{"id":39778,"date":"2026-06-30T10:47:36","date_gmt":"2026-06-30T10:47:36","guid":{"rendered":"https:\/\/smartdev.com\/?p=39778"},"modified":"2026-06-30T10:47:36","modified_gmt":"2026-06-30T10:47:36","slug":"your-ai-vendor-is-now-a-mas-third-party-risk-heres-what-your-auditor-will-ask","status":"publish","type":"post","link":"https:\/\/smartdev.com\/jp\/your-ai-vendor-is-now-a-mas-third-party-risk-heres-what-your-auditor-will-ask\/","title":{"rendered":"Your AI Vendor Is Now a MAS Third-Party Risk Here&#8217;s What Your Auditor Will Ask"},"content":{"rendered":"<div id=\"fws_6a443479ac82b\"  data-column-margin=\"default\" data-midnight=\"dark\"  class=\"wpb_row vc_row-fluid vc_row\"  style=\"padding-top: 0px; padding-bottom: 0px; \"><div class=\"row-bg-wrap\" data-bg-animation=\"none\" data-bg-animation-delay=\"\" data-bg-overlay=\"false\"><div class=\"inner-wrap row-bg-layer\" ><div class=\"row-bg viewport-desktop\"  style=\"\"><\/div><\/div><\/div><div class=\"row_col_wrap_12 col span_12 dark left\">\n\t<div  class=\"vc_col-sm-12 wpb_column column_container vc_column_container col no-extra-padding inherit_tablet inherit_phone flex_gap_desktop_10px\"  data-padding-pos=\"all\" data-has-bg-color=\"false\" data-bg-color=\"\" data-bg-opacity=\"1\" data-animation=\"\" data-delay=\"0\" >\n\t\t<div class=\"vc_column-inner\" >\n\t\t\t<div class=\"wpb_wrapper\">\n\t\t\t\t\n<div class=\"wpb_text_column wpb_content_element\" >\n\t<h3 aria-level=\"3\"><span class=\"ez-toc-section\" id=\"TLDR\"><\/span><b><span data-contrast=\"auto\">TL;DR<\/span><\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"21\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559683&quot;:0,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">AI vendors are now enterprise third-party risks.\u00a0Under MAS expectations, organizations stay accountable for vendor data handling, automated decisions, and critical processes.\u00a0<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"21\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559683&quot;:0,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Traditional due diligence is no longer enough.\u00a0Enterprises must assess AI-specific risks like transparency, governance, data usage, and human oversight.\u00a0<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"21\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559683&quot;:0,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Auditors now expect AI governance evidence.\u00a0This includes AI use, data protection, model governance, resilience, and supply chain risk.\u00a0<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"21\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559683&quot;:0,&quot;335559684&quot;:-2,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Governed AI workflows build trust. Audit trails, explainable outputs, human oversight, and compliance-ready evidence help enterprises adopt AI confidently.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-39779 size-full\" src=\"https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/1-62.png\" alt=\"\" width=\"1920\" height=\"1080\" srcset=\"https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/1-62.png 1920w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/1-62-300x169.png 300w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/1-62-1024x576.png 1024w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/1-62-768x432.png 768w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/1-62-1536x864.png 1536w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/1-62-18x10.png 18w\" sizes=\"auto, (max-width: 1920px) 100vw, 1920px\" \/><\/p>\n<h3 aria-level=\"3\"><span class=\"ez-toc-section\" id=\"Introduction\"><\/span><b><span data-contrast=\"auto\">Introduction<\/span><\/b><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<div class=\"qMYqUG_convSearchResultHighlightRoot\">\n<div class=\"\" data-turn-id-container=\"request-6a3f435d-eb84-83ec-87e7-23fca564f5c5-4\" data-is-intersecting=\"true\">\n<section class=\"text-token-text-primary w-full focus:outline-none has-data-writing-block:pointer-events-none &#091;&amp;:has(&#091;data-writing-block&#093;)&gt;*&#093;:pointer-events-auto R6Vx5W_threadScrollVars scroll-mb-&#091;calc(var(--scroll-root-safe-area-inset-bottom,0px)+var(--thread-response-height))&#093; scroll-mt-&#091;calc(var(--header-height)+min(200px,max(70px,20svh)))&#093;\" dir=\"auto\" data-turn-id=\"request-6a3f435d-eb84-83ec-87e7-23fca564f5c5-4\" data-turn-id-container=\"request-6a3f435d-eb84-83ec-87e7-23fca564f5c5-4\" data-testid=\"conversation-turn-62\" data-turn=\"assistant\">\n<div class=\"text-base my-auto mx-auto pb-10 &#091;--thread-content-margin:var(--thread-content-margin-xs,calc(var(--spacing)*4))&#093; @w-sm\/main:&#091;--thread-content-margin:var(--thread-content-margin-sm,calc(var(--spacing)*6))&#093; @w-lg\/main:&#091;--thread-content-margin:var(--thread-content-margin-lg,calc(var(--spacing)*16))&#093; px-(--thread-content-margin)\">\n<div class=\"&#091;--thread-content-max-width:40rem&#093; @w-lg\/main:&#091;--thread-content-max-width:48rem&#093; mx-auto max-w-(--thread-content-max-width) flex-1 group\/turn-messages focus-visible:outline-hidden relative flex w-full min-w-0 flex-col agent-turn\" data-conversation-screenshot-content=\"\">\n<div class=\"flex max-w-full flex-col gap-4 grow\">\n<div class=\"min-h-8 text-message relative flex w-full flex-col items-end gap-2 text-start break-words whitespace-normal outline-none keyboard-focused:focus-ring &#091;.text-message+&amp;&#093;:mt-1\" dir=\"auto\" tabindex=\"0\" data-message-author-role=\"assistant\" data-message-id=\"c2fa9549-c625-42b6-9a42-7a31617e3731\" data-message-model-slug=\"gpt-5-5\" data-turn-start-message=\"true\">\n<div class=\"flex w-full flex-col gap-1 empty:hidden\">\n<div class=\"markdown prose dark:prose-invert wrap-break-word w-full dark markdown-new-styling\">\n<p class=\"PDq2pG_selectionAnchorContainer\" data-start=\"0\" data-end=\"508\" data-is-last-node=\"\" data-is-only-node=\"\">Artificial intelligence is now central to enterprise operations, with organizations relying on third-party vendors for automation, decision-making, and productivity gains. As AI becomes embedded in outsourced software and services, AI risk increasingly overlaps with third-party risk. Vendors that handle sensitive data or support critical processes introduce new regulatory and security risks, making it essential for organizations to understand not only whether vendors use AI, but also how they govern it.<\/p>\n<p class=\"PDq2pG_selectionAnchorContainer\" data-start=\"0\" data-end=\"508\" data-is-last-node=\"\" data-is-only-node=\"\"><span data-contrast=\"auto\">This concern is no longer theoretical. <\/span><a href=\"https:\/\/www.ibm.com\/reports\/data-breach\"><span data-contrast=\"none\">IBM\u2019s 2025 Cost of a Data Breach Report<\/span><\/a><span data-contrast=\"auto\">\u00a0found\u00a0that shadow AI was involved in 20% of data breaches, while\u00a0<\/span><a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2025-11-19-gartner-identifies-critical-genai-blind-spots-that-cios-must-urgently-address0\"><span data-contrast=\"none\">Gartner<\/span><\/a><span data-contrast=\"auto\">\u00a0predicts that more than 40% of enterprises will face a security or compliance incident linked to unauthorized AI use by 2030. For organizations regulated by the Monetary Authority of Singapore (MAS), this shift carries significant implications. AI vendors are increasingly treated as part of the third-party risk landscape and are subject to the same level of scrutiny as other critical providers.<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n<\/div>\n<\/div>\n<p><span data-contrast=\"auto\">During audits, organizations must demonstrate not only the value of their AI solutions but also how they govern, secure, and oversee them. In the sections that follow, we examine why AI vendors are regarded as third-party risks under MAS expectations, outline the key areas auditors focus on, and discuss how organizations can develop AI strategies that strengthen regulatory confidence.<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<h3 aria-level=\"3\"><span class=\"ez-toc-section\" id=\"Why_MAS_treats_AI_Vendor_as_Third-Party_Risk\"><\/span><b><span data-contrast=\"auto\">Why MAS treats AI Vendor as Third-Party Risk<\/span><\/b><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><a href=\"https:\/\/www.lseg.com\/en\/risk-intelligence\/glossary\/regulatory-compliance\/mas\"><span data-contrast=\"none\">The Monetary Authority of Singapore (MAS)\u00a0<\/span><\/a><span data-contrast=\"auto\">is Singapore\u2019s central bank and financial regulator, responsible for overseeing banks, insurers, capital markets, and other financial institutions.\u00a0<\/span><a href=\"https:\/\/www.bakermckenzie.com\/en\/insight\/publications\/2026\/03\/singapore-mas-proposes-updated-guidelines-on-operational-risk-management\"><span data-contrast=\"none\">MAS guidelines<\/span><\/a><span data-contrast=\"auto\">\u00a0apply broadly to regulated financial institutions\u00a0operating\u00a0in Singapore, including banks, payment service providers, asset managers, and fintech companies. A key expectation under\u00a0<\/span><a href=\"https:\/\/qualysec.com\/mas-compliance\/\"><span data-contrast=\"none\">MAS regulations<\/span><\/a><span data-contrast=\"auto\">\u00a0is that these institutions must manage risks arising from outsourcing and third-party service providers &#8211; commonly referred to as third-party risk.<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Third-party risk refers to the potential impact that\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/vendor-relationship-management-building-trust-growth\/\"><span data-contrast=\"none\">external vendor<\/span><\/a><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">or service providers can have on an organization\u2019s operations,\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/glossary-data-security\/\"><span data-contrast=\"none\">data security<\/span><\/a><span data-contrast=\"auto\">,\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/ai-compliance-audit-trail\/\"><span data-contrast=\"none\">compliance<\/span><\/a><span data-contrast=\"auto\">, and overall risk profile. When a financial institution relies on a vendor to perform critical functions or handle sensitive information, it\u00a0remains\u00a0accountable for any risks or failures that arise from that relationship.<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">As AI becomes increasingly embedded in enterprise software and managed services, these expectations naturally extend to\u00a0<\/span><a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2025-09-29-gartner-says-ai-vendor-race-is-reshaping-competition-across-the-entire-ai-technology-stack\"><span data-contrast=\"none\">AI vendors<\/span><\/a><span data-contrast=\"auto\">. Unlike traditional software,\u00a0<\/span><a href=\"https:\/\/www.atlassian.com\/blog\/artificial-intelligence\/ai-solutions\"><span data-contrast=\"none\">AI-powered solutions<\/span><\/a><span data-contrast=\"auto\">\u00a0often process sensitive data, generate business recommendations, or automate decisions that were previously performed by employees. Many third-party vendors have also embedded AI capabilities into their products or internal service delivery without customers fully understanding when, where, or how AI is being used. This lack of visibility creates new risks around data governance, security, explainability, and regulatory compliance.<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<p>Traditional vendor<span data-contrast=\"auto\">due diligence is no longer sufficient. Reports such as\u00a0<\/span><a href=\"https:\/\/www.fortinet.com\/resources\/cyberglossary\/soc-2-compliance\"><span data-contrast=\"none\">SOC 2<\/span><\/a><span data-contrast=\"auto\">\u00a0or standard security questionnaires can demonstrate that a vendor has baseline security controls, but they rarely explain how AI models are used, what data they process, whether customer data is used for model training, or what safeguards exist to prevent inaccurate or unauthorized AI outputs. As a result, organizations must expand\u00a0their\u00a0<\/span><a href=\"https:\/\/www.gartner.com\/en\/legal-compliance\/topics\/third-party-risk-management-tprm\"><span data-contrast=\"none\">third-party risk management programs<\/span><\/a><span data-contrast=\"auto\">\u00a0to include AI-specific assessments, contractual disclosure requirements, and ongoing monitoring of AI use throughout the\u00a0vendor\u00a0relationship.<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<p>From an MAS perspective, the key concern is not simply whether an organization uses AI, but whether it understands and governs the risks that third-party AI vendors introduce. When an AI vendor influences critical operations or accesses regulated information, the organization must treat that vendor as part of its overall risk posture and evaluate it with the same rigor as any other critical service provider.<\/p>\n<h3 aria-level=\"3\"><span class=\"ez-toc-section\" id=\"Key_Dimensions_of_Third-Party_AI_Risk\"><\/span><b><span data-contrast=\"auto\">Key Dimensions of Third-Party AI Risk<\/span><\/b><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span data-contrast=\"auto\">Recognizing AI vendors as third-party risks is only the first step.\u00a0Organizations must also understand<\/span><a href=\"https:\/\/riskpublishing.com\/ai-vendor-risk-assessment-evaluating-third-part\/\"><span data-contrast=\"none\">\u00a0what makes AI vendor risk fundamentally different from traditional third-party risk<\/span><\/a><span data-contrast=\"auto\">.\u00a0Unlike conventional software, AI systems introduce\u00a0additional\u00a0challenges around transparency, accountability, and long-term governance that are not always captured through existing vendor assessments.<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<h4 aria-level=\"4\"><b>Transparency and Explainability<\/b><\/h4>\n<p><span data-contrast=\"auto\">One of the biggest challenges is the<\/span><a href=\"https:\/\/www.ibm.com\/think\/topics\/black-box-ai\"><span data-contrast=\"none\">\u00a0&#8220;black box&#8221;\u00a0<\/span><\/a><span data-contrast=\"auto\">nature of many AI models. Organizations can\u00a0observe\u00a0the outputs an AI system generates but often have little visibility into the underlying models, training data, or decision logic. This makes it difficult to independently assess whether AI-generated outcomes are\u00a0accurate, unbiased, secure, and compliant with regulatory expectations. Without sufficient transparency, organizations may struggle to justify AI-assisted decisions during regulatory reviews or audits.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<h4 aria-level=\"4\"><b>Shared Responsibility<\/b><\/h4>\n<p><span data-contrast=\"auto\">Using\u00a0<\/span><a href=\"https:\/\/www.pwc.com\/us\/en\/tech-effect\/ai-analytics\/responsible-ai-tprm.html\"><span data-contrast=\"none\">a third-party AI service<\/span><\/a><span data-contrast=\"auto\">\u00a0does not transfer accountability to the vendor. While providers are\u00a0generally responsible\u00a0for securing the underlying infrastructure and\u00a0maintaining\u00a0the AI platform, customers\u00a0remain\u00a0responsible for governing user access, protecting their own data,\u00a0validating\u00a0AI outputs, and ensuring that AI is used\u00a0in accordance with\u00a0regulatory requirements. Clearly defining these responsibilities helps prevent governance gaps.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<h4 aria-level=\"4\"><b>Data Residency and Intellectual Property<\/b><\/h4>\n<p><span data-contrast=\"auto\">Organizations should understand where their data is processed and stored, whether it crosses national borders, and how long it is\u00a0retained. They should also clarify whether<\/span><a href=\"https:\/\/techreviewadvisor.com\/what-is-proprietary-data\/\"><span data-contrast=\"none\">\u00a0proprietary data<\/span><\/a><span data-contrast=\"auto\">\u00a0can be used to train or improve the vendor&#8217;s AI models, and who owns any resulting models or generated insights. These considerations are increasingly important for both regulatory compliance and intellectual property protection.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<h4 aria-level=\"4\"><b>Vendor Dependency<\/b><\/h4>\n<p><span data-contrast=\"auto\">As AI becomes embedded in critical business processes, organizations can become highly dependent on a single\u00a0vendor&#8217;s\u00a0models,\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/glossary-api-for-ai-tools\/\"><span data-contrast=\"none\">APIs<\/span><\/a><span data-contrast=\"auto\">, or workflows. This creates operational risk if service quality\u00a0deteriorates,\u00a0pricing changes unexpectedly, or the vendor experiences an outage. Evaluating\u00a0exit strategies\u00a0and portability should therefore form part of every\u00a0<\/span><a href=\"https:\/\/www.atlassystems.com\/blog\/ai-vendor-risk-questionnaire\"><span data-contrast=\"none\">AI\u00a0vendor\u00a0assessment.<\/span><\/a><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Understanding these dimensions provides the foundation for effective third-party AI risk management. They also explain why auditors increasingly look beyond traditional security controls and ask more detailed questions about how AI is governed,\u00a0monitored, and controlled throughout the vendor relationship.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-39780 size-full\" src=\"https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/2-62.png\" alt=\"\" width=\"1920\" height=\"1080\" srcset=\"https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/2-62.png 1920w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/2-62-300x169.png 300w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/2-62-1024x576.png 1024w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/2-62-768x432.png 768w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/2-62-1536x864.png 1536w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/2-62-18x10.png 18w\" sizes=\"auto, (max-width: 1920px) 100vw, 1920px\" \/><\/p>\n<h3 aria-level=\"3\"><span class=\"ez-toc-section\" id=\"Case_study_When_an_AI_vendor_becomes_a_MAS_Third-party_risk\"><\/span><b><span data-contrast=\"auto\">Case study: When an AI vendor becomes a MAS Third-party risk<\/span><\/b><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span data-contrast=\"auto\">To illustrate how these risk dimensions manifest in practice, consider a typical scenario.<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">A Singapore-based fintech adopts an\u00a0<\/span><span data-contrast=\"auto\">AI-powered compliance platform<\/span><span data-contrast=\"auto\">\u00a0to accelerate its<\/span><a href=\"https:\/\/smartdev.com\/jp\/nora-in-ai-powered-soc-2-compliance-enablement\/\"><span data-contrast=\"none\">\u00a0SOC 2\u00a0readiness<\/span><\/a><span data-contrast=\"auto\">. The platform automates the collection of evidence from cloud environments, reviews internal policies, summarizes security documentation, and generates draft compliance reports to support audit preparation.<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">While it may initially appear to be\u00a0<\/span>a<a href=\"https:\/\/www.sap.com\/resources\/what-is-saas\"><span data-contrast=\"none\">\u00a0standard SaaS application<\/span><\/a><span data-contrast=\"auto\">, the platform performs critical compliance functions and has access to regulated information. It processes security policies, employee records,\u00a0<\/span><a href=\"https:\/\/www.wiz.io\/academy\/cloud-security\/cloud-configuration-management\"><span data-contrast=\"none\">cloud configurations<\/span><\/a><span data-contrast=\"auto\">, access logs, and other sensitive operational data. It also contributes to decisions that support regulatory reporting and audit readiness.<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<p>At this stage, the AI platform no longer functions as just another software tool &#8211; it becomes an integral part of the organization&#8217;s third-party risk landscape. Organizations must understand not only what the platform does, but also how it processes data, generates outputs, and supports business decisions. They need to know where data is stored, whether customer information trains AI models, how the platform validates AI-generated outputs, who can access sensitive information, and whether they can explain and justify AI-assisted decisions during regulatory reviews.<\/p>\n<p><span data-contrast=\"auto\">This scenario highlights why traditional vendor due diligence is no longer sufficient. Security certifications such as SOC 2 or<\/span><b><span data-contrast=\"auto\">\u00a0<\/span><\/b><a href=\"https:\/\/smartdev.com\/jp\/smartdev-achieved-iso-iec-27001-2022\/\"><span data-contrast=\"none\">ISO 27001<\/span><\/a><span data-contrast=\"auto\">\u00a0demonstrate\u00a0that a vendor has implemented baseline security controls; however, they do not address AI-specific considerations such as transparency, governance, data usage, or human oversight. For<\/span><span data-contrast=\"auto\">\u00a0MAS-regulated organizations<\/span><span data-contrast=\"auto\">, accountability\u00a0ultimately rests\u00a0with the financial institution\u00a0&#8211;\u00a0not the vendor\u00a0&#8211;\u00a0to\u00a0demonstrate\u00a0that these risks are properly understood and effectively managed.<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">This leads to the next critical question:<\/span><span data-contrast=\"auto\">\u00a0What evidence will auditors expect to see?<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<h3 aria-level=\"3\"><span class=\"ez-toc-section\" id=\"The_audit_questions_your_AI_vendor_must_be_ready_to_answer\"><\/span><b><span data-contrast=\"auto\">The audit questions your AI vendor must be ready to answer<\/span><\/b><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Understanding the risks is only half the challenge. During audits, regulators expect organizations to demonstrate proper due diligence before deploying AI in critical business processes. Rather than asking whether AI is used, auditors increasingly focus on how organizations govern, monitor, and control AI throughout the vendor relationship.<\/p>\n<p><span data-contrast=\"auto\">Below are the key areas auditors are most likely to examine, along with examples of the specific questions that typically fall under each theme.<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1,&quot;335551620&quot;:1}\">\u00a0<\/span><\/p>\n<h4 aria-level=\"4\"><b>How Is AI\u00a0Being Used?<\/b><\/h4>\n<p><span data-contrast=\"auto\">Before diving into specific questions, auditors first need to understand\u00a0why AI usage matters in the context of risk and compliance. The role AI plays within a vendor\u2019s service directly influences the level of oversight\u00a0required.\u00a0For example, AI used in internal automation carries\u00a0a very different\u00a0<\/span><a href=\"https:\/\/www.techtarget.com\/searchsecurity\/definition\/risk-profile\"><span data-contrast=\"none\">risk profile<\/span><\/a><span data-contrast=\"auto\">\u00a0compared to AI that makes customer-facing decisions or supports regulated processes.\u00a0Without a clear understanding of how AI is embedded in the service, auditors cannot accurately assess exposure, control requirements, or potential impact on business outcomes.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Common questions\u00a0in this area include:<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"11\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Does your organization use AI or\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/glossary-machine-learning\/\"><span data-contrast=\"none\">machine learning<\/span><\/a><span data-contrast=\"auto\">\u00a0to deliver any part of the service?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"12\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Which systems or business functions rely on AI?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"13\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">What types of AI models are deployed (e.g.,\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/glossary-generative-ai\/\"><span data-contrast=\"none\">generative AI<\/span><\/a><span data-contrast=\"auto\">, predictive analytics, NLP)?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"14\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Is AI customer-facing or used only internally?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"14\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Are there plans to introduce new AI capabilities\u00a0in the near future?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<h4 aria-level=\"4\"><b>How Is Organizational Data Protected?<\/b><\/h4>\n<p><a href=\"https:\/\/smartdev.com\/jp\/glossary-data-security\/\"><span data-contrast=\"none\">Data protection<\/span><\/a><span data-contrast=\"auto\">\u00a0is a central concern because AI\u00a0systems often rely on large volumes of sensitive information. Auditors need to understand\u00a0how data flows through the\u00a0<\/span><a href=\"https:\/\/www.datascience-pm.com\/ai-lifecycle\/\"><span data-contrast=\"none\">AI lifecycle<\/span><\/a><span data-contrast=\"auto\">, including collection, processing, storage, and potential sharing with third parties. This is critical for ensuring compliance with privacy regulations, contractual obligations, and data residency requirements. If data handling practices are unclear or poorly controlled, organizations risk regulatory violations and loss of customer trust.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Typical questions include:<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">What types of data are processed by the AI system?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Will customer or proprietary data be used to train or improve AI models?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Where is data stored and processed?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Is data shared with external AI providers such as\u00a0<\/span><a href=\"https:\/\/tech-insider.org\/anthropic-vs-openai-2026\/\"><span data-contrast=\"none\">OpenAI or Anthropic<\/span><\/a><span data-contrast=\"auto\">?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"15\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">What retention and deletion policies are in place?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<h4 aria-level=\"4\"><b>Can the AI System Be Trusted?<\/b><\/h4>\n<p>Auditors do not assume AI outputs are reliable. They assess whether organizations ensure accuracy, fairness, and explainability. Trust is critical in regulated environments where decisions must be defensible. Without validation and oversight, AI can create bias, errors, compliance risks, and reputational damage.<\/p>\n<p><span data-contrast=\"auto\">Auditors often ask:<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"16\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Can you explain how AI-generated decisions or recommendations are produced?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"16\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">How are AI models tested for accuracy, bias, and fairness before deployment?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"16\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">How is model performance\u00a0monitored\u00a0over time?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"16\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">What controls exist to\u00a0validate\u00a0AI outputs before they influence decisions?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"16\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">Are there documented processes for reviewing and approving AI outputs?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<h4 aria-level=\"4\"><b>Are Security Controls Sufficient?<\/b><\/h4>\n<p><span data-contrast=\"auto\">AI systems introduce new technical risks that extend beyond<\/span><b><span data-contrast=\"auto\">\u00a0<\/span><\/b><a href=\"https:\/\/www.zscaler.com\/zpedia\/ai-vs-traditional-cybersecurity\"><span data-contrast=\"none\">traditional cybersecurity<\/span><\/a><b><span data-contrast=\"auto\">\u00a0<\/span><\/b><span data-contrast=\"auto\">concerns<\/span><b><span data-contrast=\"auto\">.<\/span><\/b><span data-contrast=\"auto\">\u00a0Auditors need to understand\u00a0whether\u00a0appropriate safeguards\u00a0are in place to protect AI systems from misuse, manipulation, or unauthorized access. This includes both<\/span><b><span data-contrast=\"auto\">\u00a0<\/span><\/b><span data-contrast=\"auto\">standard security practices<\/span><b><span data-contrast=\"auto\">\u00a0<\/span><\/b><span data-contrast=\"auto\">and controls specific to AI-related threats. Strong security measures\u00a0demonstrate\u00a0that the organization can protect sensitive data and\u00a0maintain\u00a0system integrity throughout the AI lifecycle.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Questions in this area may include:<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"20\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">How is access to AI systems controlled (e.g., role-based access,\u00a0<\/span><a href=\"https:\/\/www.microsoft.com\/en-us\/security\/business\/security-101\/what-is-multifactor-authentication-mfa?msockid=26894247098f64df0ec45127089d65d0\"><span data-contrast=\"none\">MFA<\/span><\/a><span data-contrast=\"auto\">)?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"20\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Are prompts, inputs, and outputs encrypted?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"20\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">How do you protect against AI-specific threats such as\u00a0<\/span><a href=\"https:\/\/blog.cyberdesserts.com\/prompt-injection-attacks\/\"><span data-contrast=\"none\">prompt injection<\/span><\/a><span data-contrast=\"auto\">\u00a0or<\/span><a href=\"https:\/\/www.bing.com\/search?q=data%20poisoning&amp;qs=n&amp;form=QBRE&amp;sp=-1&amp;ghc=2&amp;lq=0&amp;pq=data%20poisoning&amp;sc=9-14&amp;sk=&amp;cvid=E55BB04A72A845A3B9AC51913AE11BCF\"><span data-contrast=\"none\">\u00a0data poisoning<\/span><\/a><span data-contrast=\"auto\">?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"20\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Is AI activity continuously\u00a0monitored\u00a0for anomalies or misuse?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"20\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">What logging and alerting mechanisms are in place?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<h4 aria-level=\"4\"><b>Can the Vendor Demonstrate Regulatory Compliance?<\/b><\/h4>\n<p>As AI regulations evolve, auditors expect vendors to prove alignment with recognized frameworks. Policies alone are not enough. Vendors must show that AI systems operate transparently, traceably, and accountably. Organizations must defend their AI use during audits and regulatory reviews.<\/p>\n<p><span data-contrast=\"auto\">Auditors may ask:<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"17\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Do you align with frameworks such as\u00a0<\/span><a href=\"https:\/\/www.iso.org\/standard\/42001\"><span data-contrast=\"none\">ISO\/IEC 42001<\/span><\/a><span data-contrast=\"auto\">,\u00a0<\/span><a href=\"https:\/\/www.nist.gov\/itl\/ai-risk-management-framework\"><span data-contrast=\"none\">NIST AI RMF<\/span><\/a><span data-contrast=\"auto\">, or the\u00a0<\/span><a href=\"https:\/\/www.lw.com\/en\/insights\/ai-act-update-eu-resolves-to-change-rules-and-extend-deadlines\"><span data-contrast=\"none\">EU AI Act<\/span><\/a><span data-contrast=\"auto\">?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"17\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Can you provide documentation of\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/glossary-ai-governance\/\"><span data-contrast=\"none\">AI governance<\/span><\/a><span data-contrast=\"auto\">\u00a0policies and risk assessments?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"17\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Are AI decisions logged and auditable?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"17\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Can outputs be traced back to supporting data and logic?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"17\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">What evidence can you provide to\u00a0demonstrate\u00a0compliance?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<h4 aria-level=\"4\"><b>What Happens If the AI System Fails?<\/b><\/h4>\n<p><span data-contrast=\"auto\">Operational resilience is a critical\u00a0component\u00a0of\u00a0<\/span><a href=\"https:\/\/panorays.com\/blog\/vendor-risk-management-complete-guide\/\"><span data-contrast=\"none\">vendor risk management<\/span><\/a><span data-contrast=\"auto\">. Auditors need assurance that\u00a0business continuity is not compromised by reliance on AI systems. This includes understanding how failures are handled, how quickly systems can recover, and whether alternative processes exist. Without proper contingency planning, AI failures could disrupt operations or lead to incorrect outcomes with significant consequences.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Typical questions include:<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"18\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">What uptime commitments or\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/ai-in-professional-services-how-shared-inboxes-threaten-slas\/\"><span data-contrast=\"none\">SLAs<\/span><\/a><span data-contrast=\"auto\">\u00a0are in place for AI services?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"18\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Are manual fallback procedures available if AI fails?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"18\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">How are incorrect AI outputs detected and corrected?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"18\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">How are incidents involving AI communicated to customers?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"18\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">What incident response processes exist for AI-related failures?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<h4 aria-level=\"4\"><b>How Is Risk Managed Across the Vendor Ecosystem?<\/b><\/h4>\n<p>AI services often rely on third-party providers, including cloud platforms and foundation model vendors. Auditors must assess risk across the entire supply chain, not only the primary vendor. External dependencies can create new vulnerabilities, compliance challenges, and operational risks that require active management.<\/p>\n<p><span data-contrast=\"auto\">Auditors commonly ask:<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"19\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Which external AI providers or\u00a0subprocessors\u00a0support your platform?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"19\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Have those providers undergone security and compliance assessments?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"19\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Are\u00a0sub processors\u00a0contractually governed?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"19\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">What contingency plans exist if a critical provider fails or changes service?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"19\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:&#091;8226&#093;,&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">How do you\u00a0monitor\u00a0and manage risks across your AI supply chain?<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><span data-contrast=\"auto\">Collectively, these considerations\u00a0demonstrate\u00a0that\u00a0<\/span><a href=\"https:\/\/www.aiawareness.ai\/ai-resources\/ai-governance-and-compliance\/ai-vendor-governance\/\"><span data-contrast=\"none\">AI vendor governance<\/span><\/a><b><span data-contrast=\"auto\">\u00a0<\/span><\/b><span data-contrast=\"auto\">extends far beyond traditional security reviews. Organizations must be able to show that they understand how AI is used, how risks are controlled, and how regulatory expectations can be met throughout the vendor relationship.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-39781 size-full\" src=\"https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/3-62.png\" alt=\"\" width=\"1920\" height=\"1080\" srcset=\"https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/3-62.png 1920w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/3-62-300x169.png 300w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/3-62-1024x576.png 1024w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/3-62-768x432.png 768w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/3-62-1536x864.png 1536w, https:\/\/smartdev.com\/wp-content\/uploads\/2026\/06\/3-62-18x10.png 18w\" sizes=\"auto, (max-width: 1920px) 100vw, 1920px\" \/><\/p>\n<h3 aria-level=\"3\"><span class=\"ez-toc-section\" id=\"How_AI_Vendors_Can_Turn_Compliance_Scrutiny_into_a_Trust_Advantage\"><\/span><b><span data-contrast=\"auto\">How AI Vendors Can Turn Compliance Scrutiny into a Trust Advantage<\/span><\/b><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span data-contrast=\"auto\">As\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/what-is-an-ai-adoption-accelerator\/\"><span data-contrast=\"none\">AI adoption<\/span><\/a><span data-contrast=\"auto\">\u00a0continues to accelerate &#8211; and as more organizations explore strategies for scaling\u00a0AI\u00a0adoption across the enterprise &#8211;\u00a0<\/span><a href=\"https:\/\/esg.sustainability-directory.com\/term\/regulatory-scrutiny\/\"><span data-contrast=\"none\">regulatory scrutiny<\/span><\/a><span data-contrast=\"auto\">\u00a0will only become more rigorous. For AI vendors, this\u00a0represents\u00a0more than a compliance challenge &#8211; it is an opportunity to differentiate. Vendors that can proactively\u00a0demonstrate\u00a0strong governance, transparency, and security will inspire greater confidence among customers, auditors, and regulators alike.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Rather than treating vendor due diligence as a hurdle to overcome, AI providers should view it as a trust-building exercise, especially as enterprises move from\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/glossary-pilot-project\/\"><span data-contrast=\"none\">pilot projects<\/span><\/a><span data-contrast=\"auto\">\u00a0to\u00a0full-scale AI adoption. Customers are no longer evaluating AI vendors solely on model performance or automation capabilities. They increasingly want evidence that AI systems are secure, explainable, auditable, and designed to support regulatory obligations. Vendors that can answer these questions clearly and provide supporting documentation will reduce procurement friction, shorten security reviews, and strengthen\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/glossary-long-term-partnership\/\"><span data-contrast=\"none\">long-term\u00a0<\/span><span data-contrast=\"none\">partnerships<\/span><\/a><span data-contrast=\"auto\">\u00a0&#8211; key factors in accelerating enterprise AI adoption.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:1,&quot;335551620&quot;:1,&quot;335559685&quot;:0,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:279}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">This shift also changes what it means to build enterprise-ready AI. Beyond delivering intelligent automation, vendors should be able to provide clear\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/compliance-audit-trail-ai-decisions\/\"><span data-contrast=\"none\">audit trails<\/span><\/a><span data-contrast=\"auto\">, transparent governance processes, robust security controls, human oversight mechanisms, and comprehensive documentation that enables customers to\u00a0demonstrate<\/span><span data-contrast=\"auto\">\u00a0compliance<\/span><b><span data-contrast=\"auto\">\u00a0<\/span><\/b><span data-contrast=\"auto\">with confidence. These capabilities are becoming essential as organizations look to operationalize AI adoption in regulated environments.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">This is the philosophy behind\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/nora-your-ai-adoption-accelerator\/\"><span data-contrast=\"none\">NORA<\/span><\/a><span data-contrast=\"auto\">. Rather than functioning as a standalone AI assistant,\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/nora-in-logistics\/\"><span data-contrast=\"none\">NORA<\/span><\/a><span data-contrast=\"auto\">\u00a0is designed to help organizations automate complex\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/ai-workflow-automation-for-risk-compliance\/\"><span data-contrast=\"none\">compliance workflows<\/span><\/a><span data-contrast=\"auto\">\u00a0while\u00a0maintaining\u00a0enterprise-grade governance. It combines\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/ai-automation-document-data-processing\/\"><span data-contrast=\"none\">AI-powered document processing<\/span><\/a><span data-contrast=\"auto\">\u00a0with structured human oversight, producing audit-ready outputs that are traceable, explainable, and supported by evidence &#8211; making it easier for organizations to scale AI adoption responsibly.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><a href=\"https:\/\/smartdev.com\/jp\/document-processing\/\"><span data-contrast=\"none\">NORA<\/span><\/a><span data-contrast=\"auto\">\u00a0also addresses many of the questions auditors increasingly ask during third-party assessments. Organizations can\u00a0demonstrate\u00a0how AI-generated outputs are\u00a0validated, maintain clear decision trails, manage sensitive documents within secure enterprise infrastructure, and\u00a0retain\u00a0the visibility\u00a0required\u00a0for regulatory reviews. By embedding governance directly into AI-enabled workflows,\u00a0<\/span><a href=\"https:\/\/smartdev.com\/jp\/nora-in-financial-compliance\/\"><span data-contrast=\"none\">NORA<\/span><\/a><span data-contrast=\"auto\">\u00a0enables organizations to adopt AI without compromising compliance or control, supporting a more sustainable and compliant approach to AI adoption.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p>The future of enterprise AI will depend on governance, not just automation. As AI vendors become part of third-party risk profiles, trust becomes a competitive advantage. Organizations navigating AI adoption must choose vendors that prioritize transparency, accountability, and governance. This will be critical to scaling AI responsibly and achieving long-term success.<\/p>\n<h3 aria-level=\"3\"><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span><b><span data-contrast=\"auto\">Conclusion<\/span><\/b><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<div class=\"qMYqUG_convSearchResultHighlightRoot\">\n<div class=\"\" data-turn-id-container=\"request-6a3f435d-eb84-83ec-87e7-23fca564f5c5-8\" data-is-intersecting=\"true\">\n<section class=\"text-token-text-primary w-full focus:outline-none has-data-writing-block:pointer-events-none &#091;&amp;:has(&#091;data-writing-block&#093;)&gt;*&#093;:pointer-events-auto R6Vx5W_threadScrollVars scroll-mb-&#091;calc(var(--scroll-root-safe-area-inset-bottom,0px)+var(--thread-response-height))&#093; scroll-mt-&#091;calc(var(--header-height)+min(200px,max(70px,20svh)))&#093;\" dir=\"auto\" data-turn-id=\"request-6a3f435d-eb84-83ec-87e7-23fca564f5c5-8\" data-turn-id-container=\"request-6a3f435d-eb84-83ec-87e7-23fca564f5c5-8\" data-testid=\"conversation-turn-70\" data-turn=\"assistant\">\n<div class=\"text-base my-auto mx-auto pb-10 &#091;--thread-content-margin:var(--thread-content-margin-xs,calc(var(--spacing)*4))&#093; @w-sm\/main:&#091;--thread-content-margin:var(--thread-content-margin-sm,calc(var(--spacing)*6))&#093; @w-lg\/main:&#091;--thread-content-margin:var(--thread-content-margin-lg,calc(var(--spacing)*16))&#093; px-(--thread-content-margin)\">\n<div class=\"&#091;--thread-content-max-width:40rem&#093; @w-lg\/main:&#091;--thread-content-max-width:48rem&#093; mx-auto max-w-(--thread-content-max-width) flex-1 group\/turn-messages focus-visible:outline-hidden relative flex w-full min-w-0 flex-col agent-turn\" data-conversation-screenshot-content=\"\">\n<div class=\"flex max-w-full flex-col gap-4 grow\">\n<div class=\"min-h-8 text-message relative flex w-full flex-col items-end gap-2 text-start break-words whitespace-normal outline-none keyboard-focused:focus-ring &#091;.text-message+&amp;&#093;:mt-1\" dir=\"auto\" tabindex=\"0\" data-message-author-role=\"assistant\" data-message-id=\"e73b7c91-3f9b-43f5-977e-829a845aa562\" data-message-model-slug=\"gpt-5-5-thinking\" data-turn-start-message=\"true\">\n<div class=\"flex w-full flex-col gap-1 empty:hidden\">\n<div class=\"markdown prose dark:prose-invert wrap-break-word w-full dark markdown-new-styling\">\n<p class=\"PDq2pG_selectionAnchorContainer\" data-start=\"0\" data-end=\"470\" data-is-last-node=\"\" data-is-only-node=\"\">AI is transforming enterprise operations and risk management. As AI enters third-party services, due diligence must cover governance, data handling, transparency, and lifecycle controls. For MAS-regulated organizations, AI vendors now shape the overall risk posture. Enterprises should choose vendors with transparency, accountability, and audit readiness. Organizations that embed governance into AI adoption can innovate faster while maintaining regulatory confidence.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n<\/div>\n<\/div>\n<h4><b><span data-contrast=\"auto\">Build an audit-ready AI vendor governance process<\/span><\/b><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:300}\">\u00a0<\/span><\/h4>\n<p><span data-contrast=\"auto\"><a href=\"https:\/\/smartdev.com\/jp\/nora\/\">NORA<\/a> helps compliance and risk teams turn AI-assisted workflows into traceable, reviewable, evidence-backed outputs. Instead of managing AI governance through spreadsheets and fragmented documents, teams can maintain clear review trails, structured oversight, and audit-ready evidence.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:300}\">\u00a0<\/span><\/p>\n<\/div>\n\n\n\n\n\t\t\t<\/div> \n\t\t<\/div>\n\t<\/div> \n<\/div><\/div>","protected":false},"excerpt":{"rendered":"TL;DR AI vendors are now enterprise third-party risks.\u00a0Under MAS expectations, organizations stay accountable for vendor...","protected":false},"author":46,"featured_media":39782,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[236,100,518,74,49,247],"tags":[62,637,66,638],"class_list":["post-39778","post","type-post","status-publish","format-standard","has-post-thumbnail","category-ai-adoption","category-blogs","category-nora","category-services","category-technology","category-workflow-automation","tag-ai","tag-ai-risk-management","tag-smartdev","tag-workflow-automation"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AI Vendors Are Becoming MAS Third-Party Risks. 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