{"id":3415,"date":"2026-09-28T17:03:40","date_gmt":"2026-09-28T15:03:40","guid":{"rendered":"https:\/\/reciproc-it.com\/?p=3415"},"modified":"2026-09-28T17:03:42","modified_gmt":"2026-09-28T15:03:42","slug":"un-agent-ia-composant-technique-actif-a-securiser-ou-risque-a-part-entiere","status":"publish","type":"post","link":"https:\/\/reciproc-it.com\/en\/2026\/09\/28\/un-agent-ia-composant-technique-actif-a-securiser-ou-risque-a-part-entiere\/","title":{"rendered":"An AI agent: a technical component, an asset to protect, or a risk in its own right?"},"content":{"rendered":"
\"\"<\/figure>\n\n\n\n

Artificial Intelligence<\/strong> is now entering a new phase in the business world.<\/p>\n\n\n\n

Following conversational assistants and content-generation tools, we are now seeing the emergence \nof AI agents capable of interacting with applications, accessing data, using tools, and, in some \ncases, performing actions on behalf of a user or an organization.<\/p>\n\n\n\n

It spread quickly!<\/p>\n\n\n\n

These AI agents, often accessible through Open-source solutions or SaaS tools already integrated \ninto our work environments, are gradually making their way into companies, sometimes faster than \nthe governance processes needed to regulate their use.<\/p>\n\n\n\n

A SAP LeanIX study published in 2026<\/strong> indicates that of the companies<\/strong> surveyed are already deploying AI agents, while 40% are in the testing phase and 14% plan to adopt them.<\/strong><\/p>\n\n\n\n

https:\/\/www.leanix.net\/en\/download\/agentic-ai-survey-2026<\/a><\/p>\n\n\n\n

In other words, 98% of the organizations surveyed are already engaged, to varying degrees, in \nadopting, testing, or planning for AI agents.<\/p>\n\n\n\n

We no longer work quite the same way. We have instant access to results, summaries, and \nproposals. The time spent searching for information or producing an initial deliverable has been \nsignificantly reduced, an acceleration that leaves almost no time for doubt, debate, consultation, or \nvalidation.<\/strong> Sometimes we get an answer before we\u2019ve even really taken the time to formulate all the \nquestions<\/p>\n\n\n\n

All of this, in my view, is disruptive, especially in the field of risk management! The agent is no longer \nmerely a tool at the user\u2019s disposal but is gradually becoming a component that acts within the \nsystem on the user\u2019s behalf.<\/p>\n\n\n\n

This acceleration is obviously a tremendous opportunity.<\/strong> But it must also lead us to ask a \nfundamental question: what role does this \u201cnew player\u201d actually play in an existing information \nsystem,<\/strong>whether it is mature, secure, or still not fully under control?<\/p>\n\n\n\n

So this isn\u2019t a question of whether this technological advancement is useful or not; it\u2019s a question of \nhow to integrate it into a system that\u2019s already up and running. How do we actually integrate these \nnew \u201cdigital colleagues\u201d into our systems, processes, and value chains?<\/strong><\/p>\n\n\n\n

Today, there is a lot of talk about \u201cAI risk,\u201d data breaches, the risk of false positives, poor decision\nmaking, manipulation, the risk of compromise, and, finally, regulatory risk. All of these risks exist; \nthey are, in fact, consequences associated with the use of these agents.<\/p>\n\n\n\n

But if we try to take a step back and view this tool as an integral part of the company\u2019s value chain,<\/strong>or even as an asset to be protected, our way of thinking may change.<\/p>\n\n\n\n

This technological component has certain capabilities: It can access data, interact with \napplications, call services, use tools,<\/strong> generate information, or trigger certain actions.<\/p>\n\n\n\n

It is, therefore, the combination of all these capabilities with its environment, its access points, its \ndependencies, the threats to which it is exposed, and the potential consequences of its use that \ncontributes to the overall risk..<\/strong><\/p>\n\n\n\n

An isolated AI agent is therefore not, in and of itself, a risk. The risk arises from the relationship \nbetween its capabilities, its environment, its uses, and the potential consequences of its actions.<\/strong><\/p>\n\n\n\n

This distinction seems important to me when seeking to anticipate and manage the risks associated \nwith the use of AI agents in the workplace.<\/p>\n\n\n\n

So, how should we approach risk analysis from this perspective?<\/strong><\/p>\n\n\n\n

Ultimately, the question becomes quite simple: What approach should we take to analyze the risks \nassociated with integrating an AI agent into a project or information system?<\/p>\n\n\n\n

As with any new project aimed at improving or deploying an information system, , a risk analysis must \nbe conducted during the project\u2019s design phase,<\/strong>not after its deployment. From an integration \nperspective, the AI agent can therefore be considered a component of the system<\/strong> . It is therefore \nimportant to analyze its integration into the overall system as well as the risk scenarios that could \narise from it.<\/p>\n\n\n\n

It is not necessarily a matter of analyzing \u201cthe AI agent as a risk.\u201d Rather, it is a matter of analyzing \nthe risks associated with integrating this new \u201cAI agent\u201d component, examining its capabilities, its \naccess privileges, its interactions, and its role within the system.<\/p>\n\n\n\n

Perhaps that is where the real change lies. The issue, therefore, is not necessarily to create a new \ncategory called \u201cAI risk.\u201d<\/strong><\/p>\n\n\n\n

Perhaps the real change lies in having to adapt the way we describe and characterize the \ncomponents of an information system:<\/p>\n\n\n\n