{"id":152894,"date":"2026-07-10T07:32:42","date_gmt":"2026-07-10T06:32:42","guid":{"rendered":"https:\/\/univga.org\/controler-ia-avant-execution\/"},"modified":"2026-07-10T07:32:42","modified_gmt":"2026-07-10T06:32:42","slug":"ai-controller-before-execution","status":"publish","type":"post","link":"https:\/\/univga.org\/en\/controler-ia-avant-execution\/","title":{"rendered":"How to control AI before it acts on its own?"},"content":{"rendered":"<div class=\"veille-intro\">\n<p>Imagine that in a Libreville bank, an artificial intelligence assistant prepares a vendor transfer, checks the authorized ceiling, then requests the payment to be triggered. The file appears clean. Yet, one question blocks everything: who actually authorized the action, and what proof will the audit be able to read in three months?<\/p>\n<p>In a university, the same problem arises with scholarships. A tool sorts applications, identifies missing documents, suggests a priority, and prepares notifications. If the rule applied is wrong, or if personal data is used without a clear basis, the speed becomes a compliance risk.<\/p>\n<\/div>\n<aside class=\"veille-oneminute\">\n<p class=\"veille-oneminute__label\">What to remember in 1 minute<\/p>\n<ul>\n<li>On July 3, 2026, Singapore released a framework called SAFR to guide AI agents in finance.<\/li>\n<li>The central idea: control the action before execution, not just after an incident.<\/li>\n<li>Compliance must include identity, limits, human validation, and an audit log.<\/li>\n<li>For Francophone Africa, no autonomous AI without human proof or accountability.<\/li>\n<\/ul>\n<\/aside>\n<h2>What is it, concretely?<\/h2>\n<p>An artificial intelligence agent (AI agent) is not just a program that answers a question: it can prepare an action, such as classifying a file, producing a report, issuing an alert, or triggering an operation. The Safeguards for Agentic Finance at Runtime (SAFR) framework, published with the Monetary Authority of Singapore, proposes placing a control between the AI agent and the business system. Before the action, the organization verifies who is acting, what is authorized, which rule applies, if a human needs to validate, and what record will be kept. The key point is simple: AI can speed up work, but responsible decision-making remains organized, controlled, and auditable.<\/p>\n<h2>Concrete case: what to do and what not to do<\/h2>\n<aside class=\"veille-case-study\">\n<p class=\"veille-case-study__intro\">Hypothetical Case Study: Omar Bongo University in Libreville wants to reduce processing times for scholarships and social aid. The department in question receives numerous applications, along with supporting documents, social criteria, payment histories, and personal data. The temptation is strong: to entrust an AI agent with sorting applications, detecting missing documents, recommending priorities, and drafting correspondence.<\/p>\n<p class=\"veille-case-study__intro\">The problem is not the use of the tool itself. What is lacking, if we go too fast, are written rules, action limits, human validation for sensitive cases, a record of decisions, and auditable evidence for internal audit. Without this, a gain in productivity can become a legal, social, and reputational risk.<\/p>\n<div class=\"veille-case-study__grid\">\n<div class=\"veille-case-study__col veille-case-study__col--do\">\n<p class=\"veille-case-study__label\">What can be done<\/p>\n<ul>\n<li>Clearly describe the authorized tasks: sort, flag, suggest, draft.<\/li>\n<li>Keep the decision to approve or reject under human responsibility.<\/li>\n<li>Set thresholds for sensitive, incomplete, or high-value files.<\/li>\n<li>Keep an audit log with data used, rule applied, and validation.<\/li>\n<li>Test on a small perimeter with internal audit and data protection.<\/li>\n<\/ul>\n<\/div>\n<div class=\"veille-case-study__col veille-case-study__col--dont\">\n<p class=\"veille-case-study__label\">What not to do<\/p>\n<ul>\n<li>Let the AI automatically send rejections to students.<\/li>\n<li>Use unnecessary or unauthorized personal data.<\/li>\n<li>Accepting a recommendation without understanding the criteria used.<\/li>\n<li>Believing that the phrase \u00abAI suggested it\u00bb covers the organization.<\/li>\n<li>Deploy the tool without training agents and control managers.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/aside>\n<h2>Questions to Ask Before Acting<\/h2>\n<ul>\n<li>Does the AI offer a recommendation or can it act directly in the system?<\/li>\n<li>Who bears responsibility if the action is false, unjust, or non-compliant?<\/li>\n<li>What actions should remain forbidden for AI, even if they seem useful?<\/li>\n<li>From what risk level is formal human validation required?<\/li>\n<li>Is it possible to find out why a decision was made three months later?<\/li>\n<li>Are the data used necessary, authorized, and protected?<\/li>\n<li>Can internal audit test the system with concrete evidence?<\/li>\n<\/ul>\n<h2>UNIVGA Viewpoint<\/h2>\n<aside class=\"veille-univga-voice\">\n<p>For Gabon and French-speaking Africa, this topic doesn't just concern large banks. Government agencies, universities, hospitals, insurance companies, logistics firms, and small and medium-sized enterprises (SMEs) will use AI agents to speed things up. The real governance question will be less spectacular, but decisive: who decided, on what basis, with what data, within what limits, and under whose human responsibility?<\/p>\n<p>Gabon already has a strong entry point with personal data protection. The Authority for the Protection of Personal Data and Privacy (APDPVP) recalls the existence of obligations regarding data, breaches, the data protection officer, and certain processing operations related to technological innovation. For UNIVGA's School of Compliance, Audit &amp; Governance, this calls for a cross-functional approach: internal audit, risk management, cybersecurity, data governance, and regulatory compliance.<\/p>\n<p>UNIVGA's position is clear: African organizations must not only buy imported tools. They must demand audit logs, data clauses, proof of control, usage limits, and local expertise capable of evaluating these systems.<\/p>\n<\/aside>\n<aside class=\"veille-univga-encart\">\n<p class=\"veille-univga-encart__label\">Training at UNIVGA<\/p>\n<p>UNIVGA offers professional certifications in many fields. Browse the complete catalog of our schools and training programs to find the path that suits your project.<\/p>\n<p><a href=\"https:\/\/univga.org\/en\/our-training-courses\/\">Discover our training programs<\/a><\/aside>\n<h2>Sources<\/h2>\n<ol>\n<li><a href=\"https:\/\/financialit.net\/news\/artificial-intelligence\/mas-partners-industry-develop-safeguards-ai-agents-finance\">MAS Partners with Industry to Develop Safeguards for AI Agents in Finance, Financial IT<\/a><\/li>\n<li><a href=\"https:\/\/kla.digital\/blog\/safr-mas-framework-explained\">What is SAFR? MAS's Runtime Framework for AI Agents<\/a><\/li>\n<li><a href=\"https:\/\/www.iso.org\/standard\/42001?utm_source=openai\">ISO\/IEC 42001:2023, AI management systems<\/a><\/li>\n<li><a href=\"https:\/\/www.apdpvp.ga\/textes-et-decisions\/\">Texts and Laws, APDPVP<\/a><\/li>\n<li><a href=\"https:\/\/www.globenewswire.com\/news-release\/2026\/07\/07\/3323253\/0\/en\/Latest-DigiCert-Research-Shows-AI-Security-Risks-Already-Hitting-Enterprises-with-78-Reporting-Incidents.html\">Latest DigiCert Research Shows AI Security Risks Already Hitting Enterprises<\/a><\/li>\n<\/ol>","protected":false},"excerpt":{"rendered":"<p>Artificial intelligence agents can prepare payments or decisions. Here's how to set limits, human validation, and proof before action.<\/p>","protected":false},"author":6945,"featured_media":152895,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1969],"tags":[2011,2005,1982,1980,1987],"offerexpiration":[],"class_list":["post-152894","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-veille-technologique","tag-audit-interne","tag-conformite","tag-gouvernance","tag-intelligence-artificielle","tag-protection-des-donnees"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.9 (Yoast SEO v27.9) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Comment contr\u00f4ler une IA avant qu\u2019elle n\u2019agisse seule ?<\/title>\n<meta name=\"description\" content=\"Quand une IA peut agir seule, la conformit\u00e9 doit v\u00e9rifier les droits, garder la preuve et pr\u00e9voir une 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