The Complete Guide to Using AI in the Government Industry in Tunisia in 2025

AI matters for government in Tunisia in 2025 because a national plan - the Tunisia AI Roadmap - has moved the country from strategy to practical action, setting goals like raising AI awareness, building skills, and establishing cloud and HPC infrastructure to accelerate public‑sector innovation (Tunisia AI Roadmap (OECD policy dashboard)).

Real-world enablers are already appearing: Novation City's new AI innovation hub provides DGX infrastructure and developer training to help ministries and startups prototype services, while the nationwide digital identity system E‑Houwiya is simplifying secure citizen authentication for e‑government platforms - both pieces that turn policy into deployable services (Novation City AI innovation hub - NVIDIA blog, E‑Houwiya national digital identity system - Tunisia digital ID overview).

For public servants and civil‑service teams looking to adopt AI responsibly, practical training such as the AI Essentials for Work bootcamp can bridge policy intent and on‑the‑ground capability (AI Essentials for Work bootcamp syllabus - Nucamp), making pilot projects more likely to scale into everyday services.

“Novation City has launched several key AI initiatives to strengthen the ecosystem, with NVIDIA's support being instrumental in empowering AI startups and advancing AI skills,” said Anas Rochdi, chief innovation officer at Novation City.

The National AI push in Tunisia is not an isolated tech memo but a practical extension of the country's broader digital ambition: the Tunisia National Digital Strategy 2021–2025 foregrounds digitization as an engine for economic and social development, insisting on a paperless administration, wider high‑speed broadband, stronger cybersecurity, and targeted measures to leverage data and emerging technologies (Tunisia National Digital Strategy 2021–2025).

Complementing that, the Tunisia AI Roadmap (2021–2025) crystallizes implementation priorities - awareness and skills, cloud and HPC infrastructure, open data and pilot projects - and names the Ministry of Industry, the National Research and Innovation Programme and the High Authority for Public Procurement as key stewards for turning strategy into deployable public‑sector services (Tunisia AI Roadmap 2021–2025 (OECD)).

Recent announcements also signal a refreshed digital transformation and AI strategy slated for 2025 that aims to fold AI into health, education, environment and transport while seeding incubators and local support for startups - a pragmatic mix of capacity building, sectoral pilots and infrastructure that makes the promise of smarter, faster public services feel suddenly attainable (Tunisia digital transformation and AI strategy 2025 - WeAreTech).

One vivid takeaway: the roadmap treats “data + broadband + skills” as a single assembly line that must run together if AI pilots are to stop being experiments and start being everyday services.

“Whoever becomes the leader in this sphere [AI] will become the ruler of the world.”

Tunisia's legal environment for AI in 2025 is a careful balancing act between established privacy protections and recent, wide‑ranging digital‑security laws that create both guardrails and uncertainty for public‑sector AI projects: there is no dedicated AI law yet, so AI work must navigate the country's longstanding personal‑data regime (Law no.

2004‑63) and supervision by the National Authority for Protection of Personal Data (INPDP), alongside newer measures such as Decree‑Law no. 2022‑54 and Decree‑Law no.

2023‑17 that touch directly on cybercrime, surveillance, cloud hosting and mandatory audits. The practical consequence is stark - Decree‑Law 54's Article 24 allows penalties up to TND 50,000 and five years' imprisonment for “false information,” and provisions require telecoms to retain identity, traffic and geolocation data for two years - a legal backdrop that human‑rights groups say risks chilling speech and complicating responsible data use for AI systems (see analyses of the decree and calls for repeal).

At the same time, Tunisia's data framework and the INPDP remain important assets for any government AI rollout, and the 2023 cloud/cybersecurity rules introduce auditing and classification requirements that will shape procurement and hosting choices for public AI services.

In short: Tunisia offers credible data‑protection building blocks, but the sweep of cybercrime powers and surveillance rules makes clear legal mapping and strong governance essential before scaling AI across health, transport or social services; without that, a single social‑media post could trigger the same heavy penalties that human‑rights monitors warn are being used against critics, creating a chilling detail that every government AI planner must factor into risk assessments.

For legal background and advocacy perspectives, see the country data‑protection overview and the ICJ analysis of Decree‑Law 54.

“The Decree provides the Tunisian authorities with wide, unchecked powers and tools to crackdown on the right to freedom of expression and to ...”

Tunisia's AI ecosystem in 2025 is held together by a mix of public‑private platforms, research labs and international partnerships that aim to turn strategy into usable services: the Tunisian AI Society (TAIS) explicitly frames itself as a public‑private bridge linking government authorities, the commercial sector, higher‑education and research institutions to

build cooperation

and scale projects with societal impact Tunisian AI Society partnerships page; national hubs and university centres - including teams at Institut Pasteur de Tunis and University of Tunis El Manar noted in regional reviews - anchor the research side while innovation clusters and incubators provide prototyping and startup support, so ideas can move from lab notebooks to pilot dashboards relatively quickly Cambridge MENA AI governance survey (Data & Policy).

Continental frameworks and funding guidance from AUDA‑NEPAD reinforce those linkages, encouraging tech transfers and international R&D partnerships that help Tunisian hubs access talent, compute and markets AUDA‑NEPAD white paper on AI for Africa.

The practical upshot: Tunisia's ecosystem is less a single institution and more a coordinated constellation - a detail that matters because it means government teams can plug into existing labs, incubators and continental networks instead of building everything from scratch.

Tunisia's talent pipeline for public‑sector AI is increasingly practical: local providers like NobleProg offer hands‑on, instructor‑led courses (online live or onsite on customer premises) and curated learning pathways that teach Python for data analysis, machine learning, data science and sectoral subjects such as

AI for Government and Public Sector,

so civil‑service teams can move from theory to working prototypes (NobleProg Tunisia artificial intelligence training courses, NobleProg Tunisia learning pathways and eLearning).

That training links directly to real government use cases: a Nucamp example shows a syndromic surveillance engine that detects clusters of illness from clinic logs and social media in Arabic and French - the kind of applied project that turns statistical models into faster public‑health alerts and clearer operational decisions (syndromic surveillance use case for Tunisia government (Arabic & French)).

Reskilling programs can also focus on data governance and procurement reform - critical because automating tasks (auditors and tax inspectors among the roles often cited as most impacted) requires fresh skills in model oversight, data ethics and interoperable systems rather than simple task replacement; imagine a tax auditor using analytics to flag anomalies in minutes instead of combing files for days, a vivid shift that captures why practical, locally delivered training matters now.

Tunisia's public sector is already piloting practical, high‑impact AI applications that reflect the country's regional strengths: Tunis remains the main hub for research and startups, while Sfax and Monastir specialise in farm‑to‑field agriculture monitoring and industrial/textile automation respectively, supported by a modest but growing ecosystem (AI investments: $14M; 88 publications in 2025) - see the regional hub and stats overview at AI World Tunisia AI hubs and statistics.

National plans now push those pilots toward core public services: the 2025 digital and AI strategy explicitly targets health, education, environment and transport, signalling government pilots in everything from predictive maintenance for transport fleets to adaptive learning tools for schools (WeAreTech coverage of Tunisia's 2025 digital and AI strategy).

Concrete use cases already on the table include syndromic surveillance that spots illness clusters from clinic logs and Arabic/French social media, fraud detection and automated compliance checks for procurement, and precision irrigation analytics for agricultural districts - small, targeted systems meant to augment human oversight rather than replace it (read the syndromic surveillance example for Tunisia).

These choices reflect a cautious, infrastructure‑first mindset: scale is being built through hubs, universities and incubators so pilots can graduate into reliable, accountable public services rather than one‑off experiments.

“I believe AI is going to permeate the whole of society and [will not] just [be used by] the experts and, therefore, we need to figure out an appropriate pedagogy to teach AI to everyone,” Jaoua told University World News.

Private companies and public bodies in Tunisia are increasingly collaborating to turn AI pilots into market-ready services, with the 2025 International Forum of L'Économiste Maghrébin spotlighting pharma and cloud‑based startups as prime partners for government modernization - CEOs from Saydalid and Neapolis Pharma described AI wins ranging from smarter inventory to cutting order processing from an hour to 30 seconds, and a newly introduced B2B matchmaking platform famously “condensed months of prospecting into a single day,” a vivid sign that partnerships can accelerate procurement and R&D ties (26th Forum of L'Économiste Maghrébin - Tunisia and AI).

Those industry linkages were echoed by multi‑stakeholder policy work: The Future Society's workshops with GIZ and ministries helped shape Tunisia's National AI Strategy by bringing startups, academia and regulators into the same roadmap discussions, creating practical entry points for public procurement and talent pipelines (Stakeholder consultation workshops for Tunisia's National AI Strategy - The Future Society).

For health and pharmaceuticals specifically, the WHO case study on Tunisia's local production ecosystem shows where R&D partnerships, technology transfer and regulatory alignment can unlock value - together these elements point to a pragmatic, sectoral approach where public‑private partnerships reduce time‑to‑value and strengthen domestic supply chains, provided legal and currency hurdles are addressed (WHO case study: Tunisia pharmaceutical ecosystem).

“There is no better response to global geopolitical upheavals than unity. And there is no time to waste if we want to open a new industrial chapter rooted in innovation and responsibility,” he said.

Tunisia's AI plans sit inside a global landscape where a few superpowers still set the tempo: the Stanford HAI AI Index shows the U.S. dominating model production (40 notable models in 2024) and private investment ($109.1 billion in 2024), while China - though behind in sheer model count (15) - has rapidly closed performance gaps and focused on cost‑effective scaling, and Europe has leaned into regulatory and ethics leadership (AI Act and privacy‑first approaches) (Stanford HAI AI Index 2025 report, Regional AI model comparison 2025 - USA, Europe, China strengths).

For Tunisian policymakers the practical takeaway is familiar: full sovereign AI stacks are expensive and often lock countries into foreign supply chains, so picking a realistic niche - learning from the syndromic‑surveillance pilot that stitches clinic logs and Arabic/French social media into faster health alerts - can deliver outsized public value without trying to race for every layer of the stack (Tunisian syndromic surveillance AI use case).

The global picture - U.S. performance+funding, China's efficiency, Europe's regulatory pull - means Tunisia can best accelerate impact by partnering smartly for compute, adopting clear procurement and data rules, and concentrating scarce talent on high‑value public services rather than chasing broad technical self‑sufficiency; think of it as choosing one well‑stocked harbour rather than building an entire merchant fleet.

“For most states, the smarter play is to find a niche in the supply chain where they can insert themselves,” he said.

Predictive policing abroad offers a cautionary tale Tunisia cannot ignore: algorithms trained on historical arrest and stop‑and‑search data can mirror and magnify existing biases, turning a labelled “hotspot” into a self‑fulfilling cycle of increased patrols, stops and community mistrust rather than safer streets - an ethical pitfall highlighted by the West Midlands review and reporting in The Guardian on predictive tools and by academic analyses that show how place‑ and person‑based systems disproportionately target marginalised groups (The Guardian: ethics committee warns predictive policing could entrench bias, USC Viterbi Center analysis of predictive policing pitfalls).

For Tunisian planners, the practical lessons are clear and concrete: insist on transparent data pipelines and independent oversight before any deployment; treat models as decision‑support, not infallible truth; and build community‑centred feedback and bias‑correction mechanisms so that dynamic, qualitative inputs can counter “dirty data” feedback loops identified in international studies.

Where law and procurement already constrain hosting and surveillance choices, embedding public scrutiny, clear redress paths and routine impact assessments will be the difference between a useful situational tool and a system that hardens inequality - a vivid reminder that technical accuracy alone does not guarantee justice (UK Parliamentary Office of Science & Technology report: AI in policing and security).

“It's labelled a crime hotspot. So, when the police enter the area, they're in the mindset of ‘we're in a dangerous community – the people here are dangerous.' It doesn't matter if they're young people, they're still ‘dangerous' and therefore ‘we can police them violently' and they do police them violently.”

For Tunisian public servants new to AI, a practical roadmap is short, specific and repeatable: pick one high‑value pilot (health surveillance or waterborne‑pathogen dashboards are ready examples), pair it with clear data governance and open‑data practices, and double down on hands‑on training so teams can operationalise models rather than just read reports.

Tunisia already has a strong foundation - ranked second in the Africa 2025 AI Talent Readiness Index - so capacity exists to staff these pilots (Invest in Tunisia - Africa 2025 AI Talent Readiness Index (FIPA)), and the arrival of a public AI institute at the University of Tunis promises more local, accredited training pathways (University World News - University of Tunis public AI institute).

Tactical next steps: start with a narrowly scoped, audited pilot that uses existing datasets (open data hackathons are a quick way to surface civic datasets), require regular impact and bias checks, and build a short training sprint for every pilot team - courses like the Nucamp AI Essentials for Work bootcamp turn policy talk into usable skills in weeks, not years.

A vivid test: if a small dashboard can turn routine wastewater samples into a coloured risk map for local health teams, that single, trustworthy output will convert sceptics faster than a thousand slides on theory.

“I believe AI is going to permeate the whole of society and [will not] just [be used by] the experts and, therefore, we need to figure out an appropriate pedagogy to teach AI to everyone.”