{"id":11005,"date":"2026-05-01T18:42:43","date_gmt":"2026-05-02T00:42:43","guid":{"rendered":"https:\/\/attentionmedia.io\/?p=11005"},"modified":"2026-05-01T18:42:43","modified_gmt":"2026-05-02T00:42:43","slug":"can-dams-keep-up-as-content-demands-outgrow-workflows","status":"publish","type":"post","link":"https:\/\/attentionmedia.io\/?p=11005","title":{"rendered":"Can DAMs keep up as content demands outgrow workflows?"},"content":{"rendered":"
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The bottleneck in content operations isn\u2019t content creation. Research from the latest\u00a0MarTech Intelligence Report on DAM platforms<\/a>\u00a0found that as<\/span> asset volume, personalization demands, and channel complexity continue to climb, the chokepoint is likely in the systems required to manage, adapt, and distribute content at scale.<\/p>\n

Let\u2019s start with content volume, because it\u2019s at the root of everything else. Seventy-eight percent of marketers say they need more personalized content than they can currently produce, and 65% struggle to produce timely, personalized content for all their segments, according to Salesforce\u2019s \u201cState of Marketing report, Tenth Edition.\u201d<\/p>\n

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Those numbers reflect a genuine production bottleneck \u2014 but they also point to where a well-configured DAM platform pays for itself. A single campaign that once required a handful of asset variants now routinely requires dozens or hundreds. The organizations handling that volume well have the right infrastructure in place. Those that aren\u2019t yet are the ones feeling the squeeze.<\/p>\n

Video is accelerating this shift. One of the more striking data points I came across was from MediaValet\u2019s 2026 DAM Trends Report: video adoption inside DAM platforms jumped from 68% to 83% in a single year.<\/p>\n

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That\u2019s a fast move, and vendors have kept pace. Platforms are now built with video-specific capabilities, such as automated transcription, multilingual captioning, copyright detection, and reuse recommendation engines that surface existing footage before teams commission new production, with direct implications for both budget and speed to market.<\/p>\n

AI is doing more of the heavy lifting<\/h2>\n

On the operational side, AI is removing much of the friction from DAM workflows. Data from Bynder\u2019s \u201cState of DAM 2026\u201d shows that 62% of organizations have already moved beyond early-stage AI adoption in their DAM \u2014 and the platforms that are scaling it effectively are seeing real returns.<\/p>\n

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The most significant shift is the increasing use of agentic AI. It goes beyond auto-tagging and smart cropping to handle more complex, multistep work \u2014 detecting off-brand content at scale, generating hyper-personalized asset variants, managing approval routing, and resolving rights conflicts. <\/p>\n

These systems also help ensure images and videos comply with emerging SEO and GEO standards, helping brands be found by their customers. I explored this in more depth in the companion podcast for the report, and it\u2019s worth a listen if you want to understand what\u2019s actually possible right now, not just what\u2019s coming.<\/p>\n

That said, AI doesn\u2019t mean hands-off. Nine in 10 respondents to a Bynder\/Censuswide survey said human oversight is essential to safeguarding brand identity when AI-generated content is involved. The good news is that leading platforms are building that oversight in, with content credentials support, AI-generation flagging, and audit trail capabilities that give teams visibility without slowing everything down.<\/p>\n

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A growing market means more good options<\/h2>\n

The DAM market is projected to grow from $7.73 billion in 2025 to $31.99 billion by 2034 at a 15.26% compound annual growth rate, according to IMARC Group. That growth is bringing investment, competition, and capability expansion across the board \u2014 which is good news for buyers.<\/p>\n

The landscape is worth understanding before you start evaluating, though. Pure-play DAM vendors, broader marketing suites with embedded DAM capabilities, and adjacent platforms entering the space each have distinct strengths. And since organizations use an average of 2.5 DAM platforms in parallel, according to Gartner\u2019s \u201c2025 Magic Quadrant for DAM Platforms,\u201d there\u2019s a real opportunity for consolidation if you go in with the right questions.<\/p>\n

Where to start<\/h2>\n

The report is designed to make that evaluation process straightforward. If you\u2019re trying to figure out what any of this means for your specific situation, the custom chatbot built for this report is a good first stop \u2014 you can ask it questions about your use case and get answers grounded in the research.<\/p>\n

The full PDF and all of the accompanying interactive assets are available here.<\/a> Download the report, check out the podcast for a deeper dive on AI and the vendor landscape, and use the chatbot to get personalized guidance on what to look for in your next DAM evaluation.<\/p>\n

The post Can DAMs keep up as content demands outgrow workflows?<\/a> appeared first on MarTech<\/a>.<\/p>","protected":false},"excerpt":{"rendered":"

The bottleneck in content operations isn\u2019t content creation. Research from the latest\u00a0MarTech Intelligence Report on DAM platforms\u00a0found that as asset volume, personalization demands, and channel complexity continue to climb, the chokepoint is likely in the systems required to manage, adapt, and distribute content at scale. Let\u2019s start with content volume, because it\u2019s at the root … <\/p>\n

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