Marketing ‘unprepared’ for generative AI, finds Kantar study

UK – A majority of marketers feel unprepared for implementing and integrating generative artificial intelligence into their organisations, with high costs and a lack of training key issues, according to a report by Kantar.

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Kantar’s GenAI for marketing: Fear or FOMO report, which is based on in-depth qualitative interviews with more than 50 marketing leaders in Europe, the US and Australia in the last quarter of 2024, found there was a gap between the potential of generative AI and its current rates of adoption.

Senior marketers and capability builders said that while generative AI would be a game-changer, with interviewees rating its impact at nine out of 10 on average, organisational readiness was lagging, with respondents rating their company’s readiness at 4.9 out of 10.

External partners, such as agencies and data providers, were seen as comparatively ahead of the curve, albeit at a still lowly 5.3 out of 10.

Kantar said that this lack of readiness is holding back marketing’s adoption of generative AI, with respondents believing that the industry is still in the early stages, rating the current impact of the technology on the industry at 5.3 out of 10. 

A lack of job-specific generative AI training was also identified as an issue in the study.

Four areas were identified for where generative AI could play a role in marketing, including in building long-term brand strategies and challenging, validating and fine-tuning marketing outputs, as well as operational efficiency, automated marketing and brand elevation.

Thomas von der Fuhr, consulting senior director at Kantar, said: “The overwhelming consensus among senior marketers is that GenAI is going to revolutionise the industry. But reality today is that many companies don't feel ready yet.

“We see that leading organisations are making the shift from using GenAI predominantly for efficiency reasons to now also drive effectiveness. Implementation isn’t straightforward: ethical use, training and data quality all need to be addressed.

“Those that get it right will succeed by building excitement and understanding around GenAI among everyone in their business: explaining what the tools can and cannot do, and how they can help them achieve more with greater efficiency, speed, and effectiveness.”

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