A vast majority of enterprises have embraced artificial intelligence (AI) in some capacity but lack foundational infrastructure and expertise necessary to maximize its potential, according to a new survey released Thursday by data management company Cloudera Inc.
The study, which surveyed 600 IT leaders across the U.S., Europe, Middle East and Africa, and Asia-Pacific regions, found 88% of enterprises are adopting AI technologies.
Significant obstacles remain that prevent organizations from fully capitalizing on their AI investments, however. Security and compliance risks emerged as the primary concern for organizations, with 74% of respondents citing these issues as their biggest barrier to AI adoption.
A skills shortage also loomed large, with 38% of IT leaders reporting they lack proper training or talent to manage AI tools effectively. Cost considerations ranked third, with 26% saying AI tools are too expensive for their organizations.
“These findings signal that despite rapid AI adoption, many pillars of a resilient AI strategy are being neglected or forgotten,” the report noted.
A striking contradiction emerged around data trust and accessibility. While 94% of respondents expressed confidence in their data quality, 55% admitted they would rather endure a root canal than attempt to access all of their company’s information.
The frustration stems from several challenges: 49% struggle with contradictory datasets, 36% cannot effectively govern data across multiple platforms, and 35% feel overwhelmed by the sheer volume of information their organizations generate.
These issues point to a fundamental problem with modern data architecture, suggesting many enterprises lack systems that provide secure, accessible, and trustworthy data access across their organizations.
“In my 15 years in the AI field, we have gone from analytics, then machine learning, AI, agentic AI, and soon AGI,” Manasi Vartak, chief AI architect at Cloudera, said in an interview. “Change is the only constant, and everyone is well aware of the importance of guardrails.”
Despite these challenges, companies are finding practical applications for AI technology. The survey identified three primary use cases:
Customer Experience Enhancement (60%): Organizations are deploying AI for security and fraud detection (59%), automated customer support (58%), predictive customer service (57%), and chatbot functionality (55%).
Operational Efficiency Gains (57%): AI integration extends beyond IT departments, with 52% using the technology for customer service improvements and 45% applying it to marketing initiatives, such as analyzing call center data to deliver targeted customer incentives.
Analytics Acceleration (51%): Nearly 80% of respondents reported their companies are leveraging available data to make smarter business decisions, with AI helping to provide faster and more reliable access to critical insights.
Cloudera Chief Strategy Officer Abhas Ricky emphasized the importance of bringing AI models to existing data rather than the traditional approach of moving data to centralized systems.
“For the majority of companies, the quality of their data is not great, it’s distributed across various infrastructures and not documented in an efficient manner,” Ricky said. “Managing data where it resides is the most important thing when it comes to adopting AI — being able to run models in a cost efficient manner where that data already lives.”
“High AI budgets create pressure to deliver, but only if you have the talent,” Ricky said in an interview. “The market is growing too fast. It creates an urgency to adapt and innovate faster.”
