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Data and AI

Riding the next generative AI wave

The opportunities to transform, thanks to generative AI, are multiple and promising – and each CXO is looking at making their initiatives meaningful for their business and industry-specific context.

With the urge to accelerate and scale GenAI adoption across their organisation, comes challenges such as cost control, security, or ethics.

In this point of view, we explore three major dimensions of generative AI for organisations to succeed: cost, scale, and trust. From cost efficiency of large language models (LLM) to adaptative scaling and ethical data sourcing, you will learn how to best develop and deploy your custom GenAI projects by focusing on value use cases fitting your business goals – and how to create tangible and reliable outcomes.

Generative AI

As Generative AI continues to advance, early adopter organisations will benefit from reinvented business models and processes.

Related research and insights

Meet our experts

Mark Oost

Global Offer Leader – AI Analytics & Data Science
Prior to joining Capgemini, Mark was the CTO of AI and Analytics at Sogeti Global, where he developed the AI portfolio and strategy. Before that, Mark worked as a Practice Lead for Data Science and AI at Sogeti NetherLands, where he started the Data Science team, and as a (Lead) Data Scientist at Teradata and Experian. Throughout his career, Mark had the opportunity to work with clients from various markets around the world and has used AI, deep learning, and machine learning technologies to solve complex problems.

Steve Jones

Expert in Big Data

Anne-Laure Thibaud (Thieullent)

Executive Vice President, Data & AI Group Offer Leader
Choosing the right technology for the right usage is key, but how your company should change the way it acts around data is vital. My passion is to bring technology, business transformation and governance together and take our clients to where they want to be as Intelligent Enterprises, while cultivating the values of trust, privacy and fairness.