Save timeImprove quality
AI compliance monitoring
Continuous monitoring of regulatory changes, internal policy adherence and audit readiness — so your compliance team leads strategy instead of chasing paperw…
AI for the public sector: use cases, governance and how to start
Governments are rethinking service delivery through intelligence — moving from reactive to proactive, from standardized to citizen-centered.
In short
Public administrations use AI first where demand outpaces staff: citizen assistants that answer from official sources, help with forms and procedures, document processing and knowledge tools for case workers. The hard part is not the model but accountability: every answer traceable to an official source, a person responsible for every decision that affects rights, and controls that can be explained to an auditor. Decisions on benefits, access to services or public safety carry the strictest obligations under the EU AI Act.
Better services. Smarter governments.
- Predictive maintenance for urban infrastructure
- AI-driven traffic and mobility optimization
- Citizen service automation and chatbots
- Smart resource allocation and budgeting
- Public safety analytics and crime prediction
- Environmental monitoring and energy planning
Solution plays
View all solutions Save timeImprove quality
AI governance, risk & control
Build the controls, audit trails and risk framework that turn AI deployments from a liability into a governed, defensible part of your operations.
Save timeImprove quality
AI HR assistant
Handle employee queries, automate routine HR processes and free your HR team to focus on the work that actually requires human judgement.
Save timeImprove quality
AI knowledge transfer
Capture, structure and make accessible the expertise that lives in your people's heads — before it walks out the door.
Save timeImprove quality
AI patient & citizen assistant
An AI assistant designed for regulated environments — healthcare, public services and financial services — that handles sensitive queries with the accuracy, compliance and empathy they require.
Save timeImprove quality
AI research assistant
An AI research layer that searches, synthesises and structures information from internal and external sources — so your teams spend time on judgement, not on…
Save timeImprove quality
AI risk intelligence
AI that aggregates, monitors and prioritises risk signals across your organisation — so your risk function acts on evidence, not on periodic reports.
Reduce costSave time
Legacy modernization with AI co-pilots
AI-assisted refactoring on COBOL, mainframe, and aging stacks—governance gates, regression tests, and audit trail from day one.
The European angle: EU AI Act and sector rules
The EU AI Act (Regulation (EU) 2024/1689) treats several public-sector uses as high-risk under Annex III: assessing eligibility for essential public assistance benefits and services, and granting, reducing or revoking them; and uses in law enforcement, migration, asylum and border control, the administration of justice and democratic processes. Public bodies that deploy these systems must carry out a fundamental rights impact assessment before use and register the use in the EU database. Annex III obligations apply from December 2027, after the Digital Omnibus on AI entered into force on 27 July 2026; AI literacy (Article 4) and Article 50 transparency already apply. Check the consolidated text on EUR-Lex or the AI Act Service Desk.
Some practices are banned outright, and those bans already apply: social scoring of people, and predicting the risk that a person will commit a crime based solely on profiling or personality traits. “Public safety analytics” projects need to be checked against these limits from the outset. At the other end, a citizen assistant that answers from official content has mainly transparency duties, as long as it does not decide on anyone’s rights.
AI in administration also has to meet rules that already exist: the GDPR, administrative law on reasoned decisions, accessibility requirements for public websites and apps, and public procurement rules, which shape how AI systems and services are specified and contracted. In Spain, AESIA is the national AI supervisory authority. This is practical guidance, not legal advice.
How to start
- Build an inventory of AI uses, including the ones already happening informally, and classify each: prohibited, high-risk, transparency only or minimal risk.
- Start with a citizen or staff assistant that answers only from official, up-to-date sources, cites them and hands over to a person with full context when it cannot answer.
- Define governance before the pilot: who owns each system, which decisions always need a person, what is logged and how a citizen can challenge an outcome.
- Write the requirements into the procurement: documentation, logging, data location, model portability and the provider’s cooperation duties under the AI Act.
- Pilot with a limited service or group, measure answer quality, escalation and accessibility, and widen only after legal and service owners sign off.
Success stories in this sector
- Regional public administration: citizen services and responsible AILeading regional government—unifying digital services, interoperability, and governance so citizen-facing channels and back-office systems evolve together without losing accountability.
- Regional competitiveness: innovation policy and AI adoption at scaleLeading autonomous-region administration—aligning innovation funding, SME support, and sector programmes with a practical AI adoption path from pilots to portfolio governance.
Thinkia products that fit
Decisions you will face
Frequently asked questions
Is a citizen chatbot high-risk under the EU AI Act?
Usually not, if it only informs and guides from official content. It must make clear that the person is talking to AI. It becomes high-risk when it assesses eligibility for benefits or services or influences decisions on someone’s rights. Keep the boundary explicit in the design and in the documentation.
What is a fundamental rights impact assessment?
An assessment that public bodies, and private entities providing public services, must carry out before deploying certain high-risk AI systems. It describes the process, the people affected, the risks to their rights, the human oversight measures and what happens if those risks materialise. In practice it fits naturally alongside the data protection impact assessment.
Can a public administration use commercial AI models?
Yes, but the contract matters. Specify where data is processed, how long it is kept, whether it is used to train models, what logs you receive and how you can switch provider. Open-source models on your own or sovereign infrastructure are an option when data sensitivity or independence call for it.
How do we avoid isolated pilots that never scale?
By choosing use cases with a measurable outcome, building on shared components such as identity, knowledge sources and logging, and setting up governance that can be reused across departments. Thinkia has worked with regional governments on exactly this: roadmaps from policy intent to live services, with proportionate controls.
What about accessibility and languages?
They are requirements, not extras. Public digital services must be accessible, and a citizen assistant should adapt language, reading level and channel without losing accuracy. That should be tested in the pilot, not left for later.
Further reading
Key terms
Want a solution mapped to your context?
Talk to an AI Expert