Enhancing Access to and Sharing of Data in the Age of AI: Implications for Federal Contractors
Access to high-quality data is a critical factor in the development of artificial intelligence (AI), but developers often face shortages in obtaining such data. The OECD’s Recommendation on Enhancing Access to and Sharing of Data offers a structured approach for nations to optimize data sharing while ensuring protections for individuals and organizations. This policy framework emphasizes the need for a balanced approach—maximizing open access to data and AI models wherever possible while maintaining necessary security, privacy, and intellectual property safeguards.
The report underscores the growing importance of treating AI models themselves as a form of data, given their role in encapsulating recorded information. As AI models become more widely used, policymakers are urged to apply existing data governance principles consistently to both datasets and AI models, ensuring a coherent regulatory framework. This recognition is crucial as it aligns AI governance with broader data-sharing policies, reinforcing trust across the ecosystem.
The principle of Findable, Accessible, Interoperable, and Reusable (FAIR) data is at the heart of the OECD’s approach. By ensuring that data is structured in a way that facilitates discovery and reuse, governments can foster transparency and efficiency in AI deployment. Some countries are already exploring methods such as privacy-enhancing technologies (PETs) and trusted data intermediaries (TDIs) to balance data accessibility with privacy concerns. These tools are seen as essential for maintaining confidentiality while still enabling the benefits of shared data and AI models.
For federal contractors, the implications of this report are substantial. As AI adoption increases across government agencies, contractors must stay ahead of evolving data governance requirements. The report highlights that AI-driven systems require vast amounts of structured and unstructured data, meaning that contractors supplying AI solutions must comply with policies that govern both the use of raw data and the AI models trained on that data. This includes ensuring that data used in federally contracted AI applications adheres to privacy regulations and security measures, such as those outlined in frameworks like the Federal Risk and Authorization Management Program (FedRAMP).
Another key takeaway from the OECD report is the concept of a data openness continuum, which provides varying levels of access based on need and sensitivity. While open data initiatives are encouraged to spur innovation, certain datasets—such as those related to national security—must remain closed or shared under strict conditions. Federal contractors operating in sensitive domains should be mindful of these tiers of data openness and anticipate evolving compliance obligations.
Moreover, the report stresses the need for a whole-of-government approach to data strategy, encouraging agencies to align data-sharing policies across sectors. This is particularly relevant to government contractors involved in cross-agency initiatives, as inconsistent data governance frameworks can create friction in executing federal projects. Contractors that proactively develop policies to navigate these complexities will be better positioned to offer AI-driven solutions that align with federal priorities.
The OECD also addresses the growing practice of releasing AI models as open-source, with varying degrees of accessibility. While this trend has the potential to accelerate AI adoption, it also raises concerns about ensuring the quality, integrity, and security of shared models. The challenge for contractors lies in balancing the push for transparency with the need to protect proprietary and sensitive AI systems. For those in the defense and security sectors, this means carefully considering how AI models are distributed and ensuring compliance with federal security protocols.
Additionally, the report points out that trust remains a significant barrier to the effective sharing of data. Many stakeholders hesitate to share data due to concerns about misuse, competitive disadvantages, or regulatory uncertainty. Federal contractors working in AI must therefore engage in robust risk assessments and compliance reviews to build confidence with both government clients and the broader public.
From an economic standpoint, the OECD estimates that improved access to and sharing of public and private-sector data could contribute between 1% and 2.5% of GDP growth. This underscores the financial incentives for governments and contractors alike to refine their data-sharing practices. However, the slow adoption of AI and big data analytics, particularly among small and medium-sized enterprises (SMEs), presents a challenge. While large contractors may have the resources to navigate complex data-sharing policies, smaller firms may struggle with compliance, limiting their ability to compete effectively in federal contracting opportunities.
In light of these findings, policymakers are encouraged to implement measures that foster responsible data-sharing ecosystems. Recommendations include promoting market-based approaches to data access, supporting regulatory sandboxes to test AI applications under controlled conditions, and enhancing interoperability between public and private-sector data systems. For contractors, this means staying informed on regulatory developments, investing in compliance infrastructure, and advocating for practical policies that support both innovation and security.
As federal agencies continue to expand their reliance on AI, contractors will need to align their data governance strategies with emerging international frameworks like the OECD’s Recommendation on Enhancing Access to and Sharing of Data. Those that do so effectively will not only remain compliant but also position themselves as leaders in the AI-driven federal marketplace.
Disclaimer: This blog post is for informational purposes only and does not constitute legal or regulatory advice. While efforts have been made to ensure accuracy, policies and regulations may change, and contractors should consult official sources or legal counsel for specific guidance.
