Gartner Predicts at Least 80% of Governments Will Deploy AI Agents to Automate Routine Decision....
At least 80% of governments will deploy AI agents to automate routine decision-making, enhancing efficiency
and service delivery by 2028, according to Gartner, Inc., a business and
technology insights company.
“Government CIOs are under growing pressure to
embed AI into decision-making capabilities rapidly and responsibly,”
said Daniel Nieto, Sr. Director Analyst at
Gartner. “The rise of multimodal AI, alongside conversational and agentic
systems, has expanded what public organisations can automate, understand, and
anticipate.”
However, one of the most persistent barriers to
AI value in government is fragmentation.
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,” said Nieto.
Governance Must Shift From Models to Decisions
As AI transitions from experimentation to being
deeply embedded in decision-making, governance approaches must also evolve.
Traditionally, AI governance has centered on managing
models, data, and algorithms.
However, decision intelligence (DI) shifts this
focus toward 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 Gartner survey found that 39% of respondents
cited improved service and citizen satisfaction as primary reasons to invest in
building citizen trust. 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
judgment, particularly in high-stakes or rights-impacting contexts,” said
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. XAI and HITL designs
are foundational to public-sector DI. These mechanisms ensure that 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.
Citizen Experience Becomes a Qualitative Measure
of AI Value
While efficiency remains important, citizen
trust in the 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,” said 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 that could reshape how government digital services
are delivered.”
DI enables governments to redesign decision
flows across citizen-facing services, shifting from reactive, process-driven
interactions to proactive and personalised engagement. This not only improves
consistency and reduces delays but also enhances perceived fairness and builds
public trust, even as direct contact with government staff becomes less
frequent.
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