Artificial Intelligence is rapidly redefining how societies operate, from healthcare to mobility, from public safety to social services. For Europe – and particularly Italy – AI represents both an extraordinary opportunity and a complex transformation challenge. Beyond a good chatbots usage.

 Unlike the private sector, public administrations must guarantee fairness, transparency, inclusivity, and accountability in every decision. This makes the introduction of AI not just a technological upgrade, but an institutional shift.

Below are the key challenges Italy and Europe must address to build a mature, trustworthy, and citizen-centric AI-enabled public sector.

1. Governance, Legislation & Accountability

Transparency and Explainability in a European Legal Context

With the EU AI Act, European public administrations must ensure that algorithmic decisions – especially in high-risk domains such as education, welfare, employment, healthcare, public safety, and migratio – are:

• Explainable
• Traceable
• Auditable

In Italy, this intersects with the tradition of administrative transparency (Legge 241/1990) and with strong public expectations for accountability. Black-box decision-making is incompatible with European legal culture.

Algorithmic Fairness and Anti-Discrimination

Europe’s commitment to equality—formalized in the Charter of Fundamental Rights—means that biased AI is not just an ethical concern but a legal violation.
Cases in the Netherlands, the UK, and even municipal experiments in Italy reveal that biased data can lead to discriminatory outcomes in:

• welfare eligibility
• tax risk scoring
• predictive policing
• job placement and active labour policies

A fragmented data landscape increases this risk.

Responsibility and Liability

When AI supports or automates a public decision, who is formally responsible?
European jurisprudence tends to maintain human liability, but operationally, the boundaries between:

• civil servants
• system integrators
• technology vendors
• data owners

are not yet well defined.
A complex multi-layered governance (such as Stato–Regioni–Comuni), faces even more uncertainty.

2. Organisational & Cultural Barriers

Digital Maturity Gaps Across PA

Italy’s public administration suffers from unequal levels of digital maturity.
Pockets of excellence (INPS, Agenzia delle Entrate, some municipalities and regional health systems) coexist with offices still tied to:

• legacy systems
• paper workflows
• supplier lock-ins
• limited interoperability

AI cannot thrive where the basic digital layer is missing.

Skills Shortage and Talent Attraction

Europe already faces shortages of:

• data engineers
• data scientists
• ML specialists
• cybersecurity experts
• AI governance professionals

Italy struggles even more due to the lower attractiveness of public-sector salaries and the slow, rigid hiring processes that discourage young digital talent. This challenge is not uniquely Italian: even in the United States, where the tech job market is traditionally more dynamic, we’ve seen highly trained student coders resort to taking jobs in places like Chipotle just to enter the labor market—an example I discussed in a past LinkedIn post. What this shows, on both sides of the Atlantic, is that digital skills are abundant, but institutions are often too slow or too inflexible to absorb them. Europe, and especially Italy, must rethink how it recruits, nurtures, and rewards technical talent if it wants AI to truly transform the public sector.

The result is a structural dependency on external consultants, which risks reducing internal capacity and increasing strategic vulnerability.

Change Management and Trust in Technology

In many European and Italian public bodies, AI adoption is slowed by organisational culture:

• fear of automation replacing human roles
• mistrust of “opaque algorithms”
• rigid hierarchical structures
• lack of design-thinking and agile procedures

Successful AI deployment requires new models of human-machine collaboration and stronger internal communication.

3. Data Challenges: The Foundation of Everything

Fragmented Data and Limited Interoperability

Italy’s data is dispersed across:

• thousands of municipal systems
• regional healthcare silos
• ministerial databases
• legacy platforms
• varying standards and taxonomies

Despite efforts like SPID, ANPR, PagoPA, and PDND, real interoperability is still incomplete.
AI needs clean, standardized, connected datasets – a massive but essential challenge.

Privacy, GDPR, and Data Governance

Europe’s strong privacy framework (GDPR) is both a safeguard and a constraint.
Public bodies deal with highly sensitive information: health, income, education, social status, minors, migration.
The challenge is to enable innovation while:

• ensuring data minimisation
• managing consent and legal bases
• defining retention rules
• guaranteeing data sovereignty

Italy is under intensified scrutiny by the Garante Privacy, making experimentation more difficult unless governance is airtight.

4. Procurement and Operational Constraints

Rigid Procurement Models vs. Agile AI Development

European and Italian public procurement still relies heavily on:

• multi-year contracts
• upfront specifications
• waterfall project design
• lowest-price logic

AI projects require iterative, experimental, data-driven methods. Today’s procurement models often slow down innovation, create vendor lock-ins, and discourage emerging tech companies.

Infrastructure Fragmentation

Europe is not yet unified in cloud strategy.
Italy’s cloud ecosystem is divided between:

• national cloud initiatives
• regional data centers
• on-premises legacy solutions
• external hyperscalers

This lack of cohesion complicates AI scaling and cross-agency collaboration.

5. Risk, Security & Social Legitimacy

Cybersecurity and Critical Infrastructure

AI systems introduce new vulnerabilities:

• data poisoning
• prompt injection
• model inversion
• adversarial attacks
• leakage of confidential information

Given the rise in attacks on Italian hospitals, municipalities, and critical services, cybersecurity must accompany AI from day zero.

Citizen Trust and Social Acceptance

Public-sector AI directly influences rights, benefits, and obligations.
If citizens perceive AI as:

• unfair
• opaque
• intrusive
• or poorly governed

trust erodes rapidly.
Italy’s sceptical public opinion and Europe’s high expectations for fairness make trust-building essential.

6. Strategic Sovereignty & Dependence on Big Tech

Europe produces little foundational AI compared to the US and China.
Italy relies almost entirely on external platforms.
This creates long-term risks:

• dependency on foreign vendors
• exposure to geopolitical tensions
• reduced capacity to negotiate standards
• unpredictable long-term costs

The EU AI Act, European Data Strategy, and Gaia-X initiatives are attempts to regain strategic autonomy—but adoption in Italy is still uneven.

Conclusion: A European and Italian Path to Responsible AI

AI will not succeed in the public sector through technology alone. Its success requires:

• modern governance
• interoperable data
• agile procurement
• deep organisational change
• strong cybersecurity
• citizen engagement
• European digital sovereignty

Italy has already taken important steps—with ANPR, SPID, PDND, PagoPA, and national AI initiatives – but must accelerate the integration of AI with these foundational systems.

For Italy and Europe, the goal is clear: an AI-enabled public sector that is efficient, equitable, transparent, and deeply human-centred.

Francesco Iarlori is an innovation strategist, lecturer, and advisor working at the intersection of artificial intelligence, public administration, and digital transformation. With decades of experience across Europe and the United States – from telecoms to smart cities, from AI governance to public-sector modernization – he helps institutions understand how technology can create real, lasting public value. He wrote this article to highlight the structural challenges and opportunities Italy and Europe face as they integrate AI into public services, and to support policymakers, executives, and practitioners in making this transition with clarity, responsibility, and vision.