{"id":4867,"date":"2026-03-06T09:14:46","date_gmt":"2026-03-06T08:14:46","guid":{"rendered":"https:\/\/www.meltone.com\/ai-and-data-ai-is-transforming-roles-but-above-all-it-is-strengthening-accountability\/"},"modified":"2026-08-04T10:54:40","modified_gmt":"2026-08-04T08:54:40","slug":"ai-and-data-ai-is-transforming-roles-but-above-all-it-is-strengthening-accountability","status":"publish","type":"post","link":"https:\/\/www.meltone.com\/en\/ai-and-data-ai-is-transforming-roles-but-above-all-it-is-strengthening-accountability\/","title":{"rendered":"AI and data: AI is transforming roles, but above all it is strengthening accountability"},"content":{"rendered":"\n\n\n<section    \n        class=\"block-hero block-hero-article theme-dark deco-article align-left\"\n        data-halo\n        data-bg-dark=\"true\"\n        >\n                <div class=\"hero-deco\" aria-hidden=\"true\">\n                                            <svg viewBox=\"0 0 1440 738\" preserveAspectRatio=\"xMidYMid slice\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n  <defs>\n    <radialGradient id=\"articleGlow\" cx=\"0.5\" cy=\"0.5\" r=\"0.5\">\n      <stop stop-color=\"#11163A\"\/>\n      <stop offset=\"1\" stop-color=\"#404672\" stop-opacity=\"0\"\/>\n    <\/radialGradient>\n  <\/defs>\n  <!-- Glow navy centre-droite (Ellipse 57) -->\n  <circle cx=\"1233\" cy=\"615\" r=\"485\" fill=\"url(#articleGlow)\"\/>\n  <!-- Cercle jaune coin bas-droite (Ellipse 101) -->\n  <circle cx=\"1445.5\" cy=\"766.5\" r=\"250.5\" fill=\"#FCFDD5\"\/>\n  <!-- Ruban pastel (Vector 34, pivot\u00e9) -->\n  <g transform=\"translate(1394.08 447.89) rotate(-47.93) translate(-1109.87 -445.02)\">\n    <path d=\"M61.82 28.5275C194.533 316.12 578.292 46.9245 653.141 382.104C654.417 535.861 589.028 689.62 708.744 764.513C856.261 845.08 975.976 736.712 1020.8 616.429C1065.62 496.146 1153.49 283.658 1327.58 313.766C1503.1 344.122 1514.25 624.794 1765.03 775.716C1879.9 844.848 2032.71 839.997 2180.79 736.735\" stroke=\"#CED9FA\" stroke-width=\"136.17\"\/>\n  <\/g>\n<\/svg>\n\n                    <\/div>\n    \n    <span class=\"halo\"><\/span>\n    <div class=\"container\">\n                                <div class=\"breadcrumb\">\n            <ul class=\"breadcrumb-list\">\n                <li class=\"breadcrumb-list_item\">\n                    <a href=\"https:\/\/www.meltone.com\/en\/\">Accueil<\/a>\n                <\/li>\n\n                                                        \n                                                                                                                                                                                                                                                                                                \n                                                                                                    \n                                        <li class=\"breadcrumb-list_item\"><\/li>\n                            <\/ul>\n        <\/div>\n    \n                <div class=\"grid\">\n            <div class=\"grid_content\">\n                                \n                                \n                                        \n                        \n                    \n            <h1\n        class=\"title title-hero\"\n                        >AI and data: AI is transforming roles, but above all it is strengthening accountability<\/h1>\n    \n                                                                \n                                    \n                \n        <div class=\"editor\"\n        >\n        <p>In many companies, artificial intelligence is now being integrated into reporting, financial analysis, and operational management tools. Conversational agents, natural-language queries, automatic generation of KPIs: AI is speeding up access to information and simplifying tasks that have historically been technical in the data space. <\/p>\n<p>But behind this promise of analytical autonomy, one reality stands out: <strong>AI does not replace data expertise; it redefines its scope and accountability.<\/strong><\/p>\n<p>So the question is not only technological. It is above all organisational. <\/p>\n\n        <\/div>\n    \n                                                    <span class=\"block-hero-article_tag\">Opinion<\/span>\n                                                    <div class=\"block-hero-article_meta\">\n                                                    <span class=\"author-by\">\n                                R\u00e9dig\u00e9 par\n                                                                    <a class=\"author\" href=\"https:\/\/www.meltone.com\/en\/author\/agence2web\/\">agence2web<\/a>\n                                                            <\/span>\n                                                <span class=\"date\">6 March 2026<\/span>                    <\/div>\n                            <\/div>\n        <\/div>\n    <\/div>\n<\/section>\n\n\n\n<section    \n        class=\"block-content block-content-text-meltone\"\n                >\n                <div class=\"block-content-text-meltone_deco\" aria-hidden=\"true\">\n            <span class=\"deco deco--circle\"><svg viewBox=\"0 0 361 361\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\" focusable=\"false\">\n    <circle cx=\"180.5\" cy=\"180.5\" r=\"180.5\" fill=\"#404672\"\/>\n<\/svg>\n<\/span>\n            <span class=\"deco deco--arabesque\"><svg viewBox=\"0 0 699 1104.12\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\" focusable=\"false\">\n    <path d=\"M490.629 52.3639C180.108 186.874 -55.8918 558.409 103.573 660.574C243.033 749.921 491.159 636.844 579.833 551.803C691.514 444.698 654.91 330.416 530.048 359.901C387.578 393.544 248.471 577.054 237.206 839.268C226.498 1088.51 463.222 968.525 637.798 774.562C641.376 770.588 648.324 775.163 645.893 779.926C608.135 853.903 537.488 996.6 530.048 1051.76\" stroke=\"#CED9FA\" stroke-width=\"104.701\" stroke-linecap=\"round\"\/>\n<\/svg>\n<\/span>\n        <\/div>\n            <div class=\"container\">\n        <div class=\"grid\">\n            <div class=\"grid_content\">\n                                                    \n                                \n                                        \n                        \n                    \n            <h2\n        class=\"title title-section\"\n                        >Can we really trust the results produced by AI?<\/h2>\n    \n                                                            \n                                    \n                \n        <div class=\"editor\"\n        >\n        <p><em>Trust in AI does not rest on its infallibility, but on rigorous oversight: audits, testing and governance to uncover and control its weaknesses\u2014where human error, more visible, remains easier to attribute.<\/em><\/p>\n<p><strong>Scepticism towards AI often concerns its reliability.<\/strong><br \/>\nAn error generated by an automated system seems more serious than a human error: faster, potentially affecting considerable volumes, it appears systemic and difficult to attribute.<\/p>\n<p>Yet in practice, the impact and the means of preventing errors are not so different from human action.<\/p>\n<p>The difference lies elsewhere: an employee can be identified, challenged and held accountable. An AI, on the other hand, does not legally bear fault. <\/p>\n<p>This implies a shift in posture. The tool must be supervised, audited, tested\u2014not because it is intrinsically less reliable, but because its ability to produce convincing results can mask underlying weaknesses.  <\/p>\n<p>&nbsp;<\/p>\n<p><strong>Trust does not disappear with AI.<br \/>\nIt must be structured.<\/strong><\/p>\n\n        <\/div>\n    \n            <\/div>\n                    <\/div>\n    <\/div>\n<\/section>\n\n\n\n<section    \n        class=\"block-content block-content-text-meltone no-deco\"\n                >\n                <div class=\"container\">\n        <div class=\"grid\">\n            <div class=\"grid_content\">\n                                                    \n                                \n                                        \n                        \n                    \n            <h2\n        class=\"title title-section\"\n                        >A transformation of roles rather than a disappearance<\/h2>\n    \n                                                            \n                                    \n                \n        <div class=\"editor\"\n        >\n        <p style=\"text-align: left;\"><em>AI automates part of the technical tasks, refocusing data experts on their core work: defining KPIs, documentation, validating results, and accountability for the generated outputs<\/em>.<\/p>\n<p style=\"text-align: left;\">Contrary to some common misconceptions,<strong> artificial intelligence does not signal the end of data roles.<\/strong><br \/>\nHistorically, data projects relied heavily on strong individual technical skills:<\/p>\n<ul>\n<li style=\"text-align: left;\">Development<\/li>\n<li style=\"text-align: left;\">Modelling<\/li>\n<li style=\"text-align: left;\">Building complex queries<\/li>\n<\/ul>\n<p>AI agents now handle part of this technical exploration. But that does not reduce the value of experts\u2014quite the opposite.<br \/>\nTheir role is evolving towards: <\/p>\n<ul>\n<li style=\"text-align: left;\">Proper definition of KPIs<\/li>\n<li style=\"text-align: left;\">Understanding and formalising business rules<\/li>\n<li style=\"text-align: left;\">Validating calculations and generated results<\/li>\n<\/ul>\n<div class=\"is-layout-flex wp-container-2 wp-block-columns\">\n<p>Value is shifting from technical production to the <strong>guarantee of consistency.<\/strong><br \/>\nThis evolution directly affects finance, management control, marketing, and supply chain functions: all roles built on analysis and operational steering are impacted.<strong> AI speeds up processing, but paradoxically strengthens the need for human expertise.<\/strong><\/p>\n<\/div>\n\n        <\/div>\n    \n            <\/div>\n                    <\/div>\n    <\/div>\n<\/section>\n\n\n\n<section    \n        class=\"block-content block-content-text-meltone is-dark\"\n        data-halo        >\n                    <span class=\"halo\" aria-hidden=\"true\"><\/span>\n        <div class=\"container\">\n        <div class=\"grid\">\n            <div class=\"grid_content\">\n                                                    \n                                \n                                        \n                        \n                    \n            <h2\n        class=\"title title-section\"\n                        >A sense of d\u00e9j\u00e0 vu: from the Big Data wave to the AI era<\/h2>\n    \n                                                            \n                                    \n                \n        <div class=\"editor\"\n        >\n        <p><em>The arrival of AI in data raises challenges similar to those of Big Data: data quality, formalising rules and governance\u2014now with greater urgency to resolve them in order to fully harness its potential.<\/em><\/p>\n<p>This upheaval echoes that of Big Data in the 2010s. Even then, companies were asking: <\/p>\n<ul>\n<li style=\"text-align: left;\">Where can we find the relevant data?<\/li>\n<li style=\"text-align: left;\">How can we use it effectively?<\/li>\n<li style=\"text-align: left;\">For which concrete use cases?<\/li>\n<\/ul>\n<p>Issues around data quality, poorly defined business rules, or insufficient documentation have never completely disappeared.<\/p>\n<p>The difference today lies in the level of exposure. By opening up new use cases, AI makes these weaknesses immediately visible to everyone. <\/p>\n<p>An approximate KPI or an implicit rule that went unnoticed in manual processing becomes a source of inconsistency amplified by automation.<\/p>\n<p>&nbsp;<\/p>\n<p><strong>AI does not create these problems. It reveals them. <\/strong><\/p>\n\n        <\/div>\n    \n            <\/div>\n                    <\/div>\n    <\/div>\n<\/section>\n\n\n\n<section    \n        class=\"block-content block-content-text-meltone\"\n                >\n                <div class=\"block-content-text-meltone_deco\" aria-hidden=\"true\">\n            <span class=\"deco deco--circle\"><svg viewBox=\"0 0 361 361\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\" focusable=\"false\">\n    <circle cx=\"180.5\" cy=\"180.5\" r=\"180.5\" fill=\"#404672\"\/>\n<\/svg>\n<\/span>\n            <span class=\"deco deco--arabesque\"><svg viewBox=\"0 0 699 1104.12\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\" focusable=\"false\">\n    <path d=\"M490.629 52.3639C180.108 186.874 -55.8918 558.409 103.573 660.574C243.033 749.921 491.159 636.844 579.833 551.803C691.514 444.698 654.91 330.416 530.048 359.901C387.578 393.544 248.471 577.054 237.206 839.268C226.498 1088.51 463.222 968.525 637.798 774.562C641.376 770.588 648.324 775.163 645.893 779.926C608.135 853.903 537.488 996.6 530.048 1051.76\" stroke=\"#CED9FA\" stroke-width=\"104.701\" stroke-linecap=\"round\"\/>\n<\/svg>\n<\/span>\n        <\/div>\n            <div class=\"container\">\n        <div class=\"grid\">\n            <div class=\"grid_content\">\n                                                    \n                                \n                                        \n                        \n                    \n            <h2\n        class=\"title title-section\"\n                        >Concrete use cases\u2026 provided you have solid foundations<\/h2>\n    \n                                                            \n                                    \n                \n        <div class=\"editor\"\n        >\n        <p style=\"text-align: left;\"><em>AI excels at document exploration and report generation, but its effectiveness relies on structured data, clear business rules, and appropriate governance.<\/em><\/p>\n<p style=\"text-align: left;\">In the field, the most effective use cases remain pragmatic:<\/p>\n<ul>\n<li style=\"text-align: left;\">Ad-hoc exploration of existing data<\/li>\n<li style=\"text-align: left;\">Accelerated document search<\/li>\n<li style=\"text-align: left;\">Generating summary analyses or reports without specific development<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p style=\"text-align: left;\">Some platforms now integrate these capabilities directly at the heart of data environments, making natural-language interaction and the automation of analytical tasks easier.<br \/>\nBut these use cases only create value if the foundations are solid:<\/p>\n<ul>\n<li style=\"text-align: left;\">Reliable, structured data<\/li>\n<li style=\"text-align: left;\">Clearly formalised business rules<\/li>\n<li style=\"text-align: left;\">Defined governance<\/li>\n<li style=\"text-align: left;\">Established validation processes<\/li>\n<\/ul>\n<p>Without these elements, AI can produce results that appear consistent\u2026 but are fragile in their interpretation.<\/p>\n\n        <\/div>\n    \n            <\/div>\n                    <\/div>\n    <\/div>\n<\/section>\n\n\n\n<section    \n        class=\"block-content block-content-text-meltone is-dark\"\n        data-halo        >\n                    <span class=\"halo\" aria-hidden=\"true\"><\/span>\n        <div class=\"container\">\n        <div class=\"grid\">\n            <div class=\"grid_content\">\n                                                    \n                                \n                                        \n                        \n                    \n            <h2\n        class=\"title title-section\"\n                        >Towards new accountability for data roles<\/h2>\n    \n                                                            \n                                    \n                \n        <div class=\"editor\"\n        >\n        <p><em><br \/>\nAI\u2019s reliability depends on human control: its ability to convince must not obscure the need for rigorous audits and process traceability to ensure credibility.<\/em><\/p>\n<p>&nbsp;<\/p>\n<p>Artificial intelligence does not devalue data roles: it repositions them.<\/p>\n<p>The expert is no longer limited to writing queries or developing models. They become the guarantor of: <\/p>\n<ul>\n<li style=\"text-align: left;\">Consistency of indicators,<\/li>\n<li style=\"text-align: left;\">Traceability of calculations,<\/li>\n<li style=\"text-align: left;\">Control framework,<\/li>\n<li style=\"text-align: left;\">Accountability for the results used in decision-making.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p>As AI spreads across organisations, the central question is no longer only \u201cwhat can it do?\u201d, but <strong>\u201cwho is able to validate it?\u201d.<\/strong><br \/>\nThe companies that will derive the most value from AI will be those that accept the need to strengthen their data fundamentals before automating its use.<\/p>\n\n        <\/div>\n    \n            <\/div>\n                    <\/div>\n    <\/div>\n<\/section>\n\n\n\n<section    \n        class=\"block-content block-content-text-meltone\"\n                >\n                <div class=\"block-content-text-meltone_deco\" aria-hidden=\"true\">\n            <span class=\"deco deco--circle\"><svg viewBox=\"0 0 361 361\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\" focusable=\"false\">\n    <circle cx=\"180.5\" cy=\"180.5\" r=\"180.5\" fill=\"#404672\"\/>\n<\/svg>\n<\/span>\n            <span class=\"deco deco--arabesque\"><svg viewBox=\"0 0 699 1104.12\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" aria-hidden=\"true\" focusable=\"false\">\n    <path d=\"M490.629 52.3639C180.108 186.874 -55.8918 558.409 103.573 660.574C243.033 749.921 491.159 636.844 579.833 551.803C691.514 444.698 654.91 330.416 530.048 359.901C387.578 393.544 248.471 577.054 237.206 839.268C226.498 1088.51 463.222 968.525 637.798 774.562C641.376 770.588 648.324 775.163 645.893 779.926C608.135 853.903 537.488 996.6 530.048 1051.76\" stroke=\"#CED9FA\" stroke-width=\"104.701\" stroke-linecap=\"round\"\/>\n<\/svg>\n<\/span>\n        <\/div>\n            <div class=\"container\">\n        <div class=\"grid\">\n            <div class=\"grid_content\">\n                                                    \n                                \n                                        \n                        \n                    \n            <h2\n        class=\"title title-section\"\n                        >Key takeaways<\/h2>\n    \n                                                            \n                                    \n                \n        <div class=\"editor\"\n        >\n        <p>AI marks a new stage in the history of data projects. Like Big Data yesterday, it opens up a field of possibilities that seems limitless today.<br \/>\nBut it also reminds us of a simple truth: without reliable data, clear rules and structured governance, no technology guarantees decision quality.<br \/>\nArtificial intelligence does not erase data roles. It evolves them towards a more strategic role: guardians of consistency, control and accountability.  <\/p>\n\n        <\/div>\n    \n            <\/div>\n                            <div class=\"grid_action\">\n                    <div class=\"action\">\n                                                        \n    \n    \n                \n    <a href=\"https:\/\/www.meltone.com\/en\/ai-as-a-bridge-between-business-and-it-when-hybrid-agent-networks-reinvent-data-analysis\/\"\n       class=\"btn btn-primary has-icon has-icon--right\"\n                               aria-label=\"Discover another article by Camille Maurice\"                            >\n        <span class=\"btn_title\">Discover another article by Camille Maurice<\/span>\n                    <span class=\"btn_icon\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 12 8\" fill=\"none\"><path d=\"M11.3549 4.02215C11.5494 3.82617 11.5482 3.50959 11.3522 3.31505L8.15841 0.144959C7.96242 -0.0495739 7.64584 -0.0483934 7.45131 0.147595C7.25677 0.343584 7.25795 0.660165 7.45394 0.854697L10.2929 3.67256L7.47504 6.51151C7.2805 6.7075 7.28168 7.02408 7.47767 7.21861C7.67366 7.41315 7.99024 7.41197 8.18477 7.21598L11.3549 4.02215ZM0 3.71094L0.00186433 4.21093L11.0019 4.16992L11 3.66992L10.9981 3.16993L-0.00186433 3.21094L0 3.71094Z\" fill=\"currentColor\"\/><\/svg><\/span>\n            <\/a>\n\n                                            <\/div>\n                <\/div>\n                    <\/div>\n    <\/div>\n<\/section>\n\n\n<section     class=\"block-editor\"\n        >\n    <div class=\"container\">\n        <div class=\"grid\">\n            <div class=\"grid_content\">\n                <div class=\"editor\"><p><em>This article is inspired by an op-ed published by <a href=\"https:\/\/www.linkedin.com\/in\/camillemaurice\/\" target=\"_blank\" rel=\"noreferrer noopener\">Camille Maurice<\/a>, Data &#038; Analytics Director at MeltOne, in the newspaper Informatiques News in 202<\/em>6<\/p>\n<\/div>\n            <\/div>\n        <\/div>\n    <\/div>\n<\/section>\n\n\n<section    \n        class=\"block-content block-cta-contact cta--variation-1\"\n        >\n    <div class=\"container\">\n        <div class=\"grid\">\n            <div class=\"grid_content\">\n                <div class=\"card\">\n                    <div class=\"card_content\">\n                        <div class=\"card_deco\" aria-hidden=\"true\">\n                            <svg viewBox=\"0 0 520 412\" preserveAspectRatio=\"xMidYMid slice\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><svg fill=\"none\" x=\"-108\" y=\"315\" width=\"306\" height=\"306\" viewBox=\"0 0 306.0 306.0\" overflow=\"visible\">\n<circle id=\"Ellipse 59\" cx=\"153\" cy=\"153\" r=\"153\" fill=\"#9DD5D5\"\/>\n<\/svg><svg fill=\"none\" x=\"-43.0\" y=\"165.0\" width=\"597.0\" height=\"597.0\" viewBox=\"0 0 597.0 597.0\" overflow=\"visible\">\n<circle id=\"Ellipse 58\" cx=\"298.5\" cy=\"298.5\" r=\"298.5\" 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class=\"post-item_thumb\">\n                <a href=\"https:\/\/www.meltone.com\/en\/can-we-trust-generative-ai-in-finance\/\">\n                                \n                                                                                                                                            \n                <picture >\n\n                                        <source media=\"(min-width: 1024px)\" srcset=\"https:\/\/www.meltone.com\/wp-content\/uploads\/2026\/07\/Peut-on-faire-confiance-a-lIA-generative-en-Finance--1200x0-c-default.webp 1x, https:\/\/www.meltone.com\/wp-content\/uploads\/2026\/07\/Peut-on-faire-confiance-a-lIA-generative-en-Finance--2400x0-c-default.webp 2x\">\n\n                                        <source media=\"(min-width: 768px)\" srcset=\"https:\/\/www.meltone.com\/wp-content\/uploads\/2026\/07\/Peut-on-faire-confiance-a-lIA-generative-en-Finance--800x0-c-default.webp 1x, 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d=\"M11.3549 4.02215C11.5494 3.82617 11.5482 3.50959 11.3522 3.31505L8.15841 0.144959C7.96242 -0.0495739 7.64584 -0.0483934 7.45131 0.147595C7.25677 0.343584 7.25795 0.660165 7.45394 0.854697L10.2929 3.67256L7.47504 6.51151C7.2805 6.7075 7.28168 7.02408 7.47767 7.21861C7.67366 7.41315 7.99024 7.41197 8.18477 7.21598L11.3549 4.02215ZM0 3.71094L0.00186433 4.21093L11.0019 4.16992L11 3.66992L10.9981 3.16993L-0.00186433 3.21094L0 3.71094Z\" fill=\"currentColor\"\/>\n<\/svg>\n\n            <\/span>\n            <\/a>\n\n            <\/div>\n        <\/div>\n    <\/article>\n\n                            <\/div>\n        <\/div>\n    <\/div>\n<\/section>","protected":false},"excerpt":{"rendered":"<p>In many companies, artificial intelligence is now being integrated into reporting, financial analysis, and operational management tools. Conversational agents, natural-language queries, automatic generation of KPIs: AI is speeding up access to information and simplifying tasks that have historically been technical in the data space.  But behind this promise of analytical autonomy, one reality stands out: [\u2026]<\/p>\n","protected":false},"author":1,"featured_media":4868,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[154],"tags":[155],"cas-client-offre":[],"class_list":["post-4867","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-opinion","tag-data-analytics"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AI and data: AI is transforming roles, but above all it is strengthening accountability | Opinion - MeltOne<\/title>\n<meta name=\"description\" content=\"AI is profoundly transforming data roles, accelerating innovation and operational performance. 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