At least 80% of governments will deploy artificial intelligence (AI) agents to automate routine decision-making, enhancing efficiency and service delivery by 2028.
This is according to market research firm Gartner, which highlights a growing shift toward digital governance, where AI-powered systems will increasingly handle repetitive administrative tasks, such as processing applications, managing public records and responding to citizen queries.
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“Government CIOs [chief information officers] are under growing pressure to embed AI into decision-making capabilities rapidly and responsibly,” says Daniel Nieto, senior director analyst at Gartner. “The rise of multimodal AI, alongside conversational and agentic systems, has expanded what public organisations can automate, understand and anticipate.”
The Gartner report comes as South Africa is moving to embed AI into public administration, with early use cases emerging across service delivery, disaster response and internal operations, even as full-scale deployment of autonomous “AI agents” remains some years away.
The country’s National AI Policy Framework, released in 2024, has set the direction for adoption, with a comprehensive national policy expected by 2027.
Implementation is likely to follow from 2027 onwards, positioning the country for a more structured and regulated rollout of advanced AI systems across departments.
While South Africa has yet to deploy AI agents at scale, government and research initiatives indicate that agent-like systems are already taking shape.
Global use cases
Globally, governments are rapidly deploying AI agents to automate public services and internal operations, shifting from simple chatbots to systems that can execute tasks and coordinate workflows.
In the US, federal and city agencies are using AI agents to handle citizen queries, draft documents and manage call centres, while in China, autonomous systems are being integrated into administrative processes and urban management.
European governments are piloting AI-driven tools in policing and public service delivery, and in emerging markets, agentic platforms are being used to improve disaster response, financial inclusion and digital identity systems.
However, Gartner notes that fragmentation is one of the most persistent barriers to AI value in government.
According to a Gartner survey of 138 respondents from government organisations worldwide between July and September 2025, 41% of respondents cited siloed strategies and 31% cited legacy systems as key challenges to adopting and implementing digital solutions.
“Technology modernisation alone has not resolved these issues,” says Nieto.
The market analyst firm says as AI transitions from experimentation to being deeply embedded in decision-making, governance approaches must also evolve. It points out that traditionally, AI governance has centred on managing models, data and algorithms.
However, it states that decision intelligence (DI) shifts this focus towards the governance of decisions themselves; for example, on how they are designed, executed, monitored and audited. This shift in governance is especially critical in government, where public legitimacy relies on transparency and fairness, the firm explains.
Measurable impact
The Gartner survey found that 39% of respondents cited improved service and citizen satisfaction as primary reasons to invest in building citizen trust.
The firm notes that DI offers a structural foundation for operationalising this trust by making decision pathways explicit and auditable.
“By governing decisions, rather than just isolated AI components, governments can better balance automation with human judgement, particularly in high-stakes or rights-impacting contexts,” says Nieto. “Regulated industries and governments cannot rely on opaque ‘black box’ systems for consequential decisions. DI elevates explainability from a technical requirement to a governance imperative.”
Because of the need for transparency in decision-making, Gartner predicts that by 2029, 70% of government agencies will require explainable AI (XAI) and human-in-the-loop (HITL) mechanisms for all automated decisions that impact citizen service delivery.
Gartner explains that XAI and HITL designs are foundational to public-sector DI. These mechanisms ensure decision logic can be inspected, explained and challenged. Because of XAI and HITL, humans also retain authority over exceptions, appeals and high-risk cases, and accountability is preserved even as automation increases, it adds.
While efficiency remains important, Gartner says citizen trust in government’s ability to provide effective services is becoming a key driver of digital transformation. Fifty percent of government respondents cited improved citizen experience as one of their top three priorities.
“As AI and decision intelligence increasingly automate and streamline service delivery, the traditional notion of 'citizen experience’ evolves,” says Nieto.
“When citizens receive what they need from the government automatically, direct interactions may decrease, making trust in the system’s reliability, fairness and transparency even more critical. Because trust is so imperative in these situations, the predictive capacity to anticipate potential needs could reshape how government digital services are delivered.”
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