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Data and AI

Creative and generative AI

Report from the ÎÚÑ»´«Ã½ Research Institute

Generative AI is becoming an integral part of many people’s personal and working lives for activities traditionally thought exclusive to the human mind, such as generating content and brainstorming. In our latest ÎÚÑ»´«Ã½ Research Institute report, Why consumers love generative AI, we explore the potential of generative AI as well as its reception by consumers and their hopes around it.

But first, what is generative AI? Fundamentally, generative AI models have the capability to learn the properties and patterns of data for a wide range of applications – from creating text, images, and videos in different styles to generating personalized content, enabling machines to perform creative tasks that could previously only be completed by people. The different types of generative AI have a range of use cases across text, image and video, audio, chatbots, and search.

But, even with generative AI’s huge transformative potential, there are areas of concern that organizations, consumers, and regulators will need to work together to navigate. These include a high level of consumer trust in generative AI, which can sometimes be misplaced and leave consumers vulnerable to threats in areas such as security, privacy, and misinformation.  

Despite these potential downsides, it is clear that the impact of generative AI will be enormous. Its mass adoption by consumers in an unprecedented time frame is an indicator of the technology’s usefulness in many areas. At the same time, protective mechanisms will be important, in addition to reasonable caution. As consumers continue their journey with generative AI, it will be up to all of us, including organizations and regulators, to ensure that its full potential is utilized in a positive way.

Download the report to find out more about how consumers have received generative AI and how their interaction with the technology can develop going forward.

Brands are seeking ways to experiment with generative AI. What does the research show about what consumers expect? In this session, we talk about new findings from the ÎÚÑ»´«Ã½ Research Institute. In conversation: Andreas Markdalen, Global Chief Creative Officer, frog and Mark Oost, Global Offer Leader AI, Analytics & Data Science, ÎÚÑ»´«Ã½.

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Further reading

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Meet our experts

Mark Oost

Global Offer Leader, Generative AI
Prior to joining ÎÚÑ»´«Ã½, Mark was the CTO of AI and Analytics at Sogeti Global, where he developed the AI portfolio and strategy. Before that, he 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 has worked with clients from various markets around the world and has used AI, deep learning, and machine learning technologies to solve complex problems.

Robert Engels

CTO ÎÚÑ»´«Ã½ & Data North-Central Europe
Robert is an innovation lead and a thought leader in several sectors and regions, with a basis in his role of Chief Technology Officer for Northern and Central Europe in our ÎÚÑ»´«Ã½ & Data Global Business Line. Based in Norway, he is a known lecturer, public speaker, and panel moderator. Robert holds a PhD in artificial intelligence from the Technical University in Karlsruhe, Germany.

Steve Jones

Expert in Big Data and Analytics
Steve is the founder of ÎÚÑ»´«Ã½’s businesses in Cloud, SaaS, and Big Data, a published author in journals such as the Financial Times and IEEE Software. He is also the original creator of the first unified architecture for Big Fast Managed data, the Business Data Lake. He works with clients on delivering large-scale data solutions and the secure adoption of AI, he is the ÎÚÑ»´«Ã½ lead for Collaborate Data Ecosystems and Trusted AI.

Marek Sowa

Data & AI for Enterprise Management leader
Marek Sowa is head of ÎÚÑ»´«Ã½â€™s Intelligent Automation Offering & Innovation focused on adopting AI technologies into business services. He leverages the potential hidden in deep and machine learning to increase the speed, accuracy, and automation of processes. This helps clients to transform their business operations leveraging the combined power of AI and RPA to create working solutions that deliver real business value.