{"id":78192,"date":"2026-04-06T10:31:12","date_gmt":"2026-04-06T15:31:12","guid":{"rendered":"https:\/\/www.project44.com\/?p=78192"},"modified":"2026-04-06T10:31:24","modified_gmt":"2026-04-06T15:31:24","slug":"how-to-build-trust-in-ai-at-enterprise-scale","status":"publish","type":"post","link":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/","title":{"rendered":"How to build trust in AI at enterprise scale"},"content":{"rendered":"\n<h3 class=\"wp-block-heading\" id=\"h-the-barrier-to-enterprise-ai-isn-t-capability-it-s-trust-and-in-supply-chain-where-a-wrong-decision-can-cost-a-customer-relationship-or-shut-down-a-production-line-that-distinction-is-everything\"><em>The barrier to enterprise AI\u00a0isn\u2019t\u00a0capability.\u00a0It\u2019s\u00a0trust.\u00a0And in\u00a0supply\u00a0chain,\u00a0where a wrong decision can cost a customer relationship or shut down a\u00a0production line, that distinction is everything.\u00a0<\/em><\/h3>\n\n\n\n<p>In an earlier post, we argued <a href=\"https:\/\/www.project44.com\/ja\/blog\/the-context-problem-why-your-ai-agents-dont-know-enough-to-help-you\/\">that context is the only durable moat in the agentic\u00a0era<\/a>.\u00a0The\u00a0companies who win\u00a0won\u2019t\u00a0be the ones with the best models, but the ones who have spent years building the contextual understanding that makes AI useful in high-stakes environments.\u00a0<\/p>\n\n\n\n<p>But context alone&nbsp;doesn\u2019t&nbsp;build trust. And in&nbsp;supply&nbsp;chain, trust is the actual barrier to adoption. Not cost. Not technology. The question&nbsp;isn\u2019t&nbsp;whether AI can do the job.&nbsp;It\u2019s&nbsp;whether&nbsp;you\u2019d&nbsp;stake a customer relationship on it.&nbsp;<\/p>\n\n\n\n<p>Trust is built through&nbsp;a different set&nbsp;of decisions: how you design the AI, how precisely you define what&nbsp;it\u2019s&nbsp;asked to do, and how you ensure that what it does can be explained, audited, and stood behind.&nbsp;What follows is how that is built in practice.&nbsp;&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-the-nbsp-trust-killer-why-ai-nbsp-gets-nbsp-it-nbsp-wrong-nbsp\"><strong>The&nbsp;trust-killer: Why AI&nbsp;gets&nbsp;it&nbsp;wrong<\/strong>&nbsp;<\/h2>\n\n\n\n<p>The word\u00a0you hear most in enterprise AI conversations is \u201challucination.\u201d A hallucination is when an AI produces an answer that is confident, articulate, and wrong. Not slightly off.\u00a0Directionally wrong.\u00a0Consider a model that recommends a carrier with strong aggregate on-time performance, without knowing that performance collapsed in the last\u00a090 days\u00a0due to a driver shortage at their regional hub. The shipment\u00a0misses. The customer escalates. The model\u00a0didn&#8217;t\u00a0hedge or flag uncertainty. It recommended the wrong carrier with the same confidence it would have had with\u00a0accurate\u00a0data.\u00a0<\/p>\n\n\n\n<p>Hallucination is not a&nbsp;model quality problem.&nbsp;Most enterprise AI models are broadly similar in capability. The real issue is scope: when the job is too large and the data is incomplete, the&nbsp;model fills the gaps with confident-sounding&nbsp;guesses instead of grounded answers.&nbsp;<\/p>\n\n\n\n<p>This happens because&nbsp;AI models are probabilistic. They generate the most statistically plausible response to whatever question you ask.&nbsp;A precise, well-bounded question, with validated data behind&nbsp;it&nbsp;produces&nbsp;reliable output.&nbsp;A vague or overloaded question, or one answered from incomplete data, gives the model no choice but to pattern-match its way to something plausible.&nbsp;That\u2019s&nbsp;where trust breaks down.&nbsp;<\/p>\n\n\n\n<p>Ask an AI to \u201cmanage freight procurement\u201d and\u00a0you\u2019ve\u00a0asked it to confidently navigate an impossibly large problem space. Ask it to \u201crank these five carriers by expected on-time performance on this lane given the last\u00a018 months\u00a0of data\u201d\u00a0and\u00a0you\u2019ve\u00a0given it something it can\u00a0actually get\u00a0right.\u00a0But only if that\u00a018 months\u00a0of data is comprehensive,\u00a0accurate,\u00a0and continuously updated. Scope and data quality are both prerequisites. Neither works without the other.\u00a0<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-breaking-nbsp-work-nbsp-down-to-nbsp-build-nbsp-reliability-nbsp-up-nbsp\"><strong>Breaking&nbsp;work&nbsp;down to&nbsp;build&nbsp;reliability&nbsp;up<\/strong>&nbsp;<\/h2>\n\n\n\n<p>The first principle of trustworthy AI is to define the job precisely.&nbsp;Which means you first&nbsp;have to&nbsp;take the job apart, otherwise known as decomposition.&nbsp;<\/p>\n\n\n\n<p>For example, every major supply chain function that looks like a single job is&nbsp;actually&nbsp;dozens&nbsp;of smaller jobs layered on top of each other.&nbsp;Decomposition means&nbsp;breaking those layers&nbsp;all the way&nbsp;down&nbsp;to tasks specific enough to evaluate, measure, and improve.&nbsp;&nbsp;<\/p>\n\n\n\n<p>Take <a href=\"https:\/\/www.project44.com\/ja\/press-releases\/project44-launches-ai-freight-procurement-agent-to-cut-freight-spend-and-accelerate-sourcing\/\">freight procurement<\/a>.\u00a0In\u00a0practice,\u00a0it\u00a0includes\u00a0at least six distinct jobs: carrier\u00a0selection, carrier negotiation, contract generation, insurance verification, compliance screening, and onboarding coordination.\u00a0Each\u00a0requires\u00a0different inputs, different logic, and a different definition of success.\u00a0<\/p>\n\n\n\n<p>These&nbsp;aren\u2019t&nbsp;just steps in a workflow. They are genuinely separate problems.&nbsp;A mistake in carrier selection surfaces in 72 hours when a shipment is late. A mistake in insurance verification surfaces 18 months later in litigation.&nbsp;The&nbsp;data&nbsp;required&nbsp;is different.&nbsp;The stakes are different. The&nbsp;appropriate level&nbsp;of human oversight may be different.&nbsp;<\/p>\n\n\n\n<p>Treat&nbsp;all of&nbsp;that as one&nbsp;problem,&nbsp;and you get an agent that is difficult to evaluate&nbsp;and&nbsp;impossible to improve. Treat each as a distinct problem with its own requirements,&nbsp;and you create the conditions for AI that can be measured, audited, and held accountable. And when it makes a mistake, you know exactly where to look.&nbsp;&nbsp;<\/p>\n\n\n\n<p>That kind&nbsp;of accountability is&nbsp;inseparable from how precisely the work has been broken apart in the first place.&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-specialized-nbsp-agents-nbsp-context-nbsp-and-the-nbsp-role-of-nbsp-semantics-nbsp\"><strong>Specialized&nbsp;agents,&nbsp;context,&nbsp;and the&nbsp;role of&nbsp;semantics<\/strong>&nbsp;<\/h2>\n\n\n\n<p>Once&nbsp;you\u2019ve&nbsp;decomposed the&nbsp;work into precise tasks, the question&nbsp;becomes&nbsp;what&nbsp;does an AI agent&nbsp;need&nbsp;to perform each one&nbsp;reliably.&nbsp;This is where&nbsp;the concept of a skill matters,&nbsp;and where most AI implementations fall short.&nbsp;<\/p>\n\n\n\n<p>A skill&nbsp;isn\u2019t&nbsp;a feature or a prompt. A skill is what an agent develops when three things align: a task&nbsp;narrow enough to&nbsp;reason about&nbsp;precisely, validated data relevant to that task,&nbsp;and&nbsp;the&nbsp;right semantics.&nbsp;<\/p>\n\n\n\n<p>Context tells the agent&nbsp;what&#8217;s&nbsp;happening, which shipment, which customer, which lane. But context alone&nbsp;isn&#8217;t&nbsp;enough. The model also needs to be grounded in data that has already been processed through a semantic layer, one that defines what that data&nbsp;actually means&nbsp;for this decision. What counts as &#8216;on-time&#8217;&nbsp;in your system? Is it a carrier scan or confirmed delivery at the consignee? Those definitions, encoded in advance, are what&nbsp;separate&nbsp;a model that reasons correctly from one that reasons confidently from the wrong premise.&nbsp;<\/p>\n\n\n\n<p>Without both, even a data-rich agent produces outputs that experienced operators&nbsp;immediately&nbsp;recognize as off. With both, context becomes the basis for genuine judgment.&nbsp;<\/p>\n\n\n\n<p>Consider&nbsp;carrier&nbsp;selection&nbsp;as an&nbsp;example.&nbsp;An agent handling this decision&nbsp;doesn\u2019t&nbsp;just need carrier data as context.&nbsp;It needs to understand which dimensions&nbsp;drive&nbsp;outcomes: on-time performance by lane&nbsp;(not just&nbsp;overall), carrier volume in that&nbsp;specific&nbsp;corridor, safety scores trended over time&nbsp;rather than point-in-time, freight-specific handling history, and customer-specific preferences built from&nbsp;real experience.&nbsp;That semantic framework&nbsp;defines&nbsp;how to prioritize each signal, what combinations are warning signs, and what a number means in this context versus another.&nbsp;&nbsp;<\/p>\n\n\n\n<p>And because the task is narrow, that judgment can be evaluated objectively, improved continuously, and trusted operationally.&nbsp;That\u2019s&nbsp;what makes it a skill rather than a guess.&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-coordination-nbsp-at-scale-the-nbsp-orchestrator-nbsp\"><strong>Coordination&nbsp;at scale: The&nbsp;orchestrator<\/strong>&nbsp;<\/h2>\n\n\n\n<p>Decomposition solves the reliability problem by giving each agent a task narrow enough to&nbsp;reason about&nbsp;precisely. But it introduces a different challenge: coordinating agents that each own only one piece of a larger process.&nbsp;<\/p>\n\n\n\n<p>If carrier&nbsp;selection, negotiation, insurance verification, and compliance screening are all separate agents, something&nbsp;has to&nbsp;manage the sequence.&nbsp;What runs first, what feeds into what, when to escalate, how to synthesize outputs into a&nbsp;coherent&nbsp;result.&nbsp;This is where the&nbsp;orchestrator agent&nbsp;comes in.&nbsp;<\/p>\n\n\n\n<p>The orchestrator\u2019s skill is coordination, not domain&nbsp;expertise. It&nbsp;doesn\u2019t&nbsp;need to know how to select a carrier. It needs to know that carrier selection happens before negotiation,&nbsp;that an&nbsp;incomplete result means the process&nbsp;shouldn\u2019t&nbsp;proceed, that a compliance flag requires human review. It manages the workflow the way a senior operations director manages a team:&nbsp;deep process knowledge without personally executing every step.&nbsp;<\/p>\n\n\n\n<p>This is what makes AI trustworthy at scale. <a href=\"https:\/\/www.project44.com\/ja\/blog\/scaling-decision-intelligence-how-agentic-analytics-transforms-data-deep-dives\/\">Each agent is accountable for a specific, measurable outcome.<\/a> The orchestrator is accountable for the end-to-end process. When something goes wrong, you know where\u00a0it went wrong,\u00a0why, and which agent was\u00a0responsible.\u00a0\u00a0<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-what-nbsp-cannot-be-shortcut-data-and-nbsp-domain-nbsp-expertise-nbsp\"><strong>What&nbsp;cannot be shortcut: Data and&nbsp;domain&nbsp;expertise<\/strong>&nbsp;<\/h2>\n\n\n\n<p>This architecture only works if&nbsp;it\u2019s&nbsp;built on two foundations that take years to develop and&nbsp;can\u2019t&nbsp;be shortcut.&nbsp;<\/p>\n\n\n\n<p>The first is network-scale, validated&nbsp;data. An AI agent is only as trustworthy&nbsp;as the data it&nbsp;reasons from. Incomplete on-time performance data produces unreliable outputs regardless&nbsp;of how well the agent is&nbsp;designed. Lane-level data that&nbsp;doesn\u2019t&nbsp;account for seasonal patterns&nbsp;generates&nbsp;recommendations that look reasonable and fail in practice.&nbsp;&nbsp;<\/p>\n\n\n\n<p>The second is deep domain&nbsp;expertise, operationalized as semantics. The semantic framework for carrier selection&nbsp;isn\u2019t&nbsp;built by reading industry reports.&nbsp;It\u2019s&nbsp;built by spending years alongside freight brokers,&nbsp;logistics&nbsp;directors, and operations managers,&nbsp;learning not just what data they use, but how they&nbsp;weight&nbsp;it,&nbsp;what edge cases catch them, and what&nbsp;they\u2019ve&nbsp;learned&nbsp;the hard way.&nbsp;<\/p>\n\n\n\n<p>At project44, we operationalize this through a deliberate triad: domain experts (industry advisors, in-house veterans, and our customers&nbsp;who live with the consequences of these decisions every day), translators who convert domain knowledge into product requirements, and engineers who build the systems and feedback loops that let each skill compound over time.&nbsp;<\/p>\n\n\n\n<p>The&nbsp;instinct a&nbsp;veteran&nbsp;builds&nbsp;over twenty years,&nbsp;knowing within seconds which carrier to trust on which lane, becomes a permanent part of&nbsp;infrastructure.&nbsp;&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-the-nbsp-final-nbsp-piece-nbsp-proof-and-nbsp-identity-nbsp\"><strong>The&nbsp;final&nbsp;piece:&nbsp;Proof and&nbsp;identity<\/strong>&nbsp;<\/h2>\n\n\n\n<p>Context. Skills. Orchestration.&nbsp;Get all of these right and you have AI that is genuinely capable of operating in complex, high-stakes environments.&nbsp;<\/p>\n\n\n\n<p>But&nbsp;capable&nbsp;is&nbsp;not&nbsp;the same as&nbsp;trusted. Not yet.&nbsp;<\/p>\n\n\n\n<p>The question that will&nbsp;determine&nbsp;whether enterprises&nbsp;can&nbsp;hand real authority to AI systems is one of proof and identity.&nbsp;How do you&nbsp;know&nbsp;the agent that executed a decision is the one you authorized? How do you produce an audit trail that satisfies a procurement team, a regulator, or a customer asking why a decision was made? How do you&nbsp;establish&nbsp;chain&nbsp;of custody for automated action in environments where accountability is non-negotiable?&nbsp;<\/p>\n\n\n\n<p>These&nbsp;aren\u2019t&nbsp;abstract&nbsp;questions. They are the practical barriers&nbsp;standing between impressive AI pilots and deployment at scale.&nbsp;<\/p>\n\n\n\n<p>Context is the foundation. Skills&nbsp;are what you build&nbsp;on&nbsp;it.&nbsp;Proof and identity are what make&nbsp;it&nbsp;enterprise-grade.&nbsp;<\/p>\n\n\n\n<p>We will cover this important topic in our next piece.&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The barrier to enterprise AI\u00a0i&#8230;<\/p>\n","protected":false},"author":77,"featured_media":78193,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","footnotes":""},"categories":[1450],"tags":[],"blog_type":[],"class_list":["post-78192","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-1450"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.5 (Yoast SEO v27.5) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>How to build trust in AI at enterprise scale | project44<\/title>\n<meta name=\"description\" content=\"Discover how focused tasks, specialized agents, and clean data build enterprise AI trust in supply chain, where one wrong decision can cost a customer relationship.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How to build trust in AI at enterprise scale\" \/>\n<meta property=\"og:description\" content=\"Discover how focused tasks, specialized agents, and clean data build enterprise AI trust in supply chain, where one wrong decision can cost a customer relationship.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/\" \/>\n<meta property=\"og:site_name\" content=\"project44\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/project44Visibility\" \/>\n<meta property=\"article:published_time\" content=\"2026-04-06T15:31:12+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-04-06T15:31:24+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.project44.com\/wp-content\/uploads\/2026\/04\/GettyImages-2156904331-scaled.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"1707\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Evamarie Joubert\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@freightpipes\" \/>\n<meta name=\"twitter:site\" content=\"@freightpipes\" \/>\n<meta name=\"twitter:label1\" content=\"\u57f7\u7b46\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"Evamarie Joubert\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u63a8\u5b9a\u8aad\u307f\u53d6\u308a\u6642\u9593\" \/>\n\t<meta name=\"twitter:data2\" content=\"8\u5206\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/how-to-build-trust-in-ai-at-enterprise-scale\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/how-to-build-trust-in-ai-at-enterprise-scale\\\/\"},\"author\":{\"name\":\"Evamarie Joubert\",\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/#\\\/schema\\\/person\\\/f6c00e9b5099fb094711ef65d446534a\"},\"headline\":\"How to build trust in AI at enterprise scale\",\"datePublished\":\"2026-04-06T15:31:12+00:00\",\"dateModified\":\"2026-04-06T15:31:24+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/how-to-build-trust-in-ai-at-enterprise-scale\\\/\"},\"wordCount\":1836,\"publisher\":{\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/how-to-build-trust-in-ai-at-enterprise-scale\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.project44.com\\\/wp-content\\\/uploads\\\/2026\\\/04\\\/GettyImages-2156904331-scaled.jpg\",\"articleSection\":[\"\u610f\u601d\u6c7a\u5b9a\u30a4\u30f3\u30c6\u30ea\u30b8\u30a7\u30f3\u30b9\"],\"inLanguage\":\"ja\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/how-to-build-trust-in-ai-at-enterprise-scale\\\/\",\"url\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/how-to-build-trust-in-ai-at-enterprise-scale\\\/\",\"name\":\"How to build trust in AI at enterprise scale | project44\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/how-to-build-trust-in-ai-at-enterprise-scale\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/how-to-build-trust-in-ai-at-enterprise-scale\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.project44.com\\\/wp-content\\\/uploads\\\/2026\\\/04\\\/GettyImages-2156904331-scaled.jpg\",\"datePublished\":\"2026-04-06T15:31:12+00:00\",\"dateModified\":\"2026-04-06T15:31:24+00:00\",\"description\":\"Discover how focused tasks, specialized agents, and clean data build enterprise AI trust in supply chain, where one wrong decision can cost a customer relationship.\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/how-to-build-trust-in-ai-at-enterprise-scale\\\/#breadcrumb\"},\"inLanguage\":\"ja\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/how-to-build-trust-in-ai-at-enterprise-scale\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"ja\",\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/how-to-build-trust-in-ai-at-enterprise-scale\\\/#primaryimage\",\"url\":\"https:\\\/\\\/www.project44.com\\\/wp-content\\\/uploads\\\/2026\\\/04\\\/GettyImages-2156904331-scaled.jpg\",\"contentUrl\":\"https:\\\/\\\/www.project44.com\\\/wp-content\\\/uploads\\\/2026\\\/04\\\/GettyImages-2156904331-scaled.jpg\",\"width\":2560,\"height\":1707},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/how-to-build-trust-in-ai-at-enterprise-scale\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"How to build trust in AI at enterprise scale\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/#website\",\"url\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/\",\"name\":\"project44\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"ja\"},{\"@type\":\"Organization\",\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/#organization\",\"name\":\"project44\",\"url\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"ja\",\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/#\\\/schema\\\/logo\\\/image\\\/\",\"url\":\"https:\\\/\\\/www.project44.com\\\/wp-content\\\/uploads\\\/2024\\\/01\\\/logo.svg\",\"contentUrl\":\"https:\\\/\\\/www.project44.com\\\/wp-content\\\/uploads\\\/2024\\\/01\\\/logo.svg\",\"width\":213,\"height\":73,\"caption\":\"project44\"},\"image\":{\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/#\\\/schema\\\/logo\\\/image\\\/\"},\"sameAs\":[\"https:\\\/\\\/www.facebook.com\\\/project44Visibility\",\"https:\\\/\\\/x.com\\\/freightpipes\",\"https:\\\/\\\/www.linkedin.com\\\/company\\\/project-44\",\"https:\\\/\\\/www.instagram.com\\\/project44global\"]},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/#\\\/schema\\\/person\\\/f6c00e9b5099fb094711ef65d446534a\",\"name\":\"Evamarie Joubert\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"ja\",\"@id\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/24bca9a9a9ddc74057eba8cb1a4b2dfac2b96f80cb3ed58588b2076c64804fcb?s=96&d=mm&r=g\",\"url\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/24bca9a9a9ddc74057eba8cb1a4b2dfac2b96f80cb3ed58588b2076c64804fcb?s=96&d=mm&r=g\",\"contentUrl\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/24bca9a9a9ddc74057eba8cb1a4b2dfac2b96f80cb3ed58588b2076c64804fcb?s=96&d=mm&r=g\",\"caption\":\"Evamarie Joubert\"},\"url\":\"https:\\\/\\\/www.project44.com\\\/ja\\\/blog\\\/author\\\/ejoubert\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"How to build trust in AI at enterprise scale | project44","description":"Discover how focused tasks, specialized agents, and clean data build enterprise AI trust in supply chain, where one wrong decision can cost a customer relationship.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/","og_locale":"ja_JP","og_type":"article","og_title":"How to build trust in AI at enterprise scale","og_description":"Discover how focused tasks, specialized agents, and clean data build enterprise AI trust in supply chain, where one wrong decision can cost a customer relationship.","og_url":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/","og_site_name":"project44","article_publisher":"https:\/\/www.facebook.com\/project44Visibility","article_published_time":"2026-04-06T15:31:12+00:00","article_modified_time":"2026-04-06T15:31:24+00:00","og_image":[{"width":2560,"height":1707,"url":"https:\/\/www.project44.com\/wp-content\/uploads\/2026\/04\/GettyImages-2156904331-scaled.jpg","type":"image\/jpeg"}],"author":"Evamarie Joubert","twitter_card":"summary_large_image","twitter_creator":"@freightpipes","twitter_site":"@freightpipes","twitter_misc":{"\u57f7\u7b46\u8005":"Evamarie Joubert","\u63a8\u5b9a\u8aad\u307f\u53d6\u308a\u6642\u9593":"8\u5206"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/#article","isPartOf":{"@id":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/"},"author":{"name":"Evamarie Joubert","@id":"https:\/\/www.project44.com\/ja\/#\/schema\/person\/f6c00e9b5099fb094711ef65d446534a"},"headline":"How to build trust in AI at enterprise scale","datePublished":"2026-04-06T15:31:12+00:00","dateModified":"2026-04-06T15:31:24+00:00","mainEntityOfPage":{"@id":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/"},"wordCount":1836,"publisher":{"@id":"https:\/\/www.project44.com\/ja\/#organization"},"image":{"@id":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/#primaryimage"},"thumbnailUrl":"https:\/\/www.project44.com\/wp-content\/uploads\/2026\/04\/GettyImages-2156904331-scaled.jpg","articleSection":["\u610f\u601d\u6c7a\u5b9a\u30a4\u30f3\u30c6\u30ea\u30b8\u30a7\u30f3\u30b9"],"inLanguage":"ja"},{"@type":"WebPage","@id":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/","url":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/","name":"How to build trust in AI at enterprise scale | project44","isPartOf":{"@id":"https:\/\/www.project44.com\/ja\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/#primaryimage"},"image":{"@id":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/#primaryimage"},"thumbnailUrl":"https:\/\/www.project44.com\/wp-content\/uploads\/2026\/04\/GettyImages-2156904331-scaled.jpg","datePublished":"2026-04-06T15:31:12+00:00","dateModified":"2026-04-06T15:31:24+00:00","description":"Discover how focused tasks, specialized agents, and clean data build enterprise AI trust in supply chain, where one wrong decision can cost a customer relationship.","breadcrumb":{"@id":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/#breadcrumb"},"inLanguage":"ja","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/"]}]},{"@type":"ImageObject","inLanguage":"ja","@id":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/#primaryimage","url":"https:\/\/www.project44.com\/wp-content\/uploads\/2026\/04\/GettyImages-2156904331-scaled.jpg","contentUrl":"https:\/\/www.project44.com\/wp-content\/uploads\/2026\/04\/GettyImages-2156904331-scaled.jpg","width":2560,"height":1707},{"@type":"BreadcrumbList","@id":"https:\/\/www.project44.com\/ja\/blog\/how-to-build-trust-in-ai-at-enterprise-scale\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.project44.com\/ja\/"},{"@type":"ListItem","position":2,"name":"How to build trust in AI at enterprise scale"}]},{"@type":"WebSite","@id":"https:\/\/www.project44.com\/ja\/#website","url":"https:\/\/www.project44.com\/ja\/","name":"project44","description":"","publisher":{"@id":"https:\/\/www.project44.com\/ja\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.project44.com\/ja\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"ja"},{"@type":"Organization","@id":"https:\/\/www.project44.com\/ja\/#organization","name":"project44","url":"https:\/\/www.project44.com\/ja\/","logo":{"@type":"ImageObject","inLanguage":"ja","@id":"https:\/\/www.project44.com\/ja\/#\/schema\/logo\/image\/","url":"https:\/\/www.project44.com\/wp-content\/uploads\/2024\/01\/logo.svg","contentUrl":"https:\/\/www.project44.com\/wp-content\/uploads\/2024\/01\/logo.svg","width":213,"height":73,"caption":"project44"},"image":{"@id":"https:\/\/www.project44.com\/ja\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/project44Visibility","https:\/\/x.com\/freightpipes","https:\/\/www.linkedin.com\/company\/project-44","https:\/\/www.instagram.com\/project44global"]},{"@type":"Person","@id":"https:\/\/www.project44.com\/ja\/#\/schema\/person\/f6c00e9b5099fb094711ef65d446534a","name":"Evamarie Joubert","image":{"@type":"ImageObject","inLanguage":"ja","@id":"https:\/\/secure.gravatar.com\/avatar\/24bca9a9a9ddc74057eba8cb1a4b2dfac2b96f80cb3ed58588b2076c64804fcb?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/24bca9a9a9ddc74057eba8cb1a4b2dfac2b96f80cb3ed58588b2076c64804fcb?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/24bca9a9a9ddc74057eba8cb1a4b2dfac2b96f80cb3ed58588b2076c64804fcb?s=96&d=mm&r=g","caption":"Evamarie Joubert"},"url":"https:\/\/www.project44.com\/ja\/blog\/author\/ejoubert\/"}]}},"_links":{"self":[{"href":"https:\/\/www.project44.com\/ja\/wp-json\/wp\/v2\/posts\/78192","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.project44.com\/ja\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.project44.com\/ja\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.project44.com\/ja\/wp-json\/wp\/v2\/users\/77"}],"replies":[{"embeddable":true,"href":"https:\/\/www.project44.com\/ja\/wp-json\/wp\/v2\/comments?post=78192"}],"version-history":[{"count":6,"href":"https:\/\/www.project44.com\/ja\/wp-json\/wp\/v2\/posts\/78192\/revisions"}],"predecessor-version":[{"id":78234,"href":"https:\/\/www.project44.com\/ja\/wp-json\/wp\/v2\/posts\/78192\/revisions\/78234"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.project44.com\/ja\/wp-json\/wp\/v2\/media\/78193"}],"wp:attachment":[{"href":"https:\/\/www.project44.com\/ja\/wp-json\/wp\/v2\/media?parent=78192"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.project44.com\/ja\/wp-json\/wp\/v2\/categories?post=78192"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.project44.com\/ja\/wp-json\/wp\/v2\/tags?post=78192"},{"taxonomy":"blog_type","embeddable":true,"href":"https:\/\/www.project44.com\/ja\/wp-json\/wp\/v2\/blog_type?post=78192"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}