Top 10 AI Prompts and Use Cases and in the Government Industry in Portugal

Portugal's government is betting on AI to make public services faster, fairer and more data-driven: the national AI Portugal 2030 strategy pushes pilots, skills and a National Data Infrastructure while platforms like ePortugal's Sigma chatbot and the Azure OpenAI

Virtual Assistant

show how voice and natural language can guide citizens to services without a trip to an office; at the same time EU rules such as the AI Act and national overseers (CNPD, ANACOM) are tightening privacy, liability and transparency for high‑risk systems - especially in health and biometrics - creating a practical need for upskilling across ministries.

Read the legal roadmap in the Artificial Intelligence 2025 – Portugal guide and the strategy brief on AI Portugal 2030 to see why training matters; courses such as the AI Essentials for Work bootcamp syllabus teach prompt-writing, governance and hands-on AI skills that public servants will need to implement secure, explainable pilots at scale.

Bootcamp	Length	Early-bird Cost	Registration
AI Essentials for Work	15 Weeks	$3,582	Register for AI Essentials for Work (15 Weeks)

Selection of the top 10 prompts and use cases combined legal realism, sectoral priority and technical practicality: each candidate was scored for AIA/GDPR compliance and documentation needs (transparency, human oversight and risk management per the EU rules and CNPD expectations), alignment with national priorities under AI Portugal 2030 (education, health, justice and public services), demonstrable public value (e.g., citizen-facing gains like faster triage or simpler form filling), and feasibility on Portugal's existing infrastructure such as the HealthDataHub or national HPC resources; full legal and regulatory criteria draw on the consolidated Portugal practice guide on the AIA and supervisory roles Portugal Artificial Intelligence 2025 practice guide (Chambers) while strategy and upskilling priorities reference the national AI Portugal 2030 roadmap and its emphasis on human capital and living labs Portugal AI Strategy Report (AI Watch).

The result: prompts that are high-impact yet tractable under Portuguese procurement, data-governance and oversight constraints - a practical mix that favours explainable, auditable systems citizens can trust, not experimental

Criterion	Why it matters for Portugal
Regulatory fit (AIA/GDPR)	Ensures deployable prompts avoid high-risk non‑compliance and costly redesigns
Sector priority	Targets healthcare, education, justice & public services highlighted by AI Portugal 2030
Technical feasibility	Matches use cases to national infra (HealthDataHub, RNCA/Vision HPC)
Upskilling & governance	Favors use cases that public servants can audit, govern and scale

“black box” bets.

ePortugal's Sigma chatbot and the 2023

Virtual Assistant

show how natural‑language and voice interfaces - the latter built on the Azure OpenAI Service - can steer citizens to services on the portal without a trip to an office, simplifying routine interactions while keeping them traceable and auditable; the Chambers Artificial Intelligence 2025 guide explains Sigma's role on ePortugal and notes the Virtual Assistant's May 2023 launch using Azure OpenAI (Chambers guide: Artificial Intelligence 2025 – Portugal).

These deployments illustrate AI Portugal 2030's push to modernise public services, but they also underscore practical limits under GDPR, CNPD scrutiny and the EU AI Act - especially around transparency, data governance and biometric restrictions - which public servants must navigate when procuring and operating chatbots (AI Portugal 2030 public service modernisation and legal constraints).

The immediate takeaway for adopters: favour simple, explainable intents, document human oversight and invest in staff prompt‑writing and governance skills so citizens reap faster, fairer services they can trust.

Health‑data platforms in Portugal - think national HealthDataHub capabilities plugged into the EU's HealthData@EU fabric - promise real gains for analytics, research and clinical decision support by giving clinicians and researchers controlled, secure access to large, interoperable datasets; under the new European Health Data Space Regulation the route is clear but guarded: national Health Data Access Bodies (HDABs) issue permits, data is delivered in closed secure processing environments and only anonymised or justified pseudonymised extracts leave those sandboxes, which helps tools be clinically useful without exposing identities.

For Portuguese hospitals this can mean faster, evidence‑driven decision support and fewer duplicated tests (imagine avoiding a repeat CT for a patient who just arrived from another EU country), while policymakers get richer, auditable evidence for planning.

Practical caveats from EHDS workstreams include catalogue and data‑quality obligations for data holders, possible cost recovery fees, and a phased rollout that requires national readiness and upskilling; read the EU's EHDS Regulation for the legal framing and the impact report for policy implications to plan pilots and governance now.

EHDS milestone	Date
Entered into force	26 March 2025
Commission implementing acts due	March 2027
First priority data categories apply (primary & secondary use)	March 2029
Second group (images, labs, discharge reports)	March 2031

Portugal's INCoDe.2030 programme is the backbone of a practical national push to make adaptive learning and personalised education routine in schools and continuing training: the initiative extends ICT into early grades, funds teacher training and seals award-winning projects (like ubbu and TechNovation Girls) to scale classroom-first AI tools while keeping inclusion front‑and‑centre; pairing INCoDe.2030's education action lines with the AI Portugal 2030 pillars helps ministries prioritise explainable, curriculum‑aligned tutors and modular micro‑learning that fit local needs rather than ungoverned pilots (see the INCoDe.2030 roadmap for initiatives and the OECD summary of AI Portugal 2030).

A striking result from recent national upskilling pilots: the Rampa Digital programme reported that 91% of participants said their confidence applying new digital skills rose significantly, a concrete signal that AI‑enabled, personalised pathways can boost employability and classroom outcomes when coupled with clear governance and teacher support.

INCoDe.2030 priority	Relevance for adaptive learning
Inclusion	Ensures adaptive tools reach all regions and learners
Education	Integrates ICT and teacher training for personalised instruction
Qualification	Upskills adults for AI‑enhanced jobs
Specialisation	Develops advanced programmes and micro‑credentials
Research	Supports evidence and pilots for scalable adaptive systems

The Francisco Manuel dos Santos Foundation's policy paper maps where automation and AI will bite hardest in Portugal and offers a clear playbook for targeting reskilling: it pinpoints professions and regions most susceptible to change and stresses active labour policies and VET to steer transitions, since almost a third of jobs sit in “collapse” zones - think waiters, cashiers and textile machine operators - often held by lower‑qualified workers (only about 5.4% have higher education), making rapid, targeted retraining both urgent and feasible; the study's headline figures (and the national Digital 2030 push highlighted by Cedefop) show a mixed picture - 35.7% of employment is unlikely to be automated, 28.9% is highly vulnerable and 22.5% stands to benefit from digitalisation - so public programmes should prioritize portable digital, data and soft skills that help workers move from at‑risk roles into growing ones.

Read the FFMS policy paper for the full regional breakdown and Cedefop's note on Portugal's Digital 2030 ambitions for context.

Metric	Value
Employment unlikely to be automated	35.7%
Workforce highly vulnerable to automation/AI	28.9%
Employment likely to benefit from digitalisation	22.5%
Jobs in collapse (FFMS / press)	≈28.8–30%

For legal and administrative automation in Portugal - from public guides and citizen-facing form drafting to backend case triage - the UK Ministry of Justice offers a practical playbook worth borrowing: a co‑produced AI & Data Science Ethics Framework built with the Alan Turing Institute and an explicit

Scan, Pilot, Scale

AI Action Plan for Justice that pairs governance, transparency and workforce investment with concrete tools and pilots.

The MoJ's approach stresses five SAFE‑D principles (Sustainability, Accountability, Fairness, Explainability, Data responsibility), publishes use‑case records and insists on human oversight - measures that help make auto‑drafted forms and legal assistants auditable and defensible.

Concrete UK examples that resonate for Portugal include a Violence in Prisons Estimator tested under ethics review and a Splink‑based single‑identity project that reduced duplicate offender records, showing how explainable linkage can cut admin load while preserving rights.

Portuguese teams designing Legislation Studio workflows or citizen self‑service guides should prioritise documented governance, transparency (ATRS‑style records) and staff upskilling so automation simplifies access to justice without sacrificing fairness - see the MoJ ethics toolkit and AI Action Plan for Justice for templates and practical steps to adapt locally (MoJ AI & Data Science Ethics Framework, AI Action Plan for Justice).

For the GNR (Guarda Nacional Republicana) the next wave of AI is less about flashy robotics and more about smarter data and faster decisions: partnerships like OPPSCIENCE with A. SILVA LEAL bring SPECTRA's AI‑powered semantic search, entity resolution and multi‑dimensional “What, When, Where, Who” visualisations to Portuguese law enforcement, helping investigators fuse structured and unstructured records into a single, auditable view (OPPSCIENCE SPECTRA AI semantic search for Portuguese law enforcement); alongside academic work on web‑based decision support systems for crime‑hotspot forecasting and patrol‑route optimisation - using clustering, travel‑time matrices and multiple‑travelling‑salesman methods - these tools can suggest where to send patrols and how to minimise vehicle mileage while prioritising hotspots (Crime-prediction decision-support system study on hotspot forecasting and patrol-route optimisation).

Framing these capabilities under AI Portugal 2030 procurement and governance guidance ensures deployments are explainable, auditable and interoperable with national systems, so GNR can turn richer insights into faster, fairer response without losing public trust (AI Portugal 2030 procurement and governance guidance); a vivid payoff: investigators viewing a 4D timeline can spot links across time and space that used to live in dozens of separate files, surfacing leads hours - rather than days - sooner.

“The collaboration with OPPSCIENCE means that law enforcement institutions gain exponential investigative capability because cutting-edge technologies and ongoing research and development elevate criminal knowledge and analysis to levels never before achieved.”

Portugal Space's AI Moonshot Challenge turned space data and machine learning into a practical tool for ocean health when the SMART consortium - led by CERENA‑IST with partners from FEUP, CESAM, the Hydrographic Institute and MIT Portugal - won the first edition and €500,000 to build satellite‑driven, AI models that map plastic‑accumulation probability using Copernicus/Sentinel‑2 imagery, physics‑informed GANs and high‑resolution ocean models; the project pairs these large‑scale detections with in‑situ validation (autonomous marine vehicles) and a citizen‑facing SMART app so beachgoers can photograph debris and feed a European reference repository, a powerful civic science loop at national scale (see Portugal Space's AI Moonshot announcement and the SMART app page).

The stakes are clear: research cited by the project notes plastic concentration in the marine environment rose roughly tenfold in 15 years, so portable, auditable Earth‑observation tools can help authorities target cleanups and policy where it truly counts.

Winner	Prize	Data & Methods
SMART (CERENA‑IST consortium)	€500,000	Copernicus/Sentinel‑2 imagery, Physics‑Informed GANs, ocean models, in‑situ/autonomous vehicle validation

“The idea for this solution arose from the need to validate the plastic accumulations predicted by machine learning algorithms using in situ observations.”

For CUF and other Portuguese health providers, the UK's recent pilots offer a practical roadmap: symptom‑checkers and AI triage can safely steer patients away from unnecessary emergency visits, speed referrals and expand telemedicine while easing front‑line workload - the Tony Blair Institute estimates an AI navigation assistant could free up about 29 million GP appointments a year, a striking scale‑up opportunity for Portugal's systems to consider (Tony Blair Institute report: Preparing the NHS for the AI Era).

Peer‑reviewed work shows symptom checkers can reach acceptable diagnostic and triage accuracy in ED settings (JMIR mHealth peer-reviewed symptom-checker diagnostic accuracy study), and NHS trials of eConsult‑style AI triage underline the value of robust evaluation, safety monitoring and procurement.

Portuguese adopters should prioritise integration with records, clinician oversight, clear SaMD pathways and governance aligned to AI Portugal 2030 so pilots convert into sustained capacity gains and trust rather than transient experiments (AI Portugal 2030 guidance for government AI adoption in Portugal).

Commit to an AI Navigation Assistant for every citizen

Banco de Portugal and the CMVM are already turning AI from buzzword into concrete supervisory tools: the central bank's Alya platform automates document summarisation, email classification, audio/image processing and market‑sentiment flags, while suptech pilots now analyse draft consumer contracts to compress months of manual review into interactive dashboards - a model that makes procurement analytics, fraud detection and advertising‑compliance checks far more scalable.

These systems let supervisors scan ad campaigns, flag non‑compliant clauses and surface unusual market chatter so investigations focus on signals, not stacks of PDFs; read more on the Bank of Portugal's Alya AI platform and the suptech draft‑contract analyser for Portugal's market monitoring case study.

With EU rules like DORA and the AIA tightening documentation and human‑oversight requirements, Portuguese regulators (and firms bidding on public procurement) must bake in explainability, vendor SLAs and audit logs from day one - the CMVM's shift to embed AI in supervision (project Gaia and other analytics efforts) shows how governance needs to match ambition.

Metric	Value
Alya request classification accuracy	70%
Estimated staff‑time savings from suptech	8–16 months

“Alya could identify that Credit Suisse was at the top of news and research.”

Portugal's CNPD sits at the centre of government AI compliance: alongside ANACOM and a raft of designated market‑surveillance bodies, it will monitor how public agencies and vendors meet the EU Artificial Intelligence Act and existing GDPR duties, especially where biometric, health or cross‑border data are involved.

The AIA is being phased in (key literacy and prohibited‑practice rules from early 2025, further obligations for general‑purpose models through 2025–2027), so Portuguese teams must pair impact assessments, documented human oversight and robust procurement contracts with privacy‑by‑design measures to avoid steep sanctions; the Chambers practice guide explains the national enforcement role and sectoral list of competent authorities (Chambers Practice Guide: Portugal Artificial Intelligence 2025).

Practical implementation help is also emerging - EU and vendor toolkits stress AI literacy, FRIA-style evaluations and conformity workflows that map to CNPD expectations (Securiti report on EU AI Act implementation efforts and toolkits) - so teams should treat compliance as a project with clear deliverables (impact assessment, documentation, audit logs) rather than an afterthought; failing to do so risks the fines and market penalties the AIA prescribes.

For baseline data‑protection rules and CNPD contact guidance see Portugal's national GDPR overview (DLA Piper Portugal data protection laws overview).

AIA offence	Maximum penalty (Article 71–72)
Non‑compliance with prohibited AI practices	Up to €35 million or 7% of worldwide turnover
Non‑compliance by operators/notified bodies	Up to €15 million or 3% of worldwide turnover
Providers of general‑purpose AI models	Up to €15 million or 3% of worldwide turnover

Practical next steps for Portuguese public servants and beginners boil down to three linked priorities: train, pilot, and govern - starting with focused upskilling to meet AI Portugal 2030's human‑capital goals, use sandboxed living labs (LabX/InnoLabs) and the National Data Infrastructure to run small, explainable pilots, and bake impact assessments and transparent procurement clauses into every contract so services scale without surprise; the Portugal Digital Strategy's promise of

Portugal, where Digital Simplifies

is a useful north star for choosing projects that reduce citizen friction.

Short courses that teach prompt writing, governance and hands‑on tools speed that transition: see the AI Portugal 2030 roadmap for priorities, the Portugal Digital Strategy for simplification goals, and the AI Essentials for Work bootcamp syllabus to start building practical skills and governance literacy before larger rollouts (AI Portugal 2030 roadmap, Portugal Digital Strategy, AI Essentials for Work bootcamp syllabus), so Portugal's pilots become repeatable public services rather than one‑off experiments.

Bootcamp	Length	Early‑bird Cost	Registration
AI Essentials for Work	15 Weeks	$3,582	Register for AI Essentials for Work