{"id":128790,"date":"2026-11-05T03:51:14","date_gmt":"2026-11-05T03:51:14","guid":{"rendered":"https:\/\/youzum.net\/securing-the-agentic-enterprise-with-data-lineage\/"},"modified":"2026-11-05T03:51:14","modified_gmt":"2026-11-05T03:51:14","slug":"securing-the-agentic-enterprise-with-data-lineage","status":"publish","type":"post","link":"https:\/\/youzum.net\/it\/securing-the-agentic-enterprise-with-data-lineage\/","title":{"rendered":"Securing the agentic enterprise with data lineage"},"content":{"rendered":"<p class=\"wp-block-paragraph\">A sales representative asks an AI agent for customer pricing, and the agent pulls data from multiple sources: restricted pricing systems, internal communications, and archived quotes. The output looks accurate to the agent, so a second agent uses the data to draft the proposal for the sales rep. No human checks either handoff. When it\u2019s discovered that the proposal includes unapproved, confidential, and sensitive information, no one can trace where the problematic data entered the workflow or how it spread across systems, files, and agents.<\/p>\n<figure class=\"wp-block-image size-large is-resized\"><a href=\"https:\/\/www.cyberhaven.com\/resources\/research\/mit-data-lineage-agentic-ai\" target=\"_blank\" rel=\" noopener\"><img fetchpriority=\"high\" decoding=\"async\" height=\"2000\" width=\"1555\" src=\"https:\/\/wp.technologyreview.com\/wp-content\/uploads\/2026\/10\/MITTR_Cyberhaven_V4_Cover.png?w=840\" alt=\"\" class=\"wp-image-1147599\" \/><\/a><\/figure>\n<div class=\"wp-block-buttons is-content-justification-left is-layout-flex wp-container-core-buttons-is-layout-b192c3d7 wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button is-style-fill is-style-fill--4\"><a class=\"wp-block-button__link has-black-color has-text-color has-background has-custom-font-size wp-element-button\" href=\"https:\/\/www.cyberhaven.com\/resources\/research\/mit-data-lineage-agentic-ai\" target=\"_blank\" rel=\"noopener\">DOWNLOAD THE REPORT<\/a><\/div>\n<\/div>\n<p class=\"wp-block-paragraph\">This scenario illustrates why AI governance needs to evolve, rapidly and dynamically. As more enterprises begin to use agentic AI in daily workflows, they\u2019re realizing that they must manage more than static files; they must manage moving and fragmented data that is continuously ingested, copied, summarized, transformed, reused, and redistributed in new forms. In short, AI security isn\u2019t a tool problem; it\u2019s a data visibility problem.<\/p>\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/www.cyberhaven.com\/resources\/research\/mit-data-lineage-agentic-ai\" target=\"_blank\" rel=\" noopener\"><img loading=\"lazy\" decoding=\"async\" width=\"1200\" height=\"675\" src=\"https:\/\/wp.technologyreview.com\/wp-content\/uploads\/2026\/10\/MITTR2026_CyberhavenV1DoshiSocialCards4.png\" alt=\"\" class=\"wp-image-1147601\" \/><\/a><\/figure>\n<p class=\"wp-block-paragraph\">Consequently, traditional security approaches built solely around applications, systems, networks, or endpoints are no longer sufficient. Securing agentic AI at scale requires understanding how data moves. Teams, therefore, need to establish data lineage in order to effectively manage <a href=\"https:\/\/www.nist.gov\/itl\/ai-risk-management-framework\" target=\"_blank\" rel=\"noopener\">governance, accountability, and trust<\/a> across human, agentic, and hybrid workflows.<\/p>\n<p class=\"wp-block-paragraph\"><strong><a href=\"https:\/\/www.cyberhaven.com\/resources\/research\/mit-data-lineage-agentic-ai\" target=\"_blank\" rel=\"noopener\">Download the report<\/a><\/strong><\/p>\n<p class=\"wp-block-paragraph\"><em>This content was produced by Insights, MIT Technology Review\u2019s custom content arm, not its editorial staff. It was researched and written by humans, with any AI tools that may have been used limited to production processes under human oversight.<\/em><\/p>\n<p class=\"wp-block-paragraph\">\n<\/p>","protected":false},"excerpt":{"rendered":"<p>A sales representative asks an AI agent for customer pricing, and the agent pulls data from multiple sources: restricted pricing systems, internal communications, and archived quotes. The output looks accurate to the agent, so a second agent uses the data to draft the proposal for the sales rep. No human checks either handoff. When it\u2019s discovered that the proposal includes unapproved, confidential, and sensitive information, no one can trace where the problematic data entered the workflow or how it spread across systems, files, and agents. DOWNLOAD THE REPORT This scenario illustrates why AI governance needs to evolve, rapidly and dynamically. As more enterprises begin to use agentic AI in daily workflows, they\u2019re realizing that they must manage more than static files; they must manage moving and fragmented data that is continuously ingested, copied, summarized, transformed, reused, and redistributed in new forms. In short, AI security isn\u2019t a tool problem; it\u2019s a data visibility problem. Consequently, traditional security approaches built solely around applications, systems, networks, or endpoints are no longer sufficient. Securing agentic AI at scale requires understanding how data moves. Teams, therefore, need to establish data lineage in order to effectively manage governance, accountability, and trust across human, agentic, and hybrid workflows. Download the report This content was produced by Insights, MIT Technology Review\u2019s custom content arm, not its editorial staff. It was researched and written by humans, with any AI tools that may have been used limited to production processes under human oversight.<\/p>","protected":false},"author":2,"featured_media":128791,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"pmpro_default_level":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center 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NU","author_link":"https:\/\/youzum.net\/it\/members\/adminnu\/"},"rttpg_comment":0,"rttpg_category":"<a href=\"https:\/\/youzum.net\/it\/category\/ai-club\/\" rel=\"category tag\">AI<\/a> <a href=\"https:\/\/youzum.net\/it\/category\/committee\/\" rel=\"category tag\">Committee<\/a> <a href=\"https:\/\/youzum.net\/it\/category\/news\/\" rel=\"category tag\">News<\/a> <a href=\"https:\/\/youzum.net\/it\/category\/uncategorized\/\" rel=\"category tag\">Uncategorized<\/a>","rttpg_excerpt":"A sales representative asks an AI agent for customer pricing, and the agent pulls data from multiple sources: restricted pricing systems, internal communications, and archived quotes. The output looks accurate to the agent, so a second agent uses the data to draft the proposal for the sales rep. No human checks either handoff. When it\u2019s&hellip;","_links":{"self":[{"href":"https:\/\/youzum.net\/it\/wp-json\/wp\/v2\/posts\/128790","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/youzum.net\/it\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/youzum.net\/it\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/youzum.net\/it\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/youzum.net\/it\/wp-json\/wp\/v2\/comments?post=128790"}],"version-history":[{"count":0,"href":"https:\/\/youzum.net\/it\/wp-json\/wp\/v2\/posts\/128790\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/youzum.net\/it\/wp-json\/wp\/v2\/media\/128791"}],"wp:attachment":[{"href":"https:\/\/youzum.net\/it\/wp-json\/wp\/v2\/media?parent=128790"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/youzum.net\/it\/wp-json\/wp\/v2\/categories?post=128790"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/youzum.net\/it\/wp-json\/wp\/v2\/tags?post=128790"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}