AI in government: The path to adoption and deployment

Although some government organizations are at the forefront of artificial intelligence (AI), many others are slower to adopt than their peers in the public and private sectors. But, as the advantages of AI grow too compelling to overlook, the question for government leaders is shifting from “if” to “when” to join the movement. 

In the Economist Impact report, Reimagining the power of public sector productivity, 58% of public sector leaders surveyed agreed digital transformation is the most effective route toward greater productivity. Nearly all believe AI can accelerate this shift, with 90% agreeing the benefits outweigh any risks. Yet hesitation remains, as more than a quarter of respondents have no current plans to adopt AI.

Survey results show their reluctance stems from perceived gaps in data privacy protection, change management, funding and strategy:

• 75% have data privacy concerns.
• 64% face budgetary constraints.
• 52% cite staff resistance to change.
• 47% lack appropriate productivity metrics.

For many leaders in public services who are holding back, the underlying issue is often a gap in confidence. Can they integrate AI solutions and still protect citizen data, deliver high-quality services, support staff developing AI applications and stay within budget? And what lessons can they take from the experiences of their peers? 

At SAS, we’ve led public sector data transformations worldwide by listening closely and focusing on what matters most. Here’s a look at what we've gathered along the way. 

Robust data and AI oversight and governance

Government agencies manage highly sensitive citizen data such as social security numbers, health records and public benefits. Much of that information is locked in data silos across platforms. To protect privacy and maximize value, public sector agencies must adopt strong data management practices to ensure comprehensive and clean data as well as privacy controls. When adopting data analytics and AI, be sure your systems include these essential elements:

• Established policies for data handling, security and regulatory compliance. 
• Clearly defined, consistent data formats, definitions and quality metrics.
• Transparent data practices to nurture public trust.
• Oversight for data policy implementation and enforcement.

As AI expands across public services, effective oversight is critical. Similar to the private sector (on a bigger scale), errors in government systems, such as denying a claim, can deeply impact lives. Human-centered governance remains essential for safe, effective AI. 

Unlocking gains

Rising confidence in data safety doesn’t always lead to action. For some, data analytics and AI still feel out of reach due to perceived costs and daily time constraints to explore their potential. But AI in government could be key to driving measurable improvements, reducing strains on resources and giving more time to focus on mission goals.

As it turns out, the early stages of digital transformation in the public sector are yielding encouraging results. In a recent global research study, 81% of governments using GenAI have experienced operational cost savings.But government agencies are cautious, often being the first to be last. 

According to the Economist Impact report, 70% of those surveyed adopt new technologies only after proven success elsewhere, which can delay savings. 

While the challenge is complex, the successful path forward is incremental. Begin with high-impact, low-risk projects that deliver quick wins. These early successes build stakeholder confidence and fetch immediate gains in productivity and cost savings. From there, phased, scalable projects will lay the groundwork for enduring data transformation and sustained cost-efficiency.   

Creating the next AI leaders

AI is poised to improve government operations while freeing civil servants from repetitive tasks, allowing them to focus on more meaningful work. For instance, an employee spending six hours a day entering data across legacy AI systems can now rely on AI to read scanned forms, update systems and handle additional functions. The shift empowers staff to become strategic contributors, analyzing data, spotting trends, and guiding residents through public services.  

The Economist Impact report confirms growing civil servant trust that AI in government can deliver significant benefits: 

• 52% believe AI will have a significant or critical impact on improving productivity within their organization over the next three years.
• 58% recognize that digital transformation is necessary.
• 60% say that organizational change will be key to realizing significant gains.

As support for AI grows, some employees may still resist change, often out of concern for job impact or lack of input. Early, ongoing engagement cultivates trust and affirms that technologies align with your organization’s needs and strategic goals. 

To avoid frustration and build confidence, ensure that change management includes dedicated support for employees through training and coaching. Advancements in technology like machine learning and natural language processing make the strongest impact when employees understand how to use the tools. Comprehensive training includes guidance on using policy and privacy rules to protect data, knowing how to minimize bias, and using AI to improve accuracy.

Measuring successful AI in government

Getting into AI a little later has its perks. As other industries have experimented, failed, learned and progressed in their efforts with AI adoption, public sector leaders can benefit from the insights and best practices gleaned from these experiences.

And, as AI expands among government entities, capabilities are becoming more powerful. And AI leaders are becoming more adept at deployment. While future moves will vary based on each agency’s unique context, there will be shared practices among successful AI adopters that will play a central role across the government agencies. These include:

• A focus on AI ethics. While AI in government becomes more embedded in daily operations, global debates about biased data, accountability and societal impacts have intensified. Unlike other sectors, public AI must ensure fair outcomes for every single citizen. We prioritize responsible innovation by centering human judgement, grounding our approach in proven strategies, and upholding transparency and equity. Our cross-sector partnerships foster AI that is explainable, secure and designed to serve with integrity.
• Choosing your AI tools. Analytics drives both learning and automation in AI, but not every government task calls for an AI agent or even AI at all. Focus first on identifying the processes that need enhancement, then apply AI solutions tailored to those needs. Whether opting for traditional models suited to structured decision-making or exploring large language models (LLMs), mission clarity will enable capabilities that are aligned with outcomes and governance priorities. 
• Dynamic AI oversight. Organizations that have been more successful with AI tend to have more rigorous oversight processes in place. What begins with trustworthy AI and AI governance continues into every phase of development and deployment. Trust requires continuous oversight with real-time monitoring of performance metrics, fairness indicators and model drift. Feedback mechanisms also enable continuous refinement. 

What’s next for AI in government?

For governments, success with AI relies on accountability, inclusivity, transparency and especially human agency. See how the SAS approach to trustworthy AI integrates fairness and oversight into every phase of the data analytics and AI process, empowering you to address complex challenges with confidence and integrity.