Behind the Curtain: How AI Agents Are Reshaping Security in Italy’s Public Sector

On the surface, Italy’s public administration seems to be leaping into the future: artificial intelligence agents, powered by large language models, now help draft documents, summarize legal acts, and even classify sensitive information. But as the digital dust settles, cybersecurity experts warn that this AI-driven revolution may be opening doors to new, little-understood threats - right at the heart of government.

Fast Facts

• AI agents and large language models are now embedded in Italian public administration processes.
• CERT-AgID is leading efforts to assess and mitigate the emerging security risks.
• Applications include summarizing legal documents, drafting correspondence, and automating classification tasks.
• Key concerns include data leakage, model bias, and the manipulation of AI-generated outputs.
• CERT-AgID provides replicable tools, baseline security standards, and specialized training for government entities.

AI’s Double-Edged Sword in Public Administration

In recent months, Italy’s public sector has quietly become the testing ground for a new class of AI-powered agents. These tools promise to transform bureaucratic drudgery: imagine AI summarizing court rulings in seconds, drafting ministerial memos, or sorting through thousands of documents at lightning speed. But while the productivity gains are tantalizing, the security implications are far from straightforward.

According to the national cyber emergency response team for the public sector, CERT-AgID, the integration of large language models (LLMs) into critical workflows marks a fundamental shift. The cybersecurity challenge is no longer just about defending against external hackers - it’s about rethinking the very architecture and risk governance of digital government itself.

One of the biggest concerns is the potential for sensitive data to “leak” through AI agents. If a language model is trained or prompted with confidential information, could it inadvertently reveal secrets in its outputs? There’s also the specter of model “bias” - the risk that AI may reinforce, or even amplify, human prejudices buried deep in public records or administrative routines. And as generative AI tools become more autonomous, the threat of manipulation - by insiders or malicious actors - grows ever more real.

CERT-AgID isn’t sitting idle. The agency has rolled out a suite of replicable security tools and baseline standards, aiming to make AI deployments in the public sector both scalable and secure. Specialized training programs are equipping civil servants to spot red flags in AI behavior. Meanwhile, new research is probing the dark corners of AI reasoning, including so-called “RAG” (retrieval-augmented generation) systems, and exploring concrete mitigations for bias and refusal to answer sensitive prompts.

The message from CERT-AgID is clear: AI in government isn’t plug-and-play. It demands a new era of cyber risk management - one where technology, policy, and human vigilance must evolve in step.

Conclusion: The Price of Progress

The march of AI into public administration is inevitable, but so are the risks that come with it. As Italy’s bureaucrats embrace digital agents, the real test will be whether the systems built to protect them can keep pace. In this new frontier, security is no longer just a technical challenge - it’s a matter of public trust.

WIKICROOK

• Large Language Model (LLM): A Large Language Model (LLM) is an AI trained to understand and generate human-like text, often used in chatbots, assistants, and content tools.
• Agent: An agent is a software program that acts independently to perform tasks, often collaborating with others to manage or secure computer systems.
• CERT: A CERT (Computer Emergency Response Team) is a specialized group that monitors, detects, and responds to cybersecurity incidents and threats.
• RAG (Retrieval: RAG (Retrieval-Augmented Generation) is an AI method that merges information retrieval with text generation to deliver more accurate, relevant answers.
• Bias: Bias is systematic prejudice in AI or cybersecurity systems, often reflecting the data or beliefs of developers, leading to unfair or inaccurate outcomes.