Bridging the AI readiness gap in government begins with trusted data

In almost every conference and strategy session, Artificial Intelligence (AI) is hailed as the answer to the government’s most pressing challenges—from overcoming workforce reductions to competing with near-peer adversaries. While the potential is enormous, there is a stark reality that the public sector must confront: Much of their data isn’t ready for AI.

According to one industry report, only 12% of large enterprise executives say their data is of sufficient quality and accessibility to support AI at scale. This isn’t just a statistic; it’s a critical warning. Rushing into AI without building a trusted data foundation is a recipe for failed initiatives and wasted resources.

Across the largest public sector organizations, siloed data is the primary pain point. Despite top-down directives, the prevailing culture is still “I am a system owner; therefore, the data is mine.” This entrenched mindset forces analysts into a manual, fragmented data collection process, creating inconsistent outputs and undermining audit quality.

This was difficult enough in the era of dashboards and traditional analytics. However, with the advent of agentic AI and autonomous recommendations, the problem has grown exponentially. Now, it’s not just about trusting the data—it’s also about trusting what fed and trained the model. If agencies can’t deliver clean, governed data fast enough to support the operational tempo of the mission, AI becomes a liability, not a solution.

To break this impasse and prepare for an AI-driven future, government leaders must champion a new approach to data management that includes these three decisive actions:

1. Establish top-down mandates for trustworthy data: This must be a leadership-led, enterprise-wide initiative. The goal is to treat data as a true enterprise asset, breaking down the cultural and technical silos that have held it captive for so long.
2. Modernize with open, flexible architectures: Adopt cloud-native, open-source tools like Apache Iceberg on AWS. This architecture allows data to be stored once in secure environments like Amazon S3 and mirrored across consumers without lock-in, ensuring agencies can take advantage of the rapid growth of data anticipated in the coming years.
3. Empower users with governed, at-scale analytics: Agencies need analytics platforms that go beyond dashboards but don’t require custom coding. Empowering staff with access to trusted, governed data unlocks value without adding complexity.

By embracing this data-first philosophy, agencies can unlock three transformative benefits:

To start, they will realize the value of AI. Without a trusted data foundation, AI is just an expensive experiment. The data shows it: a recent Boston Consulting Group study found that only 26% of AI initiatives realized value in 2024. By prioritizing data readiness, agencies can finally cross this chasm and turn AI’s promise into tangible mission outcomes.

Second, they can achieve real-time mission agility. In national security settings, policy shifts and emerging threats demand rapid decision-making. Qlik supports agencies where data is expected to answer questions that have yet to be asked. This level of agility is only possible when multiple data sources are unified in platforms like AWS and when non-technical subject matter experts can generate insights in real time as the mission changes.

Finally, agencies will be able to show that enterprise-scale modernization is not only possible but achievable. For example, the DoD CDAO’s Advana platform remains one of the most successful government data integration efforts to date. Its success was built upon key pillars: strong top-down ownership, a centralized cloud foundation and a steadfast cultural commitment to dismantling data silos.

At Qlik, we focus on helping agencies work with whatever data they have — wherever it lives — and convert it into mission-ready insights. Unlike ERP or CRM vendors, we specialize in integrating data from hundreds of sources into modern cloud environments like AWS to power real-time analytics.

Our partnership with AWS is a critical multiplier in this effort. Their global footprint helps us solve complex data sovereignty issues for our customers, while AWS Marketplace streamlines acquisition and Amazon Bedrock accelerates GenAI integration with minimal friction. Together, we help agencies build modular, interoperable data ecosystems that scale.

The journey to an AI-enabled government begins and succeeds with data. By committing to enterprise-wide data trust, federal agencies can stop talking about transformation and start delivering on it.

Learn more about how Qlik and AWS can help your organization optimize the use of data analytics in the cloud.

Discover how other AWS partners are helping agencies accelerate their AI and cloud modernization efforts.

The article was sponsored by AWS and Qlik.