Fivetran released new research showing that 49% of enterprise technology leaders believe their current data architecture can handle the demands of AI. At the same time, 89% say they plan to use proprietary data to train LLMs this year. The disconnect highlights how quickly companies are pushing forward with AI, even as they acknowledge their data systems aren’t ready. 68% said they rely on 50 or more data sources to support decision-making, and more than a third cited integration complexity as a major hurdle. Others pointed to scalability limitations (34%) and security and compliance risks (33%) as top concerns. Half of the executives surveyed said their organizations plan to invest $500,000 or more in data integration over the next year. Their focus areas include reducing manual pipeline maintenance, improving real-time access to data, and ensuring data quality and governance. Still, challenges remain. 45% reported a lack of automation or self-service capabilities, 44% said legacy systems and implementation costs were holding them back, and 41% pointed to talent gaps on their data teams. The report also shows how the role of the technology leader is shifting, with 48% expecting to take on more responsibility for data privacy and compliance, and 45 percent anticipating a larger role in company-wide data strategy. Some organizations are already seeing results. Key findings include: 89% of tech leaders plan to use proprietary data to train LMMs this year, but only 49% believe their architecture can support AI workloads; 68% say they rely on 50 or more data sources to support decision-making; 64% of CIOs have delayed innovation efforts due to compliance concerns; 50% plan to invest $500,000 or more in data integration in the next year; Nearly half of respondents expect to take on more responsibility for privacy, compliance, and company-wide data strategy.