Data Infrastructure in OBBB: Reviewing Key Provisions

Passage of the federal reconciliation bill—dubbed the "One Big Beautiful Bill" (OBBB) by its supporters—includes big changes for the country, and more than just for fiscal policy. Embedded within its hundreds of pages are significant federal data provisions that signal Congress's continued commitment to using data as a tool for government efficiency, fraud prevention, and evidence-based decision-making.

As the nonpartisan Data Foundation has long advocated, effective government depends on high-quality data infrastructure. While federal capacity constraints – including those documented in the Data Foundation’s Evidence Capacity Pulse Reports – present real challenges in 2025, the final OBBB legislation demonstrates that data remains central to how Congress envisions a more effective, accountable government.

The Data Infrastructure Imperative

The OBBB bill's most significant data investments center on what we've long called "data as infrastructure"—systems that prevent fraud, reduce waste, and improve program integrity. Three provisions stand out:

• Cross-State Verification Systems: The legislation establishes a federal system to prevent duplicate Medicaid enrollment across states, with implementation beginning in 2029. This builds on lessons learned from the Payment Accuracy Information System (PARIS) and represents exactly the kind of cross-agency data sharing that can deliver measurable taxpayer savings.
   
• Enhanced Eligibility Verification: New requirements for Premium Tax Credit verification will use “real-time” data from multiple sources—income verification, residency validation, and immigration status checks—before qualifying applicants for monthly credits. This automated approach exemplifies how modern data systems can improve program integrity without creating excessive administrative burden.
   
• AI-Powered Auditing Systems: The Department of Defense receives $200 million specifically for "deployment of automation and artificial intelligence to accelerate the audits of financial statements." This represents an increasingly modern approach to leveraging emerging technologies for government efficiency—exactly the kind of strategic AI application the Data Foundation has advocated for.

Beyond Fraud Prevention: Data for Innovation

OBBB also includes forward-looking provisions that position government data as a strategic asset for American competitiveness:

• The American Science Cloud: The Department of Energy's $150 million investment aims to mobilize National Laboratories to structure and preprocess scientific data for AI and machine learning applications. Importantly, the legislation requires these models to be made available to the broader scientific community through a cloud-based platform—embodying the principles of open data and collaborative innovation.
   
• Relevant Performance Metrics: From Qualified Opportunity Zones reporting requirements to postsecondary education earnings benchmarks, the bill establishes outcome-focused metrics across multiple programs. Congress’s articulation of the specific data elements and information it needs reflects an approach for accountability, tying together policy decisions and funding eligibility.

Navigating Capacity Constraints

Notwithstanding the changes in OBBB, federal agencies face significant capacity constraints, and many data governance functions have been consolidated or reduced. The bill reflects these realities and policy priorities—while also introducing some new capacity restraints. For example, OBBB rescinds funding for EPA greenhouse gas corporate reporting and Council on Environmental Quality climate data collection, but also invests billions in verification systems and defense AI capabilities. Many federal agencies are reorganizing and grappling with changes in staff or contractor capacity and infrastructure. Congress appears to also be adapting its approach by focusing on high-impact, automated systems that deliver measurable results without requiring extensive new agency infrastructure. The verification systems established in OBBB appear to be designed to operate with minimal human intervention once implemented while providing human-led decision support tools—exactly the kind of "smart government" approach that makes sense given current constraints.

The Reconciliation Context Matters

What makes these data provisions particularly noteworthy is their inclusion in reconciliation legislation. Under Senate rules, only provisions with direct budgetary impact can be included in reconciliation bills. The fact that these data systems cleared that threshold demonstrates concrete, quantifiable value in reducing improper payments and improving program efficiency.

This is data policy designed for fiscal impact, as well as better information for decision makers. Each verification system included in the bill had to demonstrate measurable savings that the Congressional Budget Office (CBO) scored. In other words, these data policy changes reflect data investment as essential infrastructure for effective government.  

What This Means Going Forward

As we've learned from implementing previous data legislation and large bills with data provisions, success depends on more than just statutory requirements. Agencies will need technical assistance, coordination support, and meaningful stakeholder engagement to implement these systems effectively. The OBBB’s 2029 implementation timeline for major verification systems provides breathing room for thoughtful implementation that prioritizes privacy protection, system interoperability, and stakeholder input. This is especially important given that many of these systems will handle sensitive personal information and require coordination across multiple federal and state agencies, and processes to ensure robust privacy protections are deployed consistent with other relevant law and policy

While the current political environment has constrained some aspects of federal data governance, it has also clarified priorities around efficiency, accountability, and results for the current administration and Executive Branch. The Data Foundation will continue monitoring implementation of these provisions and providing technical assistance where helpful. We'll also be analyzing how these systems can serve as models for broader improvements in federal data infrastructure.

Clearly data infrastructure remains essential to effective governance, regardless of partisan differences on specific programs or priorities. Whether the goal is preventing fraud, accelerating scientific research, or improving program outcomes, effective government depends on high-quality data systems and information. 

NICK HART, PH.D. is President and CEO of the Data Foundation.