{"id":188671,"date":"2026-03-05T10:34:27","date_gmt":"2026-03-05T09:34:27","guid":{"rendered":"https:\/\/www.ainia.com\/?p=188671"},"modified":"2026-03-05T10:36:09","modified_gmt":"2026-03-05T09:36:09","slug":"lia-anticipe-les-risques-optimise-les-processus-et-renforce-la-tracabilite-en-securite-alimentaire","status":"publish","type":"post","link":"https:\/\/www.ainia.com\/fr\/ainia-news\/lia-anticipe-les-risques-optimise-les-processus-et-renforce-la-tracabilite-en-securite-alimentaire\/","title":{"rendered":"L\u2019IA anticipe les risques, optimise les processus et renforce la tra\u00e7abilit\u00e9 en s\u00e9curit\u00e9 alimentaire"},"content":{"rendered":"

Dans un contexte de cha\u00eenes d\u2019approvisionnement mondiales, de pression r\u00e9glementaire accrue et de consommateurs plus exigeants, AINIA a organis\u00e9 une session en ligne au cours de laquelle il a \u00e9t\u00e9 analys\u00e9 comment l\u2019intelligence artificielle (IA) transforme la s\u00e9curit\u00e9 alimentaire. Le responsable du d\u00e9veloppement strat\u00e9gique digital et des alliances, David Mart\u00ednez, et le responsable de la s\u00e9curit\u00e9 alimentaire chez AINIA, Roberto Ortu\u00f1o, ont convenu que l\u2019IA renforce l\u2019expertise humaine<\/strong> et am\u00e9liore la prise de d\u00e9cision<\/strong>. Tous deux ont \u00e9galement soulign\u00e9 l\u2019importance de disposer d\u2019\u00e9quipes multidisciplinaires<\/strong> (technologie et s\u00e9curit\u00e9 alimentaire), de garantir la qualit\u00e9 des donn\u00e9es<\/strong> et d\u2019assurer l\u2019explicabilit\u00e9 des mod\u00e8les<\/strong> afin d\u2019\u00e9voluer vers une approche plus proactive et plus efficace <\/strong>du contr\u00f4le alimentaire.<\/p>\n

L\u2019IA, un \u00ab copilote \u00bb pour des d\u00e9cisions fond\u00e9es sur des preuves<\/strong><\/h2>\n

Pour le responsable du d\u00e9veloppement strat\u00e9gique digital et des alliances chez AINIA, \u00ab l\u2019IA ne remplace pas l\u2019expertise ; elle l\u2019amplifie. C\u2019est notre copilote pour r\u00e9agir plus t\u00f4t, avec plus de pr\u00e9cision et avec des d\u00e9cisions fond\u00e9es sur des preuves \u00bb. Dans cette perspective, David Mart\u00ednez a expliqu\u00e9 comment la combinaison de capteurs avanc\u00e9s, d\u2019analytique de donn\u00e9es et de mod\u00e8les pr\u00e9dictifs<\/a><\/strong> permet de passer de mod\u00e8les r\u00e9actifs \u00e0 des approches proactives en mati\u00e8re de s\u00e9curit\u00e9 alimentaire.<\/p>\n

Dans cette ligne, le responsable de la s\u00e9curit\u00e9 alimentaire chez AINIA a mis en avant une gestion efficace des donn\u00e9es : \u00ab Nous traitons de plus en plus de donn\u00e9es et assumons davantage de responsabilit\u00e9s. L\u2019IA nous aide \u00e0 transformer les donn\u00e9es en informations utiles pour prendre de meilleures d\u00e9cisions et au bon moment \u00bb. Roberto Ortu\u00f1o a ajout\u00e9 que \u00ab la cl\u00e9 r\u00e9side dans la normalisation et l\u2019unification des donn\u00e9es internes et externes afin de prendre des d\u00e9cisions fond\u00e9es sur des preuves, avec des mod\u00e8les explicables et align\u00e9s sur les exigences r\u00e9glementaires \u00bb.<\/p>\n

Applications pratiques : de l\u2019alerte pr\u00e9coce \u00e0 la pr\u00e9diction en usine<\/strong><\/h2>\n

Les intervenants ont convenu que l\u2019approche la plus efficace est progressive, interdisciplinaire et fond\u00e9e sur des projets pilotes rapides avec des indicateurs clairs. Ils ont \u00e9galement soulign\u00e9 l\u2019importance de l\u2019interop\u00e9rabilit\u00e9 et de la collaboration sectorielle pour multiplier l\u2019impact, notamment dans des domaines tels que l\u2019alerte pr\u00e9coce et l\u2019identification des risques \u00e9mergents<\/a>.<\/strong><\/p>\n

Parmi les applications pr\u00e9sent\u00e9es lors du webinaire, il a \u00e9t\u00e9 montr\u00e9 comment l\u2019IA acc\u00e9l\u00e8re la d\u00e9tection des risques \u00e9mergents gr\u00e2ce \u00e0 la curation automatis\u00e9e de signaux dans la litt\u00e9rature scientifique, am\u00e9liore le filtrage des alertes pr\u00e9coces (RASFF, AESAN) et permet d\u2019anticiper les contaminations en usine gr\u00e2ce \u00e0 l\u2019int\u00e9gration de capteurs IoT et d\u2019images<\/strong>. Des cas d\u2019inspection automatique en ligne, d\u2019analytique de donn\u00e9es pour les KPI et de pr\u00e9diction des risques microbiologiques en temps r\u00e9el<\/strong> ont \u00e9galement \u00e9t\u00e9 abord\u00e9s.<\/p>\n

\u00ab La combinaison de l\u2019alerte pr\u00e9coce et de l\u2019analytique avanc\u00e9e nous permet d\u2019anticiper les risques \u00e9mergents et r\u00e9\u00e9mergents et d\u2019agir avant qu\u2019un probl\u00e8me n\u2019atteigne le march\u00e9 \u00bb, a soulign\u00e9 Roberto Ortu\u00f1o.<\/p>\n

Cl\u00e9s de mise en \u0153uvre : cas d\u2019usage d\u00e9finis, donn\u00e9es de qualit\u00e9 et \u00e9quipes mixtes<\/strong><\/h2>\n

Concernant le rythme d\u2019adoption, David Mart\u00ednez a indiqu\u00e9 : \u00ab Le d\u00e9fi n\u2019est plus de savoir s\u2019il faut appliquer l\u2019IA, mais quand et avec quel niveau d\u2019ambition. Ceux qui int\u00e9greront ces technologies feront la diff\u00e9rence en mati\u00e8re de s\u00e9curit\u00e9 alimentaire \u00bb.<\/p>\n

Parmi les recommandations op\u00e9rationnelles, les deux intervenants ont sugg\u00e9r\u00e9 de commencer par des cas concrets et mesurables avec une vision claire du succ\u00e8s ; de garantir des donn\u00e9es propres et repr\u00e9sentatives ; de cr\u00e9er des \u00e9quipes mixtes (IA, s\u00e9curit\u00e9 alimentaire et personnel d\u2019usine) ; de prototyper et valider rapidement avec des it\u00e9rations courtes ; d\u2019exiger transparence, explicabilit\u00e9 et tra\u00e7abilit\u00e9 des mod\u00e8les ; et de promouvoir l\u2019interop\u00e9rabilit\u00e9 afin d\u2019\u00e9viter les \u00ab \u00eelots de donn\u00e9es \u00bb et de permettre la cr\u00e9ation d\u2019espaces de donn\u00e9es avec des partenaires et des fournisseurs. Cette approche permet d\u2019acc\u00e9l\u00e9rer le passage de l\u2019id\u00e9e \u00e0 la r\u00e9alit\u00e9 et de consolider un cadre d\u2019am\u00e9lioration continue et d\u2019audits plus robustes.<\/p>\n

\"Logo<\/p>\n<\/body><\/html>","protected":false},"excerpt":{"rendered":"

Dans un contexte de cha\u00eenes d\u2019approvisionnement mondiales, de pression r\u00e9glementaire accrue et de consommateurs plus exigeants, AINIA a organis\u00e9 une session en ligne au cours de laquelle il a \u00e9t\u00e9 analys\u00e9 comment l\u2019intelligence artificielle (IA) transforme la s\u00e9curit\u00e9 alimentaire. Le responsable du d\u00e9veloppement strat\u00e9gique digital et des alliances, David Mart\u00ednez, et le responsable de la […]<\/p>\n","protected":false},"author":198,"featured_media":183479,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1978],"tags":[],"class_list":["post-188671","post","type-post","status-publish","format-standard","hentry","category-communiques-de-presse"],"acf":[],"yoast_head":"\nAINIA analyse comment l\u2019IA transforme la s\u00e9curit\u00e9 alimentaire - AINIA<\/title>\n<meta name=\"description\" content=\"AINIA a organis\u00e9 une journ\u00e9e au cours de laquelle il a \u00e9t\u00e9 analys\u00e9 comment l\u2019intelligence artificielle (IA) transforme la s\u00e9curit\u00e9 alimentaire.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link 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