AI infrastructure challenges delay projects for 95% of organizations

Research from Cloudera indicates that 95 percent of organizations have delayed or canceled AI projects due to infrastructure limitations and governance challenges. According to the ‘The Great AI Re-Architecture’ study, which surveyed 1,500 enterprise and data architects globally, the growth of AI is exposing deficiencies in outdated data architectures. Approximately 72 percent of respondents believe their current data architecture requires a thorough overhaul to support future AI requirements.

Key obstacles include data management, compliance, and regulatory issues. The integration of AI has also led to increased costs, with 84 percent of surveyed organizations reporting a rise in infrastructure expenses. Furthermore, 73 percent noted that AI has made data governance more complex. To address these issues, many organizations are shifting toward hybrid environments that manage data across cloud, on-premises, and edge locations to maintain control and security.

As AI infrastructure evolves, it is increasingly viewed as a strategic economic utility. Beyond software, it requires a foundation of computing power, storage, networking, and model access. Establishing reliable, independent AI capacity is becoming a critical factor for companies and governments to maintain productivity and competitiveness without becoming overly dependent on external providers.