Over the past several months of conversations with digital asset management (DAM) customers, I’ve noticed a pattern that should give both B2B marketing leaders and DAM vendors pause. AI agent adoption in the DAM market remains slow. This is hardly surprising — adoption is slow everywhere. And yes, CIO organizations still caution against ungoverned AI creeping into the enterprise from well-meaning lines of business. But that’s old news.

DAM vendors are advancing their platforms with agentic frameworks — bundling features such as agent libraries for tagging and metadata enrichment, translation and localization, and brand governance to accelerate adoption. While this approach provides a convenient on-ramp, it may also reinforce vendor dependency. But we’re seeing forward-leaning enterprises choose a very different path. They’re setting aside vendor agent decisions and focusing first on building their own agentic frameworks along with walled-garden large language models, bringing composability in house and defining “AI extensibility” on their own terms. Instead of asking, “Which vendor agent should we try?” they’re asking, “How do we create an internal architecture that any approved agent must plug into?” This shift has real implications for CMOs, DAM leaders, and vendors alike. It potentially changes how AI is procured, deployed, governed, and integrated into the broader marketing and content ecosystem.

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The Intermodal Shipping Yard Moment

To understand the shift, picture a modern shipping yard, which is typically “intermodal,” meaning that it moves standardized containers with universal twist-lock connection systems across multiple modes (rail, ship, truck, etc.) without handling the freight itself. In this analogy, an enterprise’s agentic framework is the chassis to which every container must align. Vendor agents are the containers — diverse and valuable but only useful if they attach cleanly to the standardized fittings. It doesn’t matter how beautiful the container is, how advanced the contents are, or how innovative the vendor claims to be. If it cannot twist-lock into the enterprise’s framework, it will sit on the dock unused. This is how these organizations now think about agent adoption. They are defining the rails, the governance, the security guardrails, the interoperability rules, and the connective tissue. Vendors must fit into their system — not the other way around.

What This Means For Marketing

If you’re a marketing leader navigating a martech ecosystem filled with vendors rolling out new agents every quarter, you can’t just walk into your CIO’s office saying, “Marketing wants this new agent because it looks promising.” You need to come in already understanding what your CIO will require for any agent to be approved within the enterprise’s agentic architecture, if that’s being built. Your job is no longer to champion vendor agent adoption; it’s to champion the agent that fits.

To help you do that, consider the requirements that your CIO and enterprise architecture team are likely applying to every vendor agent before it can plug into their framework. The baseline here for your CIO is composable architecture alignment: Vendor agents must be modular in design, support multiagent orchestration, and be compatible with enterprise choreography systems. The baseline for you is business-aligned functionality — agents must deliver specific, validated “jobs to be done” rather than provide generic AI features. Also consider:

  • Standards-based interoperability: open APIs, well-documented interfaces, and compatibility with emerging agent interoperability protocols
  • Governance and security: step-level logging, auditability, policy enforcement, and agent-level security requirements such as authentication, privilege controls, isolation, and safe data access rules, all aligned to enterprise frameworks like AEGIS to ensure that agents operate within approved compliance conditions
  • Extensibility without lock-in: agents that can operate across ecosystems — not locked to a vendor’s proprietary platform
  • Data and semantic integration: the ability to securely connect to enterprise data layers, metadata systems, and domain schemas
  • Observability and performance transparency: monitoring, telemetry, operational analytics, cost visibility, and behavior reporting
  • Lifecycle and version management: safe rollout, versioning, testing harnesses, and continuous validation processes

What This Means For Vendors

For DAM and martech vendors, know that your customers increasingly see themselves as builders of agent ecosystems, not passive consumers of agents. They will not adopt agents that float freely outside their architecture. To succeed, vendors must:

  • Treat enterprise customers as technology partners, not just buyers.
  • Build agents that snap onto customer frameworks with standardized interfaces.
  • Abandon the idea that customers will accept siloed or proprietary agent environments.

The enterprises most ready for AI are redrawing the boundaries, and vendors that adapt will find themselves embedded in these new architectures. Those that don’t will find their agents — in intermodal terms — to be beautifully painted containers that simply don’t fit the rail.

See Us At Forrester’s B2B Summit

If you’re wrestling with agent adoption, interoperability, and content operations in a multiagent world, join us at Forrester’s B2B Summit North America this April. You’ll get fresh research, real-world peer examples, and hands-on guidance that your marketing organization needs. (If you’re a Forrester client, ask your account team about passes and sessions tailored for marketing and content leaders and for martech owners.)