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As generative AI becomes the new normal, data strategies must keep up, as well as priorities around adoption and investments

If you would like to learn more about generative AI Then this white-paper is for you:

• Among data leaders implementing or planning to implement generative AI, the quality of data (42%) is the top data-related obstacle to the adoption of generative AI and large language models (LLMs) reveals a survey of 600 data leaders from companies with $500M+ in revenue from the U.S., EU, and APAC regions conducted by Wakefield Research on behalf of Informatica.
• Top data strategy priorities for 2024 include delivering reliable and consistent data fit for generative AI (39%), improving data-driven culture and data literacy (39%), and improving governance over data and data processes (38%)
• An impressive 45% have already adopted generative AI (including 50% in the U.S. and 48% in the UK/EU) and another 54% anticipate doing so, including 36% who expect to adopt it within two years—which explains why delivering reliable and consistent data fit for generative AI (39%) is the most commonly cited main priority for organizations’ data strategies.
• All who are adopting or planning to adopt generative AI (more than 99%) have encountered challenges, including quality of data (42%, led by 49% of those in the U.S.) and data privacy & protection (40%)—familiar big picture issues data leaders face elsewhere
• At 43%, improving readiness of data for AI and analytics initiatives is the most common metric for measuring data strategy effectiveness.

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