AI Survey: Integration Challenges, High Model Costs, and Growing Adoption
A recent survey on AI and data architecture reveals key trends and challenges. Notably, 37% of respondents struggle with data integration, while 46% cite security and compliance risks as the main barrier to AI adoption. Despite this, 96% of IT leaders have integrated AI into their core processes to some extent.
The most popular AI models in use are generative (60%), deep learning (53%), and predictive (50%). However, 42% of respondents find the cost of model training computation too high, a significant increase from last year's 8%.
Looking ahead, 52% of IT leaders prioritize integrated AI and ML operations tooling in their data architecture. Meanwhile, 44% emphasize the need for granular data governance. Interestingly, 36% already employ agentic AI models, suggesting a growing trend in AI adoption and integration.
The survey underscores the progress and challenges in AI integration. While data integration issues and high model training costs persist, IT leaders are increasingly adopting and integrating AI into their core processes. The demand for robust AI and ML operations tooling and granular data governance indicates a maturing approach to AI in enterprise environments.
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