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

Generative AI matters for Spain's public sector because it turns time‑consuming, text‑heavy chores into fast, repeatable workflows that shorten waits for benefits, speed up permits, and free public servants for higher‑value work: EsadeEcPol estimates up to 67% of public‑administration workers could see a significant share of their tasks enhanced by AI, delivering roughly €7 billion a year in value EsadeEcPol report on AI in Spain's public sector.

Homegrown assets like ALIA and the MareNostrum supercomputer make Spanish and co‑official language NLP more reliable at scale (Analysis of Spain's AI landscape (March 2025)), and real pilots - ISSA answering two million queries in its first month - show what's possible.

Getting this right needs cloud readiness, reskilling, and clear governance in sandboxes, plus practical prompt and workflow skills; short applied courses such as Nucamp AI Essentials for Work bootcamp (15-week) teach those tools civil teams can use immediately.

Bootcamp	AI Essentials for Work
Length	15 Weeks
Focus	AI tools, prompt writing, workplace applications
Cost (early bird)	$3,582
Register	Nucamp AI Essentials for Work registration | AI Essentials for Work syllabus

The reason to use AI in the public sector is to automate red-tape tasks, not to replace human input.

Selection of the top‑10 prompts and use cases began with an evidence‑first filter: priority went to tasks that EsadeEcPol's task‑based model flags as high‑impact (67% of public‑sector workers could see 10–50% of their tasks enhanced by generative AI), especially those that cut paperwork, speed citizen interactions, detect procurement anomalies, support grant decisions and feed policy evidence into briefs EsadeEcPol report on AI in Spain's public sector.

Each candidate use case was then screened for alignment with national strategy levers - scalability on local and regional platforms, compatibility with ALIA language models and MareNostrum‑grade compute, and fit for regulated pilot environments such as regulatory sandboxes and a GovTech Lab - following the public‑sector priorities mapped by AI Watch and Spain's AI strategy AI Watch summary of Spain's public‑sector AI strategy.

Practicality mattered: prompts had to produce verifiable outputs that reduce citizen wait times or free several hours a week for frontline staff (the vivid test: could the prompt turn an overflowing town‑hall inbox into minutes‑per‑reply?).

Finally, every entry was judged on governance readiness - data quality, privacy, and clear human‑in‑the‑loop controls - so pilots can move from sandbox to scale without surprise.

“This strategy not only strengthens our technological infrastructure and innovation capacities, but also ensures that the development of Artificial Intelligence in our country is carried out under the highest standards of sustainability and ethics.” - José Luis Escrivá, Ministry of Digital Transformation and Public Service

Citizen-facing virtual assistants promise the sort of practical, low‑friction service that citizens actually notice: an account with a personalised tracker, deadline notifications and an always‑on chat so case status isn't a mystery but a short checklist - features demonstrated by private services that guide residency and visa applicants through document checks, fingerprint steps and final uploads (MigRun: Virtual Assistance for Spain).

International good‑practice reviews from the ISSA underline why that matters for social‑security and benefits bodies: integrated service portals and automatic workflows have already delivered millions of faster actions in other systems, shortening decision time and reducing backlogs (ISSA Good Practices database).

For Spanish administrations the takeaway is tangible - combine secure personal trackers, clear human review points, and measured automation so a clogged inbox becomes a predictable timeline with a ping rather than a phone call, freeing staff for complex judgment tasks while citizens follow real‑time case status.

Feature	Example / Note
Personal account & tracker	Document status, deadlines and notifications (MigRun)
Unlimited citizen chat	Continuous guidance and document review (MigRun)
Automated workflows	Millions of automatic actions reported in ISSA good practices

A Ministry of Justice Document Summariser for Spain can turn sprawling case bundles and multilingual reports into concise, auditable briefings by combining the “chunk‑and‑synthesise” content design techniques tested in Justice Digital with secure LLMs and local language models: the GOV.UK experiment shows how segmenting hundreds of reports (about half a million words in one dataset) makes accurate summarisation tractable (GOV.UK: Combining AI and content design to extract insights from service assessment reports), while the UK Ministry of Justice's action plan endorses transcription, translation and redaction pilots as core productivity wins (UK Ministry of Justice: AI Action Plan for Justice).

Practical pilots should pair automated extraction (IBM's OLGA-style case categorisation is a useful model) with human review and language‑aware models for Spanish and co‑official languages to avoid loss of legal nuance and preserve evidentiary rigour (Spanish-language models such as ALIA and local NLP tools).

The payoff is concrete: faster, cited summaries for judges and clerks so large document stacks become short, reliable briefings that spotlight the three items that matter most to a hearing.

Feature	Evidence / Note
Automated summarisation	Chunking + LLM workflow from Justice Digital experiment
Transcription & translation pilots	MOJ plans and pilots for transcripts and AI translation
Case categorisation & metadata extraction	IBM OLGA example of automated tagging and resolution support
Quality bar for transcripts	Accuracy target cited (~99.5%) for court transcripts in MoJ exploration

“AI should support, not substitute, human judgment.”

The ALIA Legal Redactor should make legal‑text anonymisation practical for Spanish courts and administrations by applying recognised pseudonymisation patterns - replace direct identifiers, keep the mapping separate and locked down, and pair automated redaction with human review and DPIAs so outputs remain defensible in court; the UK ICO's guidance on pseudonymisation is a useful legal roadmap for those controls (UK ICO pseudonymisation guidance (UK GDPR)).

Technically, the redactor can choose from robust approaches - tokenisation, hashing or encryption - to balance utility and risk, and should test against re‑identification scenarios such as the “motivated intruder” test and attacker models described in data‑masking literature (Data masking, tokenisation, and hashing overview).

To preserve legal value, ALIA's extraction layer must retain auditable metadata and permissions so pseudonymised records can be re‑linked only under strict, logged conditions, and use Spanish and co‑official language NLP so anonymised briefs still surface the three points judges care about; see local tooling and models developed for Spain (Spanish-language legal NLP models and local AI tooling for Spain).

The payoff is clear: a ream of case files becomes manageable data for analytics without exposing identities - if key management, access controls and continuous testing are non‑negotiable.

“…processing of personal data in such a manner that the personal data can no longer be attributed to a specific data subject without the use of additional information…”

GobTech Lab's Procurement Tender Analyzer would stitch together proven analytics so Spanish procurement teams can spot collusion, split POs and pricing outliers before contracts are signed: network and link‑analysis models - frequently cited for detecting fraudulent behaviour in procurement - reveal supplier clusters and hidden relationships (EPJ Data Science study on procurement fraud), anomaly detection watches for sudden deviations from baseline spend and “stair‑stepping” invoice patterns, and text‑mining parses RFQs and bids for missing compliance clauses (SAS guide to preventing procurement fraud).

Paired with agentic review workflows that automate RFQ ingestion, scoring and evidence summaries, the system can turn weeks of manual review into hours and surface a single suspicious bid that's three standard deviations from the norm - an instant that often cracks a fraud case (Datagrid analysis of AI for RFQ evaluation).

The practical payoff for Spanish administrations is immediate: tranches of bids become auditable scorecards and flagged dossiers that investigators can triage, not drown in.

Technique	What it finds / delivers
Network / Link analysis	Supplier collusion, shared contacts and hidden relationships
Anomaly detection	Outlier pricing, split POs, sudden spend deviations
Text mining & NLP	Compliance gaps, missing clauses, structured bid data
AI agents / RFQ automation	Faster ingestion, objective scoring and summarised evidence

An AGE Grants Decision Support system that scores applications could mirror real Spanish practice where funders already use AI to screen proposals, for example the La Caixa Foundation's pilot that filters out weaker biomedical submissions before human review - an approach that trims the pile so reviewers focus on the most promising dossiers rather than wading through dozens of marginal forms (La Caixa Foundation AI screening pilot for Spanish research grants).

But adopting scoring for public grants in Spain must be wrapped in the new governance fabric: Spain's AI strategy and sandboxes emphasise transparent, language-aware models and human oversight, while recent national proposals create stiff penalties and a supervisory agency (AESIA) to enforce ethical controls (Spain national AI strategy and sandboxes (AI Watch report); Spain proposed AI bill and oversight agency AESIA).

The practical sweet spot is clear - use AI to shortlist and surface evidence, but keep final scoring and exceptions in human hands so the system does not silently exclude the one unconventional project that later becomes a breakthrough.

“does not relieve the author from taking full and sole authorship responsibilities with regard to acknowledgements, plagiarism and the practice of good scientific and professional conduct.”

An EsadeEcPol Policy Evidence Synthesiser turns sprawling research into actionable, auditable policy briefs by combining open‑science synthesis methods with pragmatic curation: synthesise the literature, surface the limited set of robust findings policymakers need, and attach clear provenance so each claim links back to sources (see the open‑science review

Open science at the science–policy interface

for synthesis techniques).

Building on OSI's call for flexible, evidence‑based open policies, the tool prioritises usability over ideology and adapts outputs to Spain's multilingual context by integrating Spanish and co‑official language models such as ALIA to preserve nuance across Catalan, Basque and Galician.

The result is a short, sourced brief that surfaces three concrete policy options with linked evidence - less debate over facts, more focus on implementation - so ministers can move from confusion to a clear next step in a single meeting.

Condition for “open” research	Percent citing as often/always important
Published to best practices (reviewed, indexed, archived)	88%
Free to read	83%
Transparent methods and sources	80%
Data included	73%

IA4Covid could give Spanish public‑health teams an early, actionable heads‑up by combining anonymised mobility traces with smart time‑series classifiers so outbreaks are spotted and localised sooner, not after hospital corridors fill up; the EPJ Data Science method demonstrates how geolocated movement patterns can be analysed to determine outbreak origins (finding disease outbreak locations from human mobility data), while a recent PLOS Computational Biology framework shows how feature‑based time‑series classification forecasts outbreaks and non‑outbreaks for faster detection (early detection using feature‑based time‑series classification).

For Spain that means analytics that can turn national and regional mobility signals into neighbourhood‑level alerts and clear, auditable flags for contact tracing teams - think of it as tracing the first domino in a stadium‑sized chain reaction - so interventions can target the right place at the right time while preserving individual privacy through anonymisation and careful, local governance.

Technique	What it delivers
Mobility‑based outbreak localisation (EPJ)	Determine outbreak origins from geolocated movement data
Feature‑based time‑series classification (PLOS)	Early detection of outbreaks vs. non‑outbreaks for warning systems

GobTech Lab's Internal Productivity Assistant tackles the daily grind of overflowing public‑sector inboxes by combining AI triage, context‑aware drafting and secure deployment so Spanish teams can spend less time filing and more on decisions: operate an inbox assistant that classifies and prioritises messages, suggests or auto‑composes policy‑aligned replies and populates department templates while keeping every action auditable and human‑reviewable - capabilities demonstrated in secure deployments like Legion's Secure Process Automation that run on segregated government clouds and integrate with Outlook, Teams and SharePoint (Legion Secure Process Automation for government inbox automation).

Practical triage lowers time spent on routine mail (AI tools can learn from historical threads to prioritise urgency and suggest smart replies; see an comprehensive AI email triage guide) and should be rolled out with the guarded approach recommended for public agencies - zero‑trust controls, strong encryption, human oversight, and cost monitoring from day one (AWS best practices for generative AI implementation in the public sector) - so an overwhelmed Monday morning can become a short, auditable triage session rather than a lost day.

Feature	Evidence / Benefit
Inbox triage on secure networks	Context‑aware auto‑composition; secure deployments and integrations (Legion)
Automatic prioritisation & smart replies	AI classification reduces time on routine emails; improves response times (Mailmodo)
Proven productivity wins (case example)	Large deployments report dramatic reductions in manual filing and email volume (Sedna / Viterra case)

“I've long believed that AI won't just enhance the way we live, but transform it fundamentally. AI is placing tools of unprecedented power, flexibility, and even personalization into everyone's hands, requiring little more than natural language to operate.” - Silvio Savarese, Chief Scientist, Salesforce

Barcelona BSC‑CNS Urban Mobility Optimiser applies the same sensor‑and‑data‑driven playbook transforming cities worldwide: stitch real‑time feeds from cameras, IoT detectors and transit apps into edge/cloud models that run adaptive signal control, eco‑routing and automated incident detection so congestion and idling fall rather than climb.

Local deployments start small - one corridor or a busy junction - and scale when adaptive timings and predictive analytics prove they shave intersection idle time and clear queues, turning a single optimized light into a visible drop in tailpipe plumes along an avenue.

This approach builds on

“smart city” advances in sensors and analytics

(Smart City innovations in urban mobility and smart city sensor analytics) and the evidence base for AI traffic systems that cut emissions and delays (AI‑integrated smart traffic systems for carbon‑neutral cities research).

For Spain, pairing these controls with Spanish and co‑official language tooling - so data products and public dashboards speak Catalan, Basque and Galician via local models like ALIA - keeps solutions equitable and easier to adopt across municipalities (Spanish‑language models such as ALIA for government deployment in Spain).

City / Region	Reported impact
Beijing	~25% CO2 reduction during peak hours
Singapore	22% reduction in intersection delays
Europe (bus optimisations)	~12% improved fuel efficiency

A focused ALIA Clinical Assistant for a heart‑failure pilot in Spain would pair Spanish‑language models and local NLP with clear operational steps so frontline teams can transform tedious note‑sorting into fast, auditable handoffs: by following an operational checklist for Spanish public sector clinical teams (Operational checklist for Spanish public sector clinical teams) and building on ALIA's language work (Spanish-language clinical AI models ALIA and local NLP for Spain), a pilot can surface the handful of patients whose notes need immediate clinician review while routing routine summaries for administrative follow‑up; this approach preserves clinician judgment (and local language nuance) while helping staff adapt roles rather than replace them, echoing the broader workforce guidance on shifting tasks in government services (Workforce guidance on adapting government roles for AI in Spain).

Imagine a ward where the single critical chart stands out in a short, sourced brief - an instant that saves review time and keeps care both fast and defensible.

Spain's path from promising pilots to reliable public‑service AI is practical and stepwise: begin with right‑sized, risk‑mitigated pilots that target high‑impact, low‑risk tasks and include clear KPIs so outcomes are visible from day one (see the Cloud Security Alliance guide on AI pilot programs and adoption for a tested playbook Cloud Security Alliance guide on AI pilot programs and adoption); pair those pilots with data‑readiness and modest IT modernisation so models aren't fed poor inputs (Avero Advisors' checklist highlights why data and systems matter for scale); bake in risk‑appropriate governance, auditability and public transparency so residents keep trust while agencies gain speed (examples and principles from Maximus' review of state AI pilots are useful Maximus review of AI in state government pilots and operational impact); and invest in workforce reskilling and plain‑language prompt skills so staff move with the tech rather than be displaced - practical short courses such as the Nucamp Nucamp AI Essentials for Work 15-week bootcamp registration teach the hands‑on prompt and workflow skills civil teams need now.

Keep language awareness in scope (use local models like ALIA for Catalan, Basque and Galician) and treat each pilot as a measured experiment whose learnings become the blueprint for scaling: that disciplined loop - pilot, measure, govern, train, scale - is the shortest route to reliable, citizen‑facing impact without surprise.

Next step	Why / source
Run right‑sized pilots	Risk‑mitigated insights; test before scale (CSA)
Define KPIs & measure	Make outcomes visible and reportable (CSA, Maximus)
Fix data & modernise infra	Essential for accuracy and scaling (Avero Advisors)
Governance & transparency	Match oversight to risk; preserve public trust (Maximus, PayIt)
Reskill staff	Enable co‑working with AI; practical training options available (Nucamp)

“There are certain processes - like [program or benefit] eligibility determination - where generative AI should not be making the decision. That needs to be done by humans, with AI supporting the process.” - Doug Robinson, NASCIO (quoted in Maximus)