Unlocking AI value in the public sector starts with people, not technology. While investments in AI solutions accelerate, many organizations overlook the critical human capabilities that enable them. Without a workforce that understands, trusts, and can act on data, even the most advanced AI initiatives will underdeliver.

The foundation lies in developing a deliberate triad of agency capabilities: data literacy, AI fluency, and a pervasive culture of continuous learning and improving — all of which are prerequisites for AI readiness. Forrester’s Data And Analytics Survey, 2025, reveals that over a quarter of public sector data leaders cite a lack of data literacy as one of the top key barriers to success. That signals an imperative: Upskilling must be designed, executed, and measured as a strategic imperative — not treated as a tactical task.

  1. Make Improving Data Literacy The Starting Point

Begin with a targeted push on improving data literacy for all employees, moving beyond technical know-how. Focus on cultivating a mindset shift. Build programs that embed curiosity, creativity, and mission-driven critical thinking. Don’t outsource this. Internal training must be grounded in your agency data, use cases, and workflows — not generic examples. Specifically:

  • Craft and deploy an effective training program to create a strong link between data insights and tangible real-world outcomes. Encourage a fail-fast mentality, encouraging staff to test, learn, and improve. It should also position employees as collaborators with AI systems — not passive recipients of automated outputs.
  • Accelerate curiosity velocity — the ability of employees to independently explore data, ask smarter questions, identify insights, and convert those insights into timely action — to drive action. Increasing curiosity velocity reduces the time in an individual’s journey from knowledge seeker to insights acquisition to action. Curiosity velocity is a leading indicator of data cultural maturity and the biggest indicator to AI readiness and insights adoption.
  • Leverage data literacy, technology, data, analytics, and AI-specific courses available to the public sector from vendors (AWS, Microsoft, Google) and learning platforms (Coursera). But don’t forget to layer in domain-specific learning. Introduce workshops tailored to key data use cases within branches/departments of the public sector. Contextual learning shortens the distance between knowledge acquisition and operational impact.

  1. Apply A Role-Based Approach To AI Fluency

Upskilling is not one-size-fits-all. First, define and prioritize AI and generative AI use cases such as advanced (predictive, causal) analytics, automation, content generation, natural language processing, and data/analytics. Then map use cases to the skills. For example, technical teams need to go deep on prompt engineering, retrieval-augmented generation (RAG), and guardrail design to reduce hallucinations and ensure responsible output. Business teams need fluency in assessing AI tools, identifying high-impact use cases, and applying ethical frameworks. Everyone should understand the dimensions of explainability, scalability, and risk — and know how to choose between building, buying, or automating.

  1. Measure What Matters, Learn, And Improve

Measurement of your progress in data literacy and AI fluency is nonnegotiable. Establish baselines with pretraining assessments (such as the Forrester AIQ Assessment), then embed microcertifications, scenario-based tests, and capstone projects that use real agency data. Monitor tool adoption, insight sharing, and engagement in internal data communities. Track curiosity velocity directly by embedding continuous learning into daily operations. Incentivize participation with recognition, certification, and visibility. Activate internal mentors, data ambassadors, and peer learning forums to reinforce habits. When learning becomes part of the culture, not just the curriculum, AI becomes operational — not theoretical.

  1. Invest In People To Unlock AI Value

Agencies that treat upskilling as a core transformation lever will outpace those that rely solely on technology upgrades. A workforce trained in data, fluent in AI, and driven by curiosity will unlock impact at scale.

For more information, set up a call with one of our analysts covering AI.