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For enterprise teams, DAM scale now depends on how well the platform connects and governs content across systems, since asset volume alone no longer defines the job. That change helps explain why 80% of enterprise DAM leaders plan to increase their investment in technology for managing rich media over the next two years, according to Forrester research commissioned by Orange Logic.
Forrester summed up the shift in the study's subtitle: a system of record is transforming into one of orchestration. Below, we break down what scale looks like in practice, the signs a DAM has hit its limit, and how to evaluate a platform for long-term growth.
What does it mean for a DAM to scale with an enterprise?
A DAM scales with an enterprise when it keeps search fast and governance consistent as the business adds more content, more teams, and more connected tools. Volume is only part of the picture. A system that holds millions of assets but has performance degradation as a result, pushes departments into separate tools, has hit its limit.
Forrester's data shows how many organizations are already there. 62% of leaders say they can't make full use of the assets they already have, and 69% say they need better AI-powered search and discovery to find content quickly.
Why are enterprises investing more in DAM now?
Enterprises are investing more in DAM because audiences, and the budgets that follow them, are spreading across more channels. In Gartner's 2026 CMO Spend Survey, digital media made up more than two-thirds of total media investment, up 18% since 2024.
Forrester's DAM study shows that pressure will keep building. Three in four decision-makers expect requirements for new rich media to rise over the next two years.
Leaders also expect to get more out of the content they already own. 69% anticipate greater adoption and reuse of rich-media assets, and most believe an optimized DAM will improve customer experience and reduce compliance risk.
What are the signs your DAM has stopped scaling?
A DAM has stopped scaling when teams start working around it by recreating assets they can't find or keeping content in separate tools. Here are the most common signs from Forrester's survey, along with a quick way to check for each one in your own organization:
- Search slows as the library grows. Test search against your full library and time how long it takes teams to find a specific asset.
- Assets sit in disconnected systems. Ask a few teams where they'd look for a recent campaign asset, and count how many different places they name. 64% of DAM decision-makers say they've missed opportunities because assets were siloed.
- Reusing content takes too much effort. Pull a handful of recent creative requests and check whether a usable version already existed in your library. 67% of DAM leaders report difficulty reusing, updating, or retiring content.
- Compliance gaps widen. Pick a few assets currently live on your website or social channels and see how quickly you can confirm their usage rights and expiration dates. 64% of those surveyed report legal and regulatory compliance challenges.
- Tools overlap. Ask your team where they go to create an AI-generated image or find a specific asset, and see whether the answer is the DAM or another tool. On average, respondents manage eight types of tasks in both their DAM and another system.
Each of these problems compounds as the library grows, which is why scale usually shows up first as friction for the people using the system.
How does a scalable DAM differ from a larger repository?
A scalable DAM orchestrates work across the content lifecycle, connecting the systems that create, approve, and publish assets. That's the direction DAM leaders are heading, with 43% in Forrester's study planning to centralize control and governance of content across systems. In practice, orchestration at enterprise scale depends on six capabilities.
1. Performance that holds under peak load
As more teams and connected systems rely on a DAM, traffic spikes become routine. Product launches, seasonal campaigns, and automated publishing can send thousands of requests to the platform at once, so search and API response times need to hold steady at peak as well as on an average day.
Pearson's video player, for example, averages 70 million plays a month. Orange Logic delivers the video behind it, meeting peak demand of 40,000 API calls a minute during the back-to-school rush.
2. One platform across departments
When a central DAM can't meet every department's needs, teams buy their own tools and content splinters across them. A DAM that scales gives each department workflows suited to its work while keeping assets and permissions in one governed system.
Lionsgate's marketing assets were once spread across seven legacy storage locations. Today every Lionsgate marketing team works from Orange Logic as its system of record, and more than 800 global partners get secure, self-service access to approved content.
3. Integrations that carry context with the asset
Integrations turn a DAM into the hub of the content operation, moving assets between the systems where teams create, review, and publish. The connections that matter at scale carry metadata and permissions along with the file, so assets stay searchable and governed. It's also where leaders are focusing, with 47% of respondents in the Forrester study ranking integration with adjacent systems as their top DAM priority for the next 12 months.
Orange Logic pairs prebuilt connectors, like its Adobe Creative Cloud integration, with open APIs for the systems unique to each organization. Headspace, for example, connected Orange Logic to its CMS and analytics tools, cutting out duplicated effort between teams.
4. Storage tiers that match how assets are used
Not every asset needs the same storage. Files in active campaigns need fast access, while finished projects and archives can sit in lower-cost tiers until someone needs them. Moving assets between tiers automatically keeps costs from climbing in step with library growth.
In Orange Logic, teams can set rules that move assets to cold storage on their own, for example once an archive date passes or usage rights expire. The assets stay searchable and governed in the DAM wherever the files sit.
5. Delivery that reaches global teams
As teams and partners spread across regions, the distance between people and files starts to show up as slow previews and downloads. Regional storage and content delivery networks (CDNs) keep access fast no matter where someone works.
Orange Logic generates proxy and derivative files when assets are ingested and supports delivery through CDNs, so teams and partners can pull the format and resolution they need without waiting on a full-size download.
6. AI that keeps pace with volume
AI becomes more valuable as libraries grow, and it's also where leaders struggle most. 58% say building an effective strategy for applying AI to their content is their top challenge. One North American director told Forrester: "I would like a DAM vendor to provide AI that suggests the right asset when I need it."
Orange Logic's agentic AI tags, enriches, and checks assets against rights rules; it also moves content through approvals and workflows. OCR and transcription make documents, audio, and video searchable, and teams can generate and adapt visuals inside the DAM using models trained on their own library and taxonomy. At high volume, teams can choose whether people review AI suggestions or let them apply automatically.
How should you evaluate a DAM for enterprise scale?
Evaluate a DAM on how it performs at your future volume, with your systems connected. These questions help separate claims from verifiable evidence:
- Proof at your volume. Ask for customer references with libraries at the size you expect to reach, not the size you have today.
- Peak performance. Request data on API throughput and search speed during traffic spikes.
- Integration depth. Confirm which connectors are prebuilt and whether metadata and permissions travel with assets into connected tools like your CMS or design software.
- Governance across teams. Ask whether company-wide rights rules and permissions still apply when a department customizes its own workspace, so no team can share an asset it isn't cleared to use.
- Control over AI. Ask whether AI tags follow your brand's own terms, and whether your team can decide when AI suggestions need human review and when they apply automatically.
A vendor that can answer these with customer evidence is far more likely to support the next five years of growth.
Frequently asked questions
Is a scalable DAM the same as scalable cloud storage?
A DAM manages the metadata, permissions, and workflows around assets, while storage holds the files themselves. Orange Logic connects to third-party storage including existing on-premise storage through Media Bridge. Wherever the files live, Orange Logic's metadata, permissions, and search keep pace as libraries grow into petabytes.
How much content can an enterprise DAM handle?
An enterprise DAM should handle petabytes of content. Orange Logic customers manage libraries of any size, with some enterprises holding tens of millions of assets.
What is the biggest barrier to scaling a DAM?
The biggest barrier is figuring out how to use AI effectively within the DAM. Leaders in Forrester’s study commissioned by Orange Logic ranked building an AI strategy as their top challenge in reaching DAM goals. Budget is a smaller factor: only about one in four decision-makers said limited budget or a lack of IT support held them back.
Go Beyond Storage
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