For years, marketers have treated automation as an answer to growing content needs. Build enough rules into your workflow, and the system can handle the rest. AI proves that is not true.
According to Bynder’s “State of DAM Report 2026,” 93% of enterprise organizations face content automation challenges based on their rules that they cannot solve. The biggest problems are not publishing content quickly. It acquires non-corporate assets, manages AI-generated content, produces personalized content at scale, and manages complex workflows.
Rule-based automation works well in predictable situations. However, AI is not good at following rules. It likes to add things as it goes along, thinking it knows what it “really” wants. So marketers went from “Yay, look at all the content that AI can create,” to “What does it do, this time?”
Security is now a top concern for marketers when using AI for content operations, followed by legal and regulatory compliance, and inaccurate or falsified results. Respondents also raised concerns about product content not being able to scale AI without creating new workflow barriers.
Those problems reach beyond DAM. Every marketing organization is trying to balance rapid content production with copyright compliance, product management, privacy requirements, and the increasing processing of AI-generated content. With AI embedded in all marketing activities, governance is becoming part of the day-to-day campaign rather than the final review step.
People are always responsible for the final decision
Across brand governance, metadata management, content quality, and cross-channel asset management, common workflows include AI and human approval. About 40% to 44% of respondents said automation does the work while humans make the final decision. Another 31% to 35% rely on mixed workflows that include automated and manual updates throughout the process.
Instead of replacing humans, AI takes over repetitive work, allowing marketers to focus on judgment, governance and accountability.
The findings also point to a broader lesson. AI works best when it has access to well-organized content, consistent metadata, clear product guidelines, and defined approval processes. Without that context, even sophisticated AI has trouble making reliable decisions.
That’s why many organizations treat their DAM platform as a foundation for AI governance. Instead of simply storing assets, these systems are becoming a place where AI can access the rules, permissions, and context needed to support content creation, review, and distribution at scale.
Marketing has spent the last two decades performing repetitive tasks. AI moves the conversation in a different direction. The challenge is no longer how much work can be automated. It determines where automation should end and human judgment should begin.
Bynder’s “State of DAM 2026 Report” is available for download here. (Registration required)
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