Articles, analysis and trends on artificial intelligence applied to the public sector
Hidden cost of processing grants: hours, errors and delays that consume internal resources and require measurement and optimization.
Practical guide to designing responsible training data flows: compliance, anonymization, traceability and operational controls.
Best practices to maintain continuity of citizen services during AI model updates in public entities.
Practical guide for city councils: how to respond to access, rectification and appeal requests regarding AI-supported decisions.
How to require and evaluate model cards and data sheets in tender documents: technical and legal requirements for municipalities.
How to turn inquiries, social platforms, and surveys into safe, compliant operational decisions.
How to document and communicate automated decisions: concrete templates and steps to comply with the GDPR, the EU AI Act and the ENS.
Practical guide to evaluate, deploy and maintain open-source LLMs in municipalities while meeting ENS, GDPR and data sovereignty requirements.
What to measure in municipal AI services: operational, quality, equity, compliance and cost KPIs, and how to implement them.
What to include in contracts with AI providers: ENS security, GDPR, EU AI Act, metrics, audit and exit plans.
Practical steps to prepare for, detect, and respond to incidents involving AI systems in municipalities, while complying with ENS, GDPR and the EU AI Act.
A practical guide to detecting model drift, setting metrics, governance and incident response for public AI models.
Practical guide to designing AI pilots in municipal governments: scope, legality, metrics and a 90-day scaling plan.
Practical checklist to ensure AI projects in government are accessible, inclusive, and compliant.
AI and GovTech trends that city councils should prioritize in 2026 and concrete steps to adopt them securely and in compliance.
How to translate AI ethical principles into concrete operational controls for municipalities and public entities.
Practical guide to using AI to simplify administrative processes: procedures, legal limits, and concrete steps for municipalities.
A practical guide to redesigning positions and processes with AI while complying with ENS, GDPR and public procurement rules.
Practical guide to designing citizen-centered AI public services: accessibility, transparency, and concrete metrics.
Practical guide to identifying, piloting and scaling automation of repetitive tasks in public organizations.
Practical guide to creating an AI business case for municipalities: metrics, regulatory compliance, and a cost/benefit template.
How to structure partnerships with the private sector to deploy public AI while meeting regulations and minimizing risk.
How to prepare and publish municipal open data for AI projects with security and compliance.
How to apply NLP techniques to review decrees, permits and grants with legal and security assurances.
How to decide between building, buying, or combining AI solutions in local government, with legal requirements and actionable steps.
How to adopt generative models in municipalities: use cases, operational controls, regulatory requirements and an implementation checklist.
How to assess whether your local authority is ready for AI projects and the concrete steps to take over 12 months.
Practical checklist to prepare municipalities and public entities for AI audits and transparency obligations.
How to design and implement predictive models to prioritize urban maintenance and social services using operational and governance criteria.
Practical framework for evaluating the return on investment of AI projects in municipalities and public entities.
Practical guide for municipalities to comply with ENS, GDPR and ensure sovereignty and security when deploying AI in the cloud.
Practical guide to deploying AI chatbots in municipalities: use cases, compliance (GDPR, ENS, EU AI Act), metrics and a deployment checklist.
How to integrate AI models with municipal legacy systems without disrupting services or compromising legal compliance.
A practical guide for municipalities on the obligations of the EU AI Act, system classification, risk management and concrete steps to achieve compliance.
How to implement OCR + NLP to automate registration, classification and routing of documents in municipal governments with legal and security guarantees.
Practical strategies for managing AI adoption in public administrations: pilots, training, compliance and impact measurement.
Practical guide to complying with the GDPR when deploying AI in public entities: DPIA, legal bases, contracts and technical measures.
Practical checklist to comply with the National Security Framework (RD 311/2022) when deploying AI in public administrations.
How artificial intelligence helps public administrations streamline tender preparation, verify documentation, and evaluate bids with greater rigor and transparency.
Before implementing artificial intelligence, public administrations need a clear governance framework. Key steps to move forward with legal certainty and organizational criteria.
Public grants management involves drafting award decrees, reviewing justifications, and document control. AI streamlines every phase without sacrificing rigor.
Municipal urban planning departments handle a growing volume of citizen queries. AI enables automatic urban planning reports from cadastral and regulatory data.