Data Governance Concerns in the Age of AI
As many organizations make use of generative AI, there is growing concern about data governance issues that may emerge.
What are the main data governance concerns with generative AI?
Organizations are expressing significant concerns regarding data governance when using generative AI. Key issues include security, privacy, transparency, ethical considerations, and the risk of data leakage into vendor AI models. According to a recent survey, two-thirds of organizations reported these apprehensions.
How are organizations preparing for AI adoption?
Organizations are prioritizing AI preparedness as a top data storage focus for 2023. This involves developing strategies that ensure they are equipped to manage data effectively in the context of AI adoption, reflecting a proactive approach to integrating AI into their operations.
What challenges do organizations face in data management?
Organizations are facing several data management challenges, including the need to move large volumes of data seamlessly, prepare for AI and cloud services, and engage non-IT personnel in data management processes. A significant 85% of respondents believe that involving non-IT users is crucial for effective data management.
Data Governance Concerns in the Age of AI
published by Thales Security
Businesses and governments rely on Thales to bring trust to the billions of transactions they have with people. Our identity and data protection technologies help banks exchange funds, people cross borders, energy become smarter, and much more. More than 30,000 organizations already rely on Thales solutions to verify the identity of people and things, grant access to digital services, analyze vast quantities of information and encrypt data.
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