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Preparing and Delivering Data for AI – Adoption Trends, Requirements and Best Practices
This study provides key insights into the obstacles and best practices for preparing data for AI. Get your data ready to avoid common problems.
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This study explores the following questions
- What does it take to make data usable for AI/ML and GenAI?
- What are the best practices of leading AI adopters?
- What are the biggest roadblocks to AI access?
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Further information
AI adopters are accelerating their rollouts in year three of the ChatGPT-triggered boom. The risks look manageable and the early results promising. In fact, we might even stand on the cusp of a generational boost to productivity, innovation and economic growth. But of course there’s a catch: the success of AI depends on how well adopters manage the data that feeds these powerful algorithms. And data management is progressing in some areas but lags in others.
This BARC study examines the pains, priorities and practices of 370 data stakeholders as they prepare and deliver data to support AI innovation.
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