Kristen Smith 
- Public sector governs data better than any industry
- Just 30 percent report full cross-environment data integration
- Agencies have a data access problem, not an AI problem, according to Cloudera executive
Public sector organizations govern their data more thoroughly than any other industry, yet have the least access to it, according to public sector findings Cloudera released Monday from its Data Readiness Index 2026.
According to the research, 72 percent of public sector respondents report that most or all of their data is governed — outpacing healthcare (66 percent), energy and utilities (65 percent) and financial services (61 percent). However, data access reveals a stark inverse trend: only 16 percent of public sector respondents report full data access across environments, trailing financial services at 24 percent and telecommunications at 51 percent.
What Are the Key Barriers to Data Accessibility?
Nearly half of public sector respondents identify complex data access requirements and governance workflows as their primary challenge. Additional bottlenecks include limited visibility into data residency and systemic data silos across agencies.
Consequently, only 31 percent of respondents report complete visibility into enterprise data residency, and just 30 percent have achieved full cross-environment data integration. Furthermore, 24 percent cite poor data quality as the primary driver of underperforming AI investments.
How Should Agencies Govern AI and Data Together?
Dario Perez, group vice president for federal civilian and state, local and education at Cloudera, said agencies do not have an AI problem but a data access problem, and that securely connecting data while maintaining governance will determine whether AI delivers.
Perez has argued that agencies should design AI strategies around existing data constraints rather than moving sensitive data to fit AI tools. In a June blog post, he laid out three principles for organizations seeking to maintain data sovereignty while deploying AI: bringing AI workloads to where sensitive data resides; extending governance beyond datasets to model training, deployment, reuse and retirement; and maintaining lineage and accountability to support audits and compliance.
Ian Brooks, Cloudera’s director of global industry AI solutions for government, has made a related case for private AI, under which an organization hosts its own large language models on infrastructure it controls. He previously warned that agencies waiting until they are ready to scale before deciding how to govern models, data and agents will hit roadblocks.
According to Brooks, solving the data readiness issue demands an end-to-end focus on the data lifecycle — from ingestion and scalable management to security, governance and AI readiness.
He said federal AI governance must encompass three critical layers:
- AI models: Tracking deployment environments, operational runtime and user access permissions.
- Underlying data: Restricting model visibility to align strictly with role-based security requirements.
- AI agents: Managing autonomous systems that execute tasks within third-party environments, introducing novel security risks beyond standard generative text models.
What FedRAMP Authorizations Does Cloudera Hold?
To support secure agency deployment, Cloudera achieved a Federal Risk and Authorization Management Program Moderate provisional authority to operate in June 2025 for its Cloudera for Government platform hosted on AWS GovCloud, allowing users to handle Impact Level 2 federal information in a public cloud environment. This milestone followed an initial FedRAMP Moderate agency authorization sponsored by the Department of Veterans Affairs.
