This indicates that the use of AI has gone from experimentation to full integration in core processes and workflows, notes the company in its Sept 25 release.
The use of AI has also yielded results within these companies, with 70% reporting “significant success” while only 1% said they have yet to see results.
According to the survey, companies are using a variety of AI forms, with 60% using generative AI, 53% using deep learning models and 50% using predictive platforms. About 67% of the IT leaders polled this year say they are more prepared to manage new forms of AI, particularly AI agents.
Leaders are also gaining confidence when it comes to diversifying their AI portfolios. This year, the survey found that 67% of IT leaders are feeling more prepared to manage new forms of AI, particularly AI agents.
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Based on this year’s findings, a hybrid approach to data architecture seems to have become the norm, with organisations managing AI across the cloud and on-prem environments. According to the poll, security (62%) was cited as the biggest advantage of a hybrid approach, along with improved data management (55%) and improved data analytics (54%).
Yet, integrating AI comes with security concerns such as data leakage during model training. Among the respondents polled, 48% cited unauthorised data access as a concern while 43% named unsecured third-party AI tools as another concern.
That said, 24% of respondents indicated that they were “extremely confident” in their organisation’s ability to secure the data used in AI systems. About 53% said they were “very confident” while 19% were “somewhat confident”.
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Despite the progress, the survey indicated that there is some room to grow when it comes to maximising the potential of AI uses and return on investment (ROI). While 24% of the respondents said their culture is now extremely data-driven, up from 17% last year, most recognise that more work is needed to embed data-first thinking into business practices.
Among the technical limitations identified in current data architectures when supporting AI workloads, data integration (37%), storage performance (17%) and compute power (17%) were identified. Data accessibility is another issue with only 9% of organisations indicating that all of their data is available and usable for AI initiatives, while only 38% reported that most of their data is accessible.
“In just a year, AI has shifted from a strategic priority to an urgent mandate, actively reshaping operations and redefining the rules of competition,” says Sergio Gago, chief technology officer at Cloudera. “But our survey shows that enterprises still face deep challenges around security, compliance, and data utilisation, with many getting stuck at the proof-of-concept stage.”
