A newly released Risk Intelligence Report by Databricks has identified inconsistent execution as the primary barrier preventing enterprises from scaling their AI deployments. The survey, which covered over 400 IT and data leaders across sectors, revealed that while a significant 92% of organisations plan to increase their AI investments over the next 12 months, only 26% have successfully operationalised and scaled their AI initiatives.
The report points out that internal fragmentation—such as data silos, lack of unified data infrastructure, and poor cross-functional collaboration—is stalling progress. Additionally, over 60% of respondents highlighted the absence of a well-defined AI strategy and governance framework as critical roadblocks. Even with growing awareness of AI’s transformative power in driving innovation and efficiency, many enterprises remain stuck in pilot phases, unable to translate experiments into scalable, real-world applications.
Databricks emphasises that the solution lies in aligning stakeholders around a common data strategy, breaking down silos, and creating reusable AI assets supported by scalable architecture. As global competition intensifies, organisations that fail to address these foundational gaps risk falling behind. The report serves as a wake-up call for enterprises to shift focus from hype-driven experimentation to disciplined, strategy-led AI execution.
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