{"id":54825,"date":"2026-08-03T13:43:18","date_gmt":"2026-08-03T11:43:18","guid":{"rendered":"https:\/\/www.altares.be\/?p=54825"},"modified":"2026-08-03T13:43:19","modified_gmt":"2026-08-03T11:43:19","slug":"etendre-usage-ia-seules-6-organisations-pretes","status":"publish","type":"post","link":"https:\/\/www.altares.be\/fr\/blog\/master-data-management\/ai-opschalen-slechts-6-van-de-organisaties-is-er-klaar-voor\/","title":{"rendered":"\u00c9tendre l\u2019usage de l\u2019IA\u00a0? Seules 6\u00a0% des organisations sont pr\u00eates"},"content":{"rendered":"

L\u2019IA produit de plus en plus souvent des r\u00e9sultats concrets. Selon la derni\u00e8re \u00e9dition de l\u2019AI Momentum Survey de Dun & Bradstreet, plus de trois organisations sur quatre tirent d\u00e9sormais un rendement mesurable de l\u2019IA. Pourtant, seules 6\u00a0% estiment que leurs donn\u00e9es sont pleinement pr\u00eates \u00e0 soutenir son d\u00e9ploiement \u00e0 grande \u00e9chelle.<\/p>\n\n\n\n

Cette \u00e9tude est men\u00e9e chaque trimestre aupr\u00e8s de 10\u00a0000\u00a0entreprises dans 32\u00a0pays.\nElle permet de suivre la rapidit\u00e9 avec laquelle l\u2019IA \u00e9volue, tout en r\u00e9v\u00e9lant les limites qui apparaissent \u00e0 mesure que son usage s\u2019\u00e9tend.\nLe rendement progresse fortement, tandis que le niveau de pr\u00e9paration \u00e0 l'IA<\/a> des donn\u00e9es sous-jacentes \u00e9volue \u00e0 peine.<\/p>\n\n\n\n

\"Fondation<\/figure>\n\n\n\n

Le rendement de l\u2019IA a fortement progress\u00e9 en un trimestre<\/h2>\n\n\n\n

Lors de l\u2019\u00e9dition pr\u00e9c\u00e9dente, 60\u00a0% des organisations d\u00e9claraient tirer au moins un rendement mesurable de l\u2019IA. Un trimestre plus tard, cette proportion d\u00e9passe 75\u00a0%. La part des organisations qui constatent un rendement important sur plusieurs projets d\u2019IA est \u00e9galement pass\u00e9e de 24\u00a0% \u00e0 28\u00a0%.<\/p>\n\n\n\n

L\u2019IA est donc de plus en plus \u00e9valu\u00e9e \u00e0 l\u2019aune de ce qu\u2019elle apporte concr\u00e8tement. Une grande partie de ce rendement reste toutefois limit\u00e9e \u00e0 des applications pr\u00e9cises et \u00e0 des projets pilotes. Le succ\u00e8s d\u2019un cas d\u2019usage au sein d\u2019une \u00e9quipe ne garantit pas que les m\u00eames r\u00e9sultats puissent \u00eatre obtenus dans plusieurs processus.<\/p>\n\n\n\n

Lisez aussi :<\/strong> La nouvelle phase de l\u2019IA : de l'exp\u00e9rimentation au rendement<\/a><\/p>\n\n\n\n

De plus en plus d\u2019organisations \u00e9tendent l\u2019usage de l\u2019IA<\/h2>\n\n\n\n

Le passage en production s\u2019acc\u00e9l\u00e8re lui aussi. La part des organisations qui \u00e9tendent activement l\u2019usage de l\u2019IA est pass\u00e9e de 30\u00a0% \u00e0 34\u00a0% en un trimestre. Plus de la moiti\u00e9 l\u2019utilisent d\u00e9sormais dans plusieurs processus cl\u00e9s, la d\u00e9ploient plus largement ou ont recours \u00e0 des applications d\u2019IA agentique.<\/p>\n\n\n\n

Cette \u00e9volution renforce les exigences en mati\u00e8re de donn\u00e9es. Un projet pilote limit\u00e9 \u00e0 un cas d\u2019usage pr\u00e9cis peut encore s\u2019appuyer sur une seule source de donn\u00e9es, compl\u00e9t\u00e9e par des v\u00e9rifications manuelles. Lorsque l\u2019usage de l\u2019IA s\u2019\u00e9tend, celle-ci doit pouvoir combiner de mani\u00e8re fiable des informations issues de diff\u00e9rents syst\u00e8mes et processus. Les clients, les fournisseurs et les liens entre soci\u00e9t\u00e9s d\u2019un m\u00eame groupe doivent \u00eatre identifi\u00e9s de fa\u00e7on coh\u00e9rente dans toute l\u2019organisation.<\/p>\n\n\n\n

Lisez aussi :<\/strong> L\u2019IA agentique : passer de la promesse \u00e0 l\u2019application concr\u00e8te<\/a><\/p>\n\n\n\n

Les donn\u00e9es ne suivent pas le rythme<\/h2>\n\n\n\n

Alors que le rendement de l\u2019IA progresse et que son usage s\u2019\u00e9tend, la pr\u00e9paration des donn\u00e9es \u00e9volue tr\u00e8s peu. Parmi les organisations interrog\u00e9es, 47\u00a0% consid\u00e8rent que leurs donn\u00e9es sont partiellement pr\u00eates pour l\u2019IA et 36\u00a0% qu\u2019elles le sont en grande partie. Seules 6\u00a0% disposent de donn\u00e9es pleinement adapt\u00e9es \u00e0 un usage de l\u2019IA \u00e0 grande \u00e9chelle, contre 5\u00a0% un trimestre plus t\u00f4t.<\/p>\n\n\n\n

Cette faible progression montre que la maturit\u00e9 en mati\u00e8re d\u2019IA et celle des donn\u00e9es n\u2019\u00e9voluent pas automatiquement au m\u00eame rythme. Il est relativement facile d\u2019obtenir des r\u00e9sultats rapides lorsque l\u2019IA est utilis\u00e9e pour un besoin bien pr\u00e9cis. En revanche, nettoyer, relier et maintenir \u00e0 jour les donn\u00e9es d\u2019entreprise dans plusieurs syst\u00e8mes et services demande davantage de temps et d\u2019efforts.<\/p>\n\n\n\n

\u00c0 mesure que l\u2019usage de l\u2019IA s\u2019\u00e9tend, les probl\u00e8mes de qualit\u00e9 des donn\u00e9es ont \u00e9galement des cons\u00e9quences plus importantes. Les doublons dans les fichiers d\u2019entreprise, les informations obsol\u00e8tes et l\u2019absence de liens entre soci\u00e9t\u00e9s d\u2019un m\u00eame groupe n\u2019affectent alors plus une seule analyse, mais plusieurs processus et d\u00e9cisions \u00e0 la fois.<\/p>\n\n\n\n

Comment maintenir le rendement de l\u2019IA dans la dur\u00e9e\u00a0?<\/h2>\n\n\n\n

Les chiffres trimestriels montrent que l\u2019IA produit des r\u00e9sultats de plus en plus rapidement, tandis que la qualit\u00e9 et la pr\u00e9paration des donn\u00e9es sous-jacentes peinent \u00e0 suivre. Ce d\u00e9calage devient particuli\u00e8rement visible lorsque les organisations cherchent \u00e0 \u00e9tendre son usage. L\u2019IA ne doit pas seulement avoir acc\u00e8s aux donn\u00e9es. Elle doit aussi comprendre de quelle entit\u00e9 juridique il s\u2019agit, comment les organisations sont li\u00e9es entre elles et si les informations utilis\u00e9es sont toujours \u00e0 jour.<\/p>\n\n\n\n

La pr\u00e9paration \u00e0 l\u2019IA ne repose donc pas sur des donn\u00e9es parfaites, mais sur un socle de donn\u00e9es capable d\u2019\u00e9voluer en m\u00eame temps que l\u2019usage de l\u2019IA dans l\u2019organisation. Au sein de l'\u00e9cosyst\u00e8me D&B.AI<\/a> , nous associons donn\u00e9es d\u2019entreprise fiables, technologies et conseils afin de fournir aux applications d\u2019IA des informations actualis\u00e9es, v\u00e9rifi\u00e9es et enrichies du contexte professionnel n\u00e9cessaire.<\/p>\n\n\n\n

Vous souhaitez \u00e9changer sur le niveau de pr\u00e9paration de votre organisation \u00e0 l\u2019IA et sur les conditions n\u00e9cessaires pour en \u00e9tendre l\u2019usage\u00a0? Planifiez un rendez-vous<\/a> avec nos experts en IA.<\/p>","protected":false},"excerpt":{"rendered":"

L\u2019IA g\u00e9n\u00e8re de plus en plus souvent un rendement mesurable, et les organisations \u00e9tendent plus rapidement son utilisation. Pourtant, la pr\u00e9paration des donn\u00e9es ne suit pas le m\u00eame rythme\u00a0: seules 6 % des organisations se disent pleinement pr\u00eates \u00e0 soutenir l\u2019IA \u00e0 grande \u00e9chelle. Pour maintenir ce rendement dans la dur\u00e9e, elles doivent pouvoir s\u2019appuyer sur un socle de donn\u00e9es fiable, o\u00f9 les informations sur les entreprises sont \u00e0 jour, reli\u00e9es entre elles et identifi\u00e9es de mani\u00e8re coh\u00e9rente.<\/p>","protected":false},"author":9,"featured_media":54827,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[19],"tags":[],"class_list":["post-54825","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-master-data-management"],"acf":[],"yoast_head":"\nAI opschalen? Slechts 6% van de organisaties is er klaar voor - Altares<\/title>\n<meta name=\"description\" content=\"Meer dan 75% van de organisaties haalt rendement uit AI, maar slechts 6% heeft volledig AI-ready data. 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