AI works for governments: A digital sprinters report

The opportunity presented by artificial intelligence (AI) is particularly profound for governments in emerging markets. Here demographic momentum, rapid digital adoption, and the absence of legacy constraints converge to create a unique position, enabling these markets to leapfrog traditional development pathways — if emerging market government leaders act decisively and strategically.

Building on this foundation, this report provides, for the first time, a quantification of AI’s public-sector-specific economic potential in emerging markets. These gains are grounded in dynamic modeling that quantifies both direct productivity improvements and the wider spillovers generated by government AI adoption.

AI can help deliver value for governments through three main pathways.

• Government efficiency and fiscal health: Improving how resources are raised, allocated and spent; reducing fraud leakage, and duplication; and strengthening long-term fiscal sustainability.
  
• Public good and service delivery: Enhancing the reach, quality and equity of public services in areas such as health, education, infrastructure and citizen engagement, while building public trust and institutional resilience.
  
• Economic growth and prosperity: Contributing directly to GDP growth, productivity and household income by driving efficiency, creating new jobs and leading by example private-sector adoption.

Our modeling suggests that widespread AI adoption within the public sector could increase public administration productivity by up to 3%. This would translate into an increase in real gross domestic product (GDP) by up to 4%, reduce government deficits by as much as 22% reduce unemployment by as much as 1.5 percentage points, and increase household incomes by 2% by 2035 when compared to the baseline scenario in 2035.   

These benefits of AI in the public sector are deeply interconnected and mutually reinforcing. A more capable tax authority funds better infrastructure. Streamlined licensing encourages small business growth. Improved agricultural extension services connect farmers with information and technology, which can boost rural incomes. Smarter healthcare systems keep citizens healthier and more productive. Together, AI-supported services can help create a more efficient, adaptive, equitable and trusted government—driving further downstream adoption and compounding benefits.

The realization of these benefits depends on several key enablers as outlined in Google’s AI Sprinters framework.

• A cloud-first, AI-forward policy: Reliable access to secure, scalable compute—whether through regional or global public cloud—accelerates time-to-value and encourages private investment.
• Skilling at scale: Broad-based literacy, implementer capacity and selective innovator pipelines should be developed in line with country realities.
• Modern data systems: High-quality, representative datasets and trusted data flows are essential for relevant, unbiased AI solutions.
• Enabling policies: A clear national strategy, central coordination and continuous feedback loops are necessary to track progress and build public trust.

Our research identified four archetypes of AI readiness. This report introduces a four archetype framework that benchmarks public sector AI readiness in emerging markets which can be used to guide the sequencing of investments and use cases. 

• Explorers: Countries early in AI adoption, typically without cloud first policies and a national AI strategy; need to focus on establishing these foundations and closing gaps in basic infrastructure and digital capabilities.
• Infra Ready: Countries with strong connectivity and cloud infrastructure but limited institutional readiness; well placed to deploy operations focused and agentic solutions while building cohesive AI governance and a cross ministry task force.
• Governance Ready: Countries with robust policy and oversight frameworks but infrastructure constraints; prioritize lightweight AI/agent deployments and leverage public cloud, while fostering private investment in infrastructure and talent.
• Leaders: Countries with national AI strategies with upskilling commitments, strong talent pools, and advanced digital infrastructure; positioned to scale high impact, cross agency (including multiagent) use cases under centralized governance.
  

This framework is a self assessment starting point—not a ranking—to help governments prioritize feasible use cases now while laying the groundwork for longer term scaling.

Effective implementation of these enablers has already shown that AI can be transformative across multiple government domains. Here are a few notable public sector use cases.

• Public finance and revenue: Fraud detection, smarter audits and procurement analytics strengthen fiscal stewardship.
• Citizen services and administration: Digital assistants, workflow automation and multilingual platforms improve efficiency and accessibility.
• Healthcare: AI-powered diagnostics and triage expand access and improve outcomes amid clinician shortages.
• Education: Adaptive learning and teacher augmentation address capacity gaps and promote equity.
• Infrastructure and mobility: Predictive maintenance and traffic optimization reduce costs and emissions.
• Environment and disaster management: Early-warning systems and geospatial analytics enhance resilience.
• Justice and security: AI-assisted evidence review and targeted analytics streamline case management.

To capture the full promise of AI, governments should treat it as a foundational capability across ministries—not as a collection of isolated pilots. Success requires quick wins to build momentum combined with investments in infrastructure, data and skills to enable more complex, cross-agency solutions. Progress should be tracked to sustain momentum and public trust.

Skills are critical for successful public-sector AI adoption. This report also sets out a practical framework to build AI capability at scale. The Google AI Sprinters Framework identifies three broad tiers of AI roles that governments should cultivate across their workforces:

• AI Learners: broad literacy for all civil servants (e.g., end users leaders),
• AI Implementers: practitioners who adapt tools to ministry workflows (e.g., business and product, governance), and
• AI Innovators: specialists who design, build, and evaluate systems (e.g., builders)
  

We outline a structured skills framework that spans core, technical and human-centric competencies across five distinct public personas—leaders, business and product, builders, governance, and end users. This framework enables governments to help align employees to critical roles, target proficiencies to baseline their workforce’s current state and design tailored talent strategies aligned with their AI needs.

Our framework provides a sequenced implementation plan that prioritizes literacy and implementer capacity first while developing innovator pipelines, and defines six actions to operationalize skills:

1. Develop a workforce AI skills taxonomy;
2. Assign proficiency targets by persona;
3. Baseline and validate skill proficiencies;
4. Build a talent action plan including hiring, redeployment, upskilling and accessing external experts;
5. Deploy right fit upskilling program including digital, experimental and on the job learning; 
6. Measure progress and refine talent and learning programs as required.
   

Together, this skills framework converts policy and infrastructure into sustained capability across the civil service. The path forward is clear. Governments in emerging markets have a unique window to harness AI for fiscal resilience, improved public services and inclusive growth. By acting strategically—anchoring efforts in robust policy, modern infrastructure and a skilled workforce—leaders can deliver transformative results for their citizens and economies.