If 2025 felt chaotic for any government and artificial intelligence, 2026 may be even more demanding. AI use in the public sector is growing fast, but trust and governance are struggling to keep up.
A recent IDC Data and AI Impact Report, commissioned by SAS, shows government agencies now use generative AI as much as, or more than, most industries. They are also early adopters of traditional and agentic AI. Yet spending on trustworthy AI tools, oversight systems and skills remains behind that of the private sector.
This gap sets up a key question for 2026. Can governments scale artificial intelligence responsibly while managing public trust, regulation and real-world risks?
One clear shift is cost pressure. Large, complex consulting projects are starting to lose appeal. Governments want tools that help staff analyse data faster and automate routine work, without years of custom development. The focus is moving toward empowering civil servants, not replacing them.
Prioritizing Speed, Control, and Public Value in 2026
At the same time, AI is moving out of pilot mode. More agencies are deploying systems that act with limited human input. That raises the stakes for transparency. Decisions made by AI will need to be explainable, auditable and easy for non-technical leaders to understand.
Governance will also take centre stage. As AI laws tighten in Europe and spread globally, many countries are exploring “sovereign AI” models. These aim to keep sensitive data and computing power within national borders, reshaping how governments buy and deploy technology.
Citizen services are another frontier. AI-powered virtual assistants are expected to handle more complex queries, across languages, cutting wait times and improving access. Behind the scenes, synthetic data may help agencies train AI systems without breaching privacy or sovereignty rules.
The workforce impact will be uneven. AI will capture institutional knowledge and support new roles, but it will also force large-scale reskilling. Fraud, tax and public health agencies, meanwhile, will rely more on real-time analysis to keep pace with smarter criminals and unlock insights from long-neglected data.
