Gartner Reveals Top Technologies Shaping Government AI Adoption

Sovereign AI and AI agents are expected to shape public sector adoption of AI within the next two to five years, according to Gartner. Both have reached the Peak of Inflated Expectations on the 2025 Gartner Hype Cycle for Government Services. Gartner Hype Cycles provide a graphic representation of the maturity and adoption of technologies and applications, and how they are potentially relevant to solving real business problems and exploiting new opportunities. Gartner Hype Cycle methodology gives a view of how a technology or application will evolve over time, providing a sound source of insight to manage its deployment within the context of specific business goals. “Public sector leaders face mounting pressure to meet rising citizen expectations, navigate geopolitical uncertainty and do more with less resources,” said Dean Lacheca, VP Analyst at Gartner. “AI agents can address these challenges, but success will depend on bridging the gap between innovation ambitions and broader government priorities to ensure investments strengthen services, trust and resilience.” Among the innovations Gartner has identified as having high potential for government organizations, prompt engineering is expected to reach mainstream adoption within the next two to five years and machine customers within five to 10 years (see Figure 1).

Sovereign AI Sovereign AI refers to the efforts of nation states to invest in and progress their own development and use of AI to achieve their unique sovereign objectives. It enhances government operations through automation, modernizes processes to improve employee experience and accelerates citizen engagement. Gartner predicts by 2028, 65% of governments worldwide will introduce some technological sovereignty requirements to improve independence and protect from extraterritorial regulatory interference. Sovereign AI aims to maximize AI value while reducing associated risks, especially for sovereign states that collaborate to achieve common goals. AI Agents AI agents are autonomous or semiautonomous software entities that use AI techniques to perceive, make decisions, take actions and achieve goals in their digital or physical environments. They can help governments enhance service delivery, from processing citizen applications against policies and interpreting legislations, to automating routine tasks. Gartner predicts by 2029, 60% of government agencies globally will leverage AI agents to automate over half of the citizen transactional interactions, up from less than 10% in 2025. “Government leaders must incorporate AI agents into strategic planning by first identifying where they can deliver the most value,” said Lacheca. “Then run targeted pilots to manage expectations and address concerns from within the organization and from citizens. This should be followed by a clear roadmap to ensure initiatives progress beyond the pilot phase.” Prompt Engineering Prompt engineering involves providing text or image inputs to GenAI models to guide and constrain their responses, with well-structured prompts significantly enhancing response quality, performance and reliability. Governments can maximize returns on AI productivity tools by fostering AI literacy in their organizations by investing in context-specific prompt engineering skills and creating reusable prompt libraries to support effective prompt development. “Governments are investing in AI solutions that work best when users create clear context-specific prompts,” said Lacheca. “They shouldn’t invest in AI solutions if they’re not willing to invest in the development of strong prompt engineering capabilities within their organizations.” Machine Customers Machine customers are nonhuman economic actors that purchase goods or services on behalf of people or organizations. Gartner predicts three billion B2B internet-connected machines can act as customers today, growing to eight billion by 2030. Governments will need the ability to authenticate, provide services and regulate machine customers. For example, the proposed electric vehicle road use tax in Australia could be administered by the vehicle reporting operations directly to the government. “Government leaders need to identify where adoption of machine customers by citizens and industries will require the reimagination of regulatory enforcement and service delivery,” said Lacheca. “Existing government service delivery models will be disrupted, creating ethical, legal and accountability challenges. Governments can’t afford to be caught unprepared for the rise of machine customers.”