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When building enterprise AI, some companies are finding the hardest part is sometimes deciding what to build and how to address the various processes involved.
At VentureBeat Transform 2025, data quality and governance were front and center as companies look beyond the experimental phase of AI and explore ways to productize and scale agents and other applications.
Organizations are dealing with the pain of thinking through how tech intersects with people, processes and design, said Braden Holstege, managing director and partner at Boston Consulting Group. He added that companies need to think about a range of complexities related to data exposure, per-person AI budgets, access permissions and how to manage external and internal risks.
Sometimes, new solutions involve ways of using previously unusable data. Speaking onstage Tuesday afternoon, Holstege gave an example of one client that used large language models (LLMs) to analyze millions of insights about people churn, product complaints and positive feedback — and discovering insights that weren’t possible a few years ago with natural language processing (NLP).
“The broader lesson here is that data are not monolithic,” Holstege said. “You have everything from transaction records to documents to customer feedback to trace data which is produced in the course of application development and a million other types of data.”
Some of these new possibilities are thanks to improvements in AI-ready data, said Susan Etlinger, Microsoft’s senior director of strategy and thought leadership of Azure AI.
“Once you’re in it, you start getting that sense of the art of the possible,” Etlinger said. “It’s a balancing act between that and coming in with a clear sense of what you’re trying to solve for. Let’s say you’re trying to solve for customer experience. This isn’t an appropriate case, but you don’t always know. You may find something else in the process.”
Why AI-ready data is critical for enterprise adoption
AI-ready data is a critical step to adopting AI projects. In a separate Gartner survey, more than half of 500 midsize enterprise CIOs and tech leaders said they expect that adoption of AI-ready infrastructures will help with faster and more flexible data processes.
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