{"id":10627,"date":"2025-12-08T18:40:34","date_gmt":"2025-12-09T00:40:34","guid":{"rendered":"https:\/\/attentionmedia.io\/?p=10627"},"modified":"2025-12-08T18:40:34","modified_gmt":"2025-12-09T00:40:34","slug":"how-to-level-up-your-ai-maturity-from-tools-to-transformation","status":"publish","type":"post","link":"https:\/\/attentionmedia.io\/?p=10627","title":{"rendered":"How to level up your AI maturity from tools to transformation"},"content":{"rendered":"<div><img loading=\"lazy\" decoding=\"async\" width=\"800\" height=\"450\" src=\"https:\/\/martech.org\/wp-content\/uploads\/2025\/11\/A-marketer-stands-on-a-podium-conducting-an-orchestra-of-AI-powered-instruments-800x450.png\" class=\"attachment-large size-large wp-post-image\" alt=\"A marketer stands on a podium conducting an orchestra of AI-powered instruments\" loading=\"lazy\" \/><\/div>\n<p>Scott Brinker and Frans Riemersma\u2019s \u201cMartech for 2026\u201d keynote opened with a wall of logos \u2014 AI agents everywhere. Content production agents deployed by 70% of marketing teams. Customer service chatbots are now commonplace. McKinsey projections show that by 2028, roughly <a target=\"_blank\" href=\"https:\/\/www.mckinsey.com\/capabilities\/growth-marketing-and-sales\/our-insights\/new-front-door-to-the-internet-winning-in-the-age-of-ai-search\" rel=\"noopener\">$750 billion<\/a> in consumer spend will flow through AI-powered search, with 20%\u201350% of traditional traffic at risk.<\/p>\n<p>The data is the most precise snapshot we have of where AI agents are actually being deployed in marketing today. Internal agents are accelerating production through marketing automation and data analytics, lightening workload while improving accuracy. Customer-facing agents are handling volume and engagement. And external agents \u2014 the ones customers control, like ChatGPT and Perplexity \u2014 are quietly becoming a shadow operating system for how buyers discover and evaluate brands.<\/p>\n<p>However, as I studied the charts and listened to the sessions, a pattern began to emerge. The survey shows that we\u2019re maturing rapidly at both the tool and process levels. This deep maturity sets the stage for the next great frontier: the constitutional layer. That\u2019s the architecture that keeps AI decisions auditable, repeatable and aligned with brand identity as agents multiply across the stack. That frontier is where the next wave of competitive advantage will be won or lost.<\/p>\n<h2 class=\"wp-block-heading\">What is AI in marketing today?<\/h2>\n<p>Brinker and Riemersma organized AI agents into three clean domains:<\/p>\n<ul class=\"wp-block-list\">\n<li><strong>Agents for marketers:<\/strong> Internal tools that accelerate work behind the scenes (content production, audience segmentation, competitive analysis, ad optimization).<\/li>\n<li><strong>Agents for customers:<\/strong> Systems that companies deploy and control, but that interact directly with buyers (chatbots, shopper concierges, AI SDRs, email marketing automation).<\/li>\n<li><strong>Agents of customers:<\/strong> AI assistants that customers control to navigate their buying journey outside of any single brand\u2019s reach \u2014 fielding queries, comparing options and making predictions about fit.<\/li>\n<\/ul>\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" loading=\"lazy\" width=\"1172\" height=\"674\" src=\"https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png\" alt=\"The Martech 2026 survey data backs this up: on average, companies are running far more Agents for Marketers than Agents for Customers or Agents of Customers, which is exactly what you\u2019d expect in an early-stage maturity curve.\u00a0\" class=\"wp-image-404758\" \/><figcaption class=\"wp-element-caption\"><em><\/em><em>The Martech 2026 survey data backs this up: on average, companies are running far more Agents for Marketers than Agents for Customers or Agents of Customers, which is exactly what you\u2019d expect in an early-stage maturity curve.\u00a0<\/em><\/figcaption><\/figure>\n<\/div>\n<p>The survey shows deployment still leans toward internal agents, with content-production tools leading at 68.9% adoption. Customer-facing agents follow at 54.4%, while external-facing agents remain uncommon. <\/p>\n<p>Only 63.1% of organizations are publishing AI-optimized content for website discovery and ecommerce visibility and barely a quarter are exposing machine-readable feeds or deep-link APIs that external agents can use.<\/p>\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" loading=\"lazy\" width=\"1299\" height=\"1600\" src=\"https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-8.png\" alt=\"Most popular AI agents deployed in marketing (content, service, data and orchestration), Martech 2026 survey\" class=\"wp-image-404760\" \/><figcaption class=\"wp-element-caption\"><em>Most popular AI agents deployed in marketing (content, service, data and orchestration), Martech 2026 survey<\/em><\/figcaption><\/figure>\n<\/div>\n<p>These adoption patterns reveal an early-stage maturity curve. Organizations have embraced agents as tools, but the underlying governance needed to manage them at scale has yet to materialize. That gap becomes more visible when viewed through the five orders of AI maturity.<\/p>\n<p><strong><em>Dig deeper: <a href=\"https:\/\/martech.org\/five-ways-ai-changed-marketing-strategy-in-just-one-year\/\" target=\"_blank\" rel=\"noopener\">5 ways AI changed marketing strategy in just one year<\/a><\/em><\/strong><\/p>\n<h2 class=\"wp-block-heading\">What are the 5 orders of AI maturity in marketing?<\/h2>\n<p>To understand where the market is \u2014 and where it\u2019s heading \u2014 it helps to think about AI maturity in marketing as a stack of five distinct orders:<\/p>\n<h3 class=\"wp-block-heading\">Order 1: Tactical (Tools and agents)<\/h3>\n<p>This is where the Martech 2026 survey lives. Which tools are we using? Which agents are deployed? It\u2019s about capability and adoption:\u00a0<\/p>\n<ul class=\"wp-block-list\">\n<li>Content agents.<\/li>\n<li>Ad placement optimization.<\/li>\n<li>Data hygiene.<\/li>\n<li>Chatbots.<\/li>\n<li>Blog automation.\u00a0<\/li>\n<\/ul>\n<p>Most organizations are here, selecting tools from various vendors based on immediate functionality.<\/p>\n<h3 class=\"wp-block-heading\">Order 2: Process (Data and workflows)<\/h3>\n<p>This is about infrastructure: first-mile vs. last-mile data, data unification, warehouse-native stacks and marketing ops evolving from tool admins to use-case onboarders.\u00a0<\/p>\n<p>Integration of customer data, user data, audience data and analytics platforms from multiple data sources defines success at this layer. The best teams are here, <a target=\"_blank\" href=\"https:\/\/martech.org\/ai-readiness-checklist-7-key-steps-to-a-successful-integration\/\" rel=\"noopener\">managing big data flows and reducing workload<\/a> through intelligent automation.<\/p>\n<h3 class=\"wp-block-heading\">Order 3: Strategic (Journeys and value engineering)<\/h3>\n<p>This is Brinker and Riemersma\u2019s Marketing Ops 3.0 world \u2014 value engineering, Pareto thinking (where 20% of your tech and content serves 80% of repeatable revenue) and the lab versus factory operating model.\u00a0<\/p>\n<p>Advanced teams are pushing into this layer with strategic segmentation, personalization at scale, workflow orchestration and prediction tools that help them grasp which customer journeys drive loyalty and long-term value.<\/p>\n<h3 class=\"wp-block-heading\">Order 4: Constitutional (Brand identity and governance rules)<\/h3>\n<p>This is the emerging layer. It\u2019s about codifying brand red lines, permission boundaries and decision guardrails in machine-readable form so that every downstream agent \u2014 internal, customer-facing and external \u2014 inherits them automatically.\u00a0<\/p>\n<p>Without this, every new tool requires manual governance negotiation. With it, governance becomes infrastructure and algorithms operate within defined boundaries, mitigating bias and ensuring that input from diverse data sources is evaluated against consistent brand standards.<\/p>\n<h3 class=\"wp-block-heading\">Order 5: Sovereign (Brand and moat)<\/h3>\n<p>This is the endgame. When governed intelligence itself becomes the moat \u2014 trust compounds, pricing power strengthens, regulatory resilience turns into competitive advantage and institutional memory encodes into systems that survive personnel turnover and technology shifts.\u00a0<\/p>\n<p>At this level, organizations possess deep expertise in managing AI across every variant of their operations and their constitutional architecture becomes a strategic asset that competitors and vendors cannot easily replicate.<\/p>\n<p>The Martech 2026 report provides a clear picture of Orders 1\u20133. That brings the challenge in Order 4 into sharp focus. It is the necessary bridge to reach Order 5 (Sovereign advantage), turning the potential of agents into a compounding competitive moat.<\/p>\n<p><strong><em>Dig deeper: <a href=\"https:\/\/martech.org\/most-ai-agents-fail-without-data-and-governance-maturity\/\" target=\"_blank\" rel=\"noopener\">Most AI agents fail without data and governance maturity<\/a><\/em><\/strong><\/p>\n<h2 class=\"wp-block-heading\">How do the Martech 2026 charts reveal the Order 4 gap?<\/h2>\n<p>Let\u2019s revisit three key slides from the keynote through this framework.<\/p>\n<p>The survey shows that 80.6% of deployed agents operate in \u201cassist only\u201d mode, where AI suggests and humans decide. Another 37.9% run in \u201cexecute with approval\u201d mode, where AI proposes an action and waits for human sign-off.<\/p>\n<p>On the surface, this appears to be responsible governance \u2014 and it is. Humans have heroically bridged the gap so far. But to scale Brinker\u2019s vision of value engineering, we need to graduate from manual approvals to constitutional architecture.<\/p>\n<p>Every approval decision is currently a one-time judgment call. There\u2019s no reusable pattern. No institutional memory, and no way to audit why one human approved and another didn\u2019t. When you add your fourth, seventh, 12th AI-powered tool, you\u2019re not inheriting governance \u2014 you\u2019re renegotiating it from scratch.<\/p>\n<p>That is Order 2 thinking applied to an Order 4 problem. It works until scaling breaks it.<\/p>\n<h3 class=\"wp-block-heading\">What does the $750 billion external agent disruption mean?<\/h3>\n<p>McKinsey\u2019s findings reinforce the urgency: external agents are becoming powerful intermediaries between brands and buyers.<\/p>\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" loading=\"lazy\" width=\"1178\" height=\"510\" src=\"https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-9.png\" alt=\"Agents of customers and the $750 billion AI search disruption, Martech 2026 report\" class=\"wp-image-404761\" \/><figcaption class=\"wp-element-caption\"><em><\/em><em>Agents of customers and the $750 billion AI search disruption, Martech 2026 report<\/em><\/figcaption><\/figure>\n<\/div>\n<p>The survey shows the gap clearly. Only 63.1% are publishing AI-optimized content (structured Q&amp;A, schema markup), and barely 17.5% are exposing machine-readable product feeds or providing MCP servers that external agents can query for accurate, real-time market data.<\/p>\n<p><strong>Here\u2019s the Order 4 opportunity:<\/strong> External agents will act as a shadow OS for your brand whether you architect for them or not. They\u2019ll scrape your website, remix your content and answer buyer queries \u2014 potentially with outdated data, competitor language or outright hallucinations.<\/p>\n<p>A constitutional layer that defines how your brand should be represented in machine-readable form turns this risk into an advantage \u2014 you author your identity proactively rather than letting external agents write it by default.<\/p>\n<h3 class=\"wp-block-heading\">Why does AI slop keep growing in lab and factory models?<\/h3>\n<p>Brinker and Riemersma describe two operating modes for martech stacks:\u00a0<\/p>\n<ul class=\"wp-block-list\">\n<li>The laboratory \u2014 where you experiment with new journeys, test problem-market fit and explore personalization strategies.<\/li>\n<li>The factory \u2014 where you scale proven, repeatable journeys with predictable economics and marketing automation.<\/li>\n<\/ul>\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" loading=\"lazy\" width=\"1302\" height=\"932\" src=\"https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-4.png\" alt=\"The two martech stack roles \u2014 laboratory versus factory, Martech 2026 report\u00a0\" class=\"wp-image-404755\" \/><figcaption class=\"wp-element-caption\"><em>The two martech stack roles \u2014 laboratory versus factory, Martech 2026 report\u00a0<\/em><\/figcaption><\/figure>\n<\/div>\n<p>Innovative teams run both in parallel. The challenge: without a shared constitutional layer, labs and factories each invent their own governance rules. The lab says, \u201cMove fast, test everything.\u201d The factory says, \u201cDon\u2019t break what\u2019s working.\u201d The collision shows up as rework, brand inconsistency and what one speaker called AI slop \u2014 content and decisions multiplying faster than teams can govern them.<\/p>\n<p>This is the reconciliation tax: the hidden cost of ungoverned AI, which appears as unexplained budget overruns, compliance risks and brand drift. It grows exponentially as you add agents, because every new tool requires manual coordination with every existing one. As I explored in \u201c<a target=\"_blank\" href=\"https:\/\/martech.org\/your-ai-strategy-is-stuck-in-the-past-heres-how-to-fix-it\/\" rel=\"noopener\">Your AI strategy is stuck in the past\u00a0 \u2014\u00a0 here\u2019s how to fix it<\/a>,\u201d the difference between getting stuck in pilot purgatory and achieving scalable success lies in moving beyond scattered experiments to governed, end-to-end workflows.<\/p>\n<p>Order 4 is the glue. It\u2019s the layer that lets labs experiment safely (because brand red lines are enforced automatically) and factories scale confidently (because governance patterns are reusable, not rebuilt every time).<\/p>\n<h2 class=\"wp-block-heading\">What is the constitutional layer and how do you build it?<\/h2>\n<p>The conversations at Martech Day made it clear that everyone recognizes the need for governance and keeping humans in the loop. The natural next step is a systematic architecture that:<\/p>\n<ul class=\"wp-block-list\">\n<li>Encodes brand identity and decision guardrails once so every agent inherits them automatically.<\/li>\n<li>Produces instant, defensible receipts for any AI-assisted decision \u2014 exportable for regulators, customers or the board with complete transparency.<\/li>\n<li>Prevents collisions when adding more AI-powered tools without requiring renegotiation of governance each time.<\/li>\n<\/ul>\n<p>This is the Order 4 bridge. And it\u2019s buildable. The architecture I call the Brand Experience AI Operating System (BXAI-OS) is built on three foundational pillars.<\/p>\n<h3 class=\"wp-block-heading\">Pillar 1: Constitutional enforcement<\/h3>\n<p>Specific brand red lines and decision guardrails are enforced before any AI acts, not after. When an agent proposes an action that crosses a boundary \u2014 offering a discount that erodes margin, using competitor language, making a promise the company can\u2019t keep \u2014 the system pauses, escalates with a documented rationale and waits for human resolution. Decisions resume only after review.\u00a0<\/p>\n<p>This functionality ensures accuracy, mitigates bias in AI input and protects customer data integrity. It prevents <a target=\"_blank\" href=\"https:\/\/martech.org\/the-hidden-ai-risk-that-could-break-your-brand\/\" rel=\"noopener\">the hidden AI risk that could break your brand<\/a>.<\/p>\n<h3 class=\"wp-block-heading\">Pillar 2: Glass-box evidence view<\/h3>\n<p>Every decision produces a tamper-evident receipt: source lineage, applied guardrails, confidence level and escalation trail. These aren\u2019t abstract logs buried in systems \u2014 they\u2019re exportable artifacts you can hand to a regulator, a customer or your CFO in minutes.\u00a0<\/p>\n<p>Speed without receipts is just undocumented chaos. Speed with receipts is governed velocity and operational transparency. This evidence trail enables stakeholders to understand precisely how AI-generated predictions were derived and which data sources informed each decision.<\/p>\n<h3 class=\"wp-block-heading\">Pillar 3: Shadow ledger and reconciliation tax<\/h3>\n<p>Most organizations fail to measure the hidden cost of ungoverned AI: the rework cycles, the compliance scares and the brand collisions that manifest as mysterious budget overruns.\u00a0Quantifying this shadow ledger turns governance from a risk-mitigation expense into a velocity investment \u2014 because you\u2019re eliminating waste that\u2019s already bleeding the profit and loss (P&amp;L) statement.<\/p>\n<p>Together, these three pillars create the constitutional infrastructure that lets you scale Orders 1\u20133 with confidence.<\/p>\n<h2 class=\"wp-block-heading\">How does Order 4 governance unlock velocity in Orders 1\u20133?<\/h2>\n<p>Here\u2019s the reframe: Governance isn\u2019t bureaucracy, it\u2019s the architecture that enables velocity.<\/p>\n<p><strong>For labs:<\/strong> Experiment aggressively because the constitutional layer catches red-line violations before they compound. You can test faster because guardrails are automated, not negotiated. Personalization experiments, email marketing campaigns and ad placement tests run with built-in safety rails. Test different variants without fear of brand drift.<\/p>\n<p><strong>For factories:<\/strong> Scale repeatable journeys without renegotiating governance or rebuilding decision logic. Each new workflow inherits constitutional patterns from the previous one, so deployment time drops from months to weeks. Marketing automation becomes more reliable and integration with CRM systems and analytics platforms happens cleanly. Workload decreases as governance becomes reusable infrastructure rather than custom negotiation.<\/p>\n<p><strong>For Marketing Ops 3.0:<\/strong> Brinker and Riemersma argue that marketing ops is evolving from \u201ctool admins\u201d to \u201cvalue engineers\u201d who focus on the Pareto balance \u2014 where 20% of your tech serves 80% of repeatable revenue. Order 4 gives value engineers the metrics and levers they actually need: quantified reconciliation tax, reusable governance templates and instant audit capability that turns compliance from a bottleneck into a checkbox. It demands expertise in both technology and brand strategy, but the payoff is substantial.<\/p>\n<p>Tie this back to the keynote\u2019s efficiency\/effectiveness chart: Order-4 architecture is what lets you reliably transition from \u201cdo more with less\u201d (scarcity-driven experiments) to \u201cdo more with more\u201d (compounding profit at scale). Constitutional infrastructure turns agent proliferation from chaos into compound advantage.<\/p>\n<h2 class=\"wp-block-heading\">What should CMOs actually do about AI governance in 2026?<\/h2>\n<p>Start with one high-value workflow from your 80% revenue band \u2014 the repeatable journeys that drive the bulk of your business. Then:<\/p>\n<ul class=\"wp-block-list\">\n<li><strong>Map the reconciliation tax: <\/strong>Where do brand collisions or compliance risks currently emerge? How much leadership time gets burned reconciling contradictory AI outputs? Quantify it.\n<ul class=\"wp-block-list\">\n<li><strong>Define 3\u20137 brand red lines:<\/strong> What decisions must <strong>never<\/strong> be violated, no matter what any AI proposes? Examples: \u201cNever promise a feature that\u2019s not on the approved roadmap.\u201d\u00a0<\/li>\n<li>\u201cNever offer a discount that erodes margin below 20%.\u201d\u00a0<\/li>\n<li>\u201cNever use competitor language or slang in premium-brand contexts.\u201d<\/li>\n<\/ul>\n<\/li>\n<li><strong>Implement simple receipts:<\/strong> For key AI-assisted decisions, generate a basic record that includes the following details: the rule applied, the user or customer data used, the confidence level that triggered the action and who approved any overrides. Make it exportable so you can explain it to regulators, boards or customers in minutes, not weeks.<\/li>\n<\/ul>\n<p>Then replicate that pattern to the following 2\u20134 business cases, mirroring the Pareto\/productization advice from Brinker\u2019s keynote. This doesn\u2019t replace his guidance \u2014 it completes it by providing a reusable constitutional pattern that scales.<\/p>\n<h2 class=\"wp-block-heading\">From Martech 2026 to Governed Intelligence 2027<\/h2>\n<p>The Martech 2026 report set the baseline for where the industry truly stands: agents deployed, data analytics unified, and ops teams evolving from tool administrators to value engineers.<\/p>\n<p>The data make clear that 2027\u20132028 will be defined by who builds Order 4 constitutional architecture to support that momentum. It is essential as AI search intensifies, regulations tighten (Colorado and California are already moving) and customer expectations shift toward brands that can explain their AI decisions in plain language with full transparency.<\/p>\n<p>The companies that architect governance as infrastructure will move faster, scale more cost-effectively and defend themselves more easily than competitors still managing governance through manual approval workflows and paying the reconciliation tax every quarter. They\u2019ll build loyalty not just through better prediction tools, but through trustworthy, auditable AI that customers can grasp and rely on.<\/p>\n<p><strong><em>Dig deeper: <a href=\"https:\/\/martech.org\/three-actions-you-must-take-to-thrive-in-the-agentic-era-of-marketing\/\" target=\"_blank\" rel=\"noopener\">3 actions you must take to thrive in the agentic era of marketing<\/a><\/em><\/strong><\/p>\n<h2 class=\"wp-block-heading\">Key takeaways<\/h2>\n<ul class=\"wp-block-list\">\n<li><strong>Martech 2026 mapped Orders 1\u20133 brilliantly:<\/strong> The survey shows where teams are deploying tools (Order 1), building process infrastructure with data analytics and marketing automation (Order 2) and thinking strategically about value engineering (Order 3).<\/li>\n<li><strong>Order 4 is the missing constitutional layer:<\/strong> Without machine-readable brand guardrails, every new AI tool requires manual governance renegotiation \u2014 creating reconciliation tax and AI slop.<\/li>\n<li><strong>BXAI-OS offers a 3-pillar solution:<\/strong> Constitutional enforcement (brand red lines enforced before AI acts), glass-box evidence (instant audit receipts with transparency) and shadow ledger visibility (quantifying hidden governance costs).<\/li>\n<li><strong>Order 4 enables velocity, not bureaucracy:<\/strong> Labs experiment safely, factories scale confidently and Marketing Ops 3.0 gets the metrics and expertise to be true value engineers.<\/li>\n<li><strong>Start with one core revenue workflow:<\/strong> Map the reconciliation tax, define 3\u20137 red lines, implement simple receipts, then replicate the pattern across 2\u20134 business cases.<\/li>\n<\/ul>\n<p><!-- START INLINE FORM --><\/p>\n<div class=\"nl-inline-form border py-2 px-1 my-2\">\n<div class=\"row align-items-center justify-content-center nl-inline-container\">\n<div class=\"col-12 pb-1\">\n<p class=\"inline-form-text text-center mb-0\">Fuel up with free marketing insights.<\/p>\n<\/div>\n<div class=\"col-12 col-lg-auto pb-2 pb-lg-0\">\n<p class=\"inline-form-text text-center mb-0\">Email:<\/p>\n<\/div>\n<div class=\"col-12 col-lg-8 pe-lg-0\">\n<div class=\"form-nl-inline\"><\/div>\n<\/div>\n<div class=\"col-12 col-lg-auto\">\n<p class=\"text-center mb-0\"><a class=\"nl-terms\" href=\"https:\/\/martech.org\/terms-of-service\/\" target=\"_blank\" aria-label=\"opens in a new tab\">See terms.<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<p><!-- END INLINE FORM --><\/p>\n<p>The post <a href=\"https:\/\/martech.org\/how-to-level-up-your-ai-maturity-from-tools-to-transformation\/\">How to level up your AI maturity from tools to transformation<\/a> appeared first on <a href=\"https:\/\/martech.org\/\">MarTech<\/a>.<\/p>","protected":false},"excerpt":{"rendered":"<p>Scott Brinker and Frans Riemersma\u2019s \u201cMartech for 2026\u201d keynote opened with a wall of logos \u2014 AI agents everywhere. Content production agents deployed by 70% of marketing teams. Customer service chatbots are now commonplace. McKinsey projections show that by 2028, roughly $750 billion in consumer spend will flow through AI-powered search, with 20%\u201350% of traditional &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/attentionmedia.io\/?p=10627\" class=\"more-link\">Read more<span class=\"screen-reader-text\"> &#8220;How to level up your AI maturity from tools to transformation&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-10627","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"featured_media_urls":{"thumbnail":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"medium":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"medium_large":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"large":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"1536x1536":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"2048x2048":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"inspiro-featured-image":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"inspiro-loop":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"inspiro-loop@2x":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"portfolio_item-thumbnail":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"portfolio_item-thumbnail@2x":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"portfolio_item-masonry":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"portfolio_item-masonry@2x":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"portfolio_item-thumbnail_cinema":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"portfolio_item-thumbnail_portrait":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"portfolio_item-thumbnail_portrait@2x":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false],"portfolio_item-thumbnail_square":["https:\/\/martech.org\/wp-content\/uploads\/2025\/12\/image-6.png",0,0,false]},"_links":{"self":[{"href":"https:\/\/attentionmedia.io\/index.php?rest_route=\/wp\/v2\/posts\/10627","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/attentionmedia.io\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/attentionmedia.io\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/attentionmedia.io\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/attentionmedia.io\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=10627"}],"version-history":[{"count":0,"href":"https:\/\/attentionmedia.io\/index.php?rest_route=\/wp\/v2\/posts\/10627\/revisions"}],"wp:attachment":[{"href":"https:\/\/attentionmedia.io\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=10627"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/attentionmedia.io\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=10627"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/attentionmedia.io\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=10627"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}