value for customers and employees.

  • 10:45 – 11:30a

    Building future-proof in-house AI systems: an illustration with intelligent document processing

    Sébastien Conort Chief Data Scientist, BNP Paribas CARDIF

    With the rapid advancement of GenAI, AI leaders are facing an unprecedented pace of innovation in AI technologies. New, open-source AI and GenAI models are emerging at an astonishing rate, with some released every few weeks.

    (click '+' at right for more)

    Driving data-centric organizational transformation

    Liesbeth Ceelen CEO, Biolizard

    In this session, we explore the ways in which organizations can transform their most core, value-creating processes to take advantage of data and AI, even in highly technical, regulated industries. Join this fireside chat with CEO BioLizard, Liesbeth Ceelen, where we will discuss how to take a data-centric approach to AI projects, drive alignment between IT, scientists and the business, as well as how to accommodate regulation, and even take advantage of the capabilities developed to comply with prior regulations.

  • 11:45 – 12:30p

    Navigating EU AI Act compliance: strategies to accelerate business value & mitigate risks

    Adam Gale Business Cloud Architect for AI & Financial Industry, NetApp

    The EU AI Act is regulation by the European Commission aimed at creating a harmonized regulatory framework for artificial intelligence (AI) systems across the European Union (EU) and is part of the EU’s broader digital strategy.

    The main objectives of the EU AI Act are to ensure the safety, trustworthiness, and ethical use of AI systems while promoting innovation and competitiveness. The act introduces a risk-based approach, categorizing AI systems into four levels of risk: unacceptable risk, high risk, limited risk, and minimal risk.This session aims to provide CDAOs, CIOs, and CROs with the guidance they need to help them address the EU AI Act’s compliance requirements.

    Harnessing the power of AI within regulated industries

    Tabitha Sleap Management Consultant, BIP

    Gabriele Oliva Head of Data Analytics and AI, BIP

    How do you implement cutting edge innovation in heavily regulated industries? In this session with Tabitha Sleap, Management Consultant at BIP, we explore the dual challenge of driving innovation while adhering to stringent governance standards in highly regulated industries such as life sciences and financial services.

    Join us as we discuss the challenges of traditional scientific platforms, tech debt, research silos, and regulatory inertia, and assess what it takes to implement the latest GenAI-driven applications in these environments. In this session, we will also get a sneak peek at one such AI application – a RAG-based site investigation assistant to accelerate the drug development process.

  • 12:30 – 1:30p

    Networking lunch

  • 1:30 – 2:00p

    Realizing AI value through responsible AI in insurance

    Raj Mukherjee Director / Head of Data Science and AI, Direct Line Group

    Innovation and AI governance aren’t at odds. Done properly, responsible AI practices can be the key to accelerating implementation of even the latest GenAI use cases. In this fireside chat with Raj Mukherjee, Head of Data Science and AI at Direct Line Group, we will find out how they embraced the principles of a lean startup, adopted a product mindset and became the first major insurance company to implement a GenAI solution to accelerate customer service. Come find out how they were able to overcome the challenges of legacy infrastructure, build trust and do the seemingly impossible — make compliance fun.

  • 2:00 – 2:30p

    How to make responsible AI happen

    Chris Wiggins Chief Data Scientist, New York Times

    Throughout history, data has been a weapon of truth and power, and AI is on course to become the most powerful weapon yet. What can we learn from the history of data to help us prepare for and shape a responsible AI-driven future?

    Join this fireside chat with Chris Wiggins, Chief Data Scientist at The New York Times and Professor of Applied Mathematics at Columbia University, where we will trace the historical evolution of data to glean insights into the ethical challenges and opportunities AI presents. Wiggins, author of the books “How Data Happened” and “Data Science in Context” will share his thoughts on the role of AI leaders and data science practitioners in ensuring responsible AI, what we can expect of AI regulation, and how we can learn from the ethical data challenges of the past.

  • 2:30 – 2:50p

    Book signing: “How Data Happened”

    Chris Wiggins Chief Data Scientist, New York Times

  • 2:50 – 3:20p

    Unlocking the power of diversity in AI: Lessons from women leaders

    Lisa Carter Founder and CEO, Panelle

    Sarah Tijou VP of Communications, Panelle (moderator)

    Sabrina Palme Co-founder and CEO, Palqee

    Roxana Mohammadian-Molina Former Investment Banker and Tech Investor

    Fostering diversity isn’t just a moral cause, it is critical for business survival. Done well, more diverse teams out-perform and out-innovate the competition. But how do we hire, empower and retain diverse talent and foster diverse AI leaders? How did AI leaders from diverse backgrounds succeed and what are their best practices for fostering diversity in their organizations?

    Join us for this discussion on gender diversity and AI leadership with three pioneering women leaders – Sabrina Palme, Co-founder and CEO of Palqee, Roxana Mohammadian-Molina, Former Investment Banker and Tech Investor, and Lisa Carter, CEO and Founder of Panelle. Learn how their diverse perspectives drove their business success, their leadership best practices, and how to develop strategies for hiring and empowering diverse talent.

  • 3:20 – 3:50p

    It’s the end of the world as we know It (and AI feel fine)

    Kjell Carlsson, Ph.D. Head of AI Strategy, Domino

    Roughly 100 years ago, the Wall Street crash led to the Great Depression and ultimately World War II. Today the conditions for economic catastrophe and geopolitical strife are far more obvious than they were then. Every major asset class is overvalued and debt to GDP ratios are at their highest levels during peacetime. Politicians across the spectrum are pursuing policies that increase protectionism and hurt the global economy.

    In this environment, how do we survive, thrive and maybe even prevent mass economic stagnation? AI (including ML) isn’t our best friend, it is our only friend. Only by accelerating innovation and adoption of AI can we unlock new sources of economic growth, build organizational resilience, and increase agility to changing economic conditions. Through AI we can develop the next generation of products and services, and augment our limited human intelligence that got us into this mess in the first place. We can tackle the biggest challenges humanity faces with AI – health, climate change, conflict. We just need to build our capabilities for innovating with AI, governing it and operationalizing it at scale.

  • 3:50 – 3:55p

    Wrap up

    Thomas Been CMO, Domino Data Lab

  • 3:55 – 5:00p

    Networking reception

    During the reception: Book signing

    Chris Wiggins Chief Data Scientist, New York Times

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