How AI Is Helping Government Companies in Belgium Cut Costs and Improve Efficiency

Belgium's 2025–2029 coalition roadmap makes AI a practical priority - calling for a data-driven public administration, administrative simplification across departments, living labs for new tech and stronger data sharing in health - so public servants now face both opportunity and urgency to learn usable AI skills.

The local training landscape is broad, from university masters to short courses and bootcamps that democratize AI for non‑specialists (see this roundup of the best AI training in Belgium), and the policy push highlights concrete priorities like smart camera pilots and a shared electronic patient record that demand skilled teams and clear governance.

For Belgian agencies aiming to cut costs and speed services, pragmatic, workplace-focused courses - such as the AI Essentials for Work syllabus - bridge policy and practice while preparing staff to supervise, not just adopt, AI systems.

administrative simplification

democratize AI

Belgium's public sector can turn policy momentum into real savings by pairing generative AI with pragmatic automation: a new study shows adopting GenAI across administrative processes could unlock an EUR 4 billion opportunity and complement 71% of public‑administration roles, meaning staff can move from paperwork to higher‑value work (see The AI opportunity for eGovernment in Belgium).

Practical RPA and intelligent‑OCR pilots already demonstrate the mechanics - in one UiPath/Hexaware engagement a Belgian pharmaceutical customer cleared its contract backlog and achieved a 71% reduction in processing effort, enabling 100% closures in a single day - a vivid example of how automation frees time for casework that needs human judgement.

At the same time, sector guidance stresses that efficiency gains must sit alongside trusted data practices and governance, so pilots focus first on low‑risk, high‑volume tasks such as document summarisation, form processing and chatbots (read Sogeti's look at generative AI for the public sector).

Start small, measure time‑to‑value, and scale the repeatable patterns that shave weeks off workflows while protecting citizen trust.

“RPA as a technology is uniquely suited for the public sector… it would release public agents from these tedious repetitive tasks and liberate their time so that they can better serve the public.” - Vargha Moayed, UiPath

Concrete AI use cases for Belgian government organisations are practical and immediate: automated document analysis can turn stacks of scanned disability claims and handwritten forms into searchable, structured records so caseworkers spend minutes - not hours - finding evidence; AI‑powered payment‑integrity systems flag suspicious health claims before payouts to reduce overpayments and speed recovery; public‑commentary analytics and specialised GenAI copilots help investigators and policy teams surface themes and leads from thousands of submissions; and digital twins - already used by Belgium's FPS Finance to model tax impacts - power flood prediction and real‑time emergency planning so responders see likely inundation zones before the rain stops.

These patterns map cleanly to Belgian priorities: faster citizen service, leaner audits and stronger fraud controls, all while keeping human oversight in the loop.

For concrete vendor examples and solution briefs, see SAS public sector AI overview, SAS Payment Integrity for Health Care solution brief, and a Nucamp case study on a procurement transparency search that uncovers high‑risk contracts and streamlines audits.

“SAS Viya, in conjunction with generative AI, is helping us have more informed, transformative conversations with regulators about topics of concern to their constituents. We can confidently provide data that shows what the public's concerns are and proactively communicate key messaging.”

Belgium already has measurable proof that thoughtful AI projects pay off: nearly half of managers (47%) report AI has delivered cost savings and higher profits, a striking signal that pilots can move beyond novelty into bottom‑line impact - see the EY European AI Barometer for Belgium (AI cost savings and profit lift study).

These savings sit alongside an organised policy and funding backdrop that channels public investment into practical rollout (the national AI strategy and regional programmes document concrete budgets and action lines), so vendors and agencies can pair grants with procurement to scale successful PoCs; the European Commission AI Watch report on federal and regional programmes and funding streams summarises these federal and regional programmes and funding streams.

Vendor outcomes are visible in sector pilots too: consultancies are using generative AI for procurement contract analysis to reveal savings and risk areas in hospital purchasing, a practical proof point for health and social‑services teams (see the BearingPoint AI-enabled procurement analysis case study).

Even as adoption grows, the landscape mixes optimism with caution - national plans estimate AI adoption at 20–25% and emphasise governance and reskilling - so finance teams should prioritise measurable, low‑risk wins (think document processing and procurement analytics) that deliver clear time and cost reductions while feeding the governance loop and workforce training pipeline.

Belgium's AI landscape is intentionally federated: a national strategy sketches three pillars - building technology and a responsible data strategy, expanding skills and public‑service optimisation, and ensuring ethical, secure deployment - while Flanders, Wallonia and Brussels run sizable regional programmes so local priorities turn into funded projects.

Flanders backs an annual EUR 32 million action plan (split EUR 15m for companies, EUR 12m for research and EUR 5m for training and ethics), Wallonia's DigitalWallonia4.ai sits inside an EUR 18 million‑per‑year regional push (with the ARIAC TRAIL research project funded at EUR 32 million for 2021–2026), and Brussels channels AI research via Innoviris (about EUR 22 million dedicated).

Policy instruments pair grants, research funding and innovation vouchers with open data and infrastructure: Data.gov.be and Statbel already expose thousands of datasets (roughly 15,000), giving public teams real raw material for pilots.

This multi‑level approach - summarised in the European Commission's Belgium AI strategy - is reinforced by the AI4Belgium coalition's emphasis on skills, trust and sandboxes to move experiments into practice, creating clear funding routes and measurable, low‑risk entry points for government agencies to start saving time and money with AI.

“Unknown is unloved. But due to a lack of knowledge about AI, Belgium may miss out on a lot of prosperity.”

Belgian public servants are eager but under‑supported: while roughly 71% of Belgians have tried AI tools and a striking three‑in‑four young consultants even use ChatGPT to draft job‑applications, only about 12% say AI already affects their day‑to‑day work and eight in ten report their employer doesn't offer enough training - a yawning gap between interest and workplace readiness that leaders must close (see the EY Belgium study for these country details).

Management frequently overestimates readiness - 56% of managers say training is adequate while shop‑floor staff disagree - so change management should pair hands‑on workshops and living‑lab experiments with clear governance and metrics to close the perception gap.

Investing in skills also has a clear return: PwC finds workers with AI skills can command a large wage premium, underlining that reskilling is both protective and value‑adding.

Start with short, role‑focused courses, supervised practice on low‑risk use cases and visible monitoring dashboards so employees see time saved; the memorable outcome to aim for is simple: staff who once spent days on forms can control AI assistants that cut that work to minutes, keeping human judgement front and centre while unlocking measurable efficiency.

“Those who do not engage with the topic of AI will fall behind.” - Adrian Ott, EY

Belgian deployments should treat governance as the first productivity tool: start with clear foundations (policy, a cross‑functional oversight committee and alignment with the EU AI Act deadlines that begin phasing in from August 2025–2026), then inventory and risk‑rank models so high‑stakes systems in health, finance or benefits get extra controls; this staged sequencing - define objectives, register models, embed explainability (think LIME/SHAP and model cards), set human‑in‑the‑loop thresholds, and deploy continuous monitoring - turns “black box” fears into auditable, repeatable practice, as explained in the Alation guide to explainable AI governance.

Practical Belgian priorities also require pairing governance with security: build AI controls into existing cybersecurity architecture so data breaches or model‑poisoning don't cascade, a point underscored by Crowe guidance on cybersecurity and AI governance.

Don't overlook regulatory readiness and transparency for auditors and citizens - radar‑style explainability keeps teams defensible under scrutiny and prevents a single opaque decision from stalling an investigation - an outcome RadarFirst warns is increasingly costly.

Start small on low‑risk, high‑volume pilots, document every step, and close the shadow‑AI gap so tools deliver efficiency without creating new legal or trust liabilities.

Practical roadmaps start with small, measurable wins: prioritise the low‑risk, high‑volume tasks that Implement Consulting Group flags as the quickest path to value (their study estimates an EUR 4 billion opportunity and that 71% of public‑administration roles can be complemented by generative AI, with 20% of potential tied to low‑risk use cases), then build the data foundations and governance that let those pilots scale into production.

Pair a simple model inventory and cross‑functional oversight committee with role‑focused training and living‑lab pilots that document decisions end‑to‑end, use public datasets from the Belgian open data portal Data.gov.be and the Belgian statistics office Statbel to reduce data‑collection delays, and feed early results into regional funding routes and innovation hubs so successful PoCs attract scaling grants.

Test compliance and technical safety inside formal regulatory sandboxes and TEF/EDIH facilities before broad rollout - the EU sandbox timetable (Member States must have national sandboxes by 2 August 2026) gives a clear deadline for safe experimentation.

The goal is tangible: shave days or weeks of casework down to minutes while keeping humans in the loop and auditors able to trace every decision.

“With rising citizen demands and stretched resources, public sector organizations recognize the ways in which AI can help them do more with less. However, the ability to deploy Gen AI and agentic AI depends on having rock‑solid data foundations.” - Marc Reinhardt, Public Sector Global Industry Leader at Capgemini

Belgian public servants closing the loop on AI should follow a clear, practical checklist: start with a light‑touch model inventory and low‑risk pilots that use public datasets from Data.gov.be and Statbel to prove time‑to‑value, pair each pilot with cross‑functional governance aligned to the national AI strategy (which maps federal and regional actions), and tap regional funding streams in Flanders, Wallonia and Brussels to scale what works; the European Commission's Belgium AI strategy offers an operational overview to match pilots with policy.

Culture and supplier partnerships matter as much as technology - external vendors can speed delivery while teams build in explainability, audits and employee training so gains stick.

For upskilling, role‑focused, workplace courses that teach prompts and supervised practice (see the AI Essentials for Work syllabus) turn interest into measurable productivity: the objective is simple and tangible - shave days of paperwork down to minutes without losing human judgement.

“Artificial intelligence offers the public sector the chance to transform how it serves citizens and enhance the experience of employees.” - Jonathan Birdwell, Head of Policy & Insights at Economist Impact