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For years, marketers have looked to automation as the answer to growing demands for content. Build enough rules into your workflows and the system can handle the rest. AI proves that this is not true.
According to Bynder’s “State of DAM Report 2026,” 93% of businesses face content challenges that their existing rules-based automation cannot solve. The biggest problem is not publishing content faster. They detect off-brand assets, govern AI-generated content, produce personalized content at scale, and manage increasingly complex workflows.
Rules-based automation works well in anticipated scenarios. However, the AI doesn’t follow the rules well. He likes to add things as he goes along, imagining that he knows what you “really” want. So marketers have gone from “Yeah, look at all the content AI can create” to “What did it do this time?”
Security is now the top concern for marketers when using AI in content operations, followed by legal and regulatory compliance and inaccurate or misleading results. Respondents also raised concerns about inconsistent branded content and scaling AI without creating new workflow bottlenecks.
These concerns extend beyond DAM. Every marketing organization is working to balance faster content production with copyright compliance, brand governance, privacy requirements, and increasing oversight of AI-generated content. As AI becomes integrated into marketing operations, governance becomes a part of day-to-day campaign execution rather than a final review step.
Humans remain responsible for the final decision
From brand governance to metadata management, content quality, and tailoring assets to different channels, the most common workflow combines AI and human approval. Around 40-44% of respondents said that automation does the work while users make the final decision. Between 31 and 35 percent rely on mixed workflows that combine automation and manual review throughout the process.
Rather than replacing people, AI takes over repetitive work, allowing marketers to focus on judgment, governance and accountability.
The results also point to a broader lesson. AI works best when it has access to well-organized content, consistent metadata, clear brand guidelines, and defined approval processes. Without this context, even sophisticated AI struggles to make reliable decisions.
This is why many organizations view their DAM platform as the foundation of AI governance. Instead of simply storing assets, these systems become the 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 automating repetitive tasks. AI is moving the conversation in a different direction. The challenge is no longer how much work can be automated. It’s about deciding where automation should stop and human judgment should begin.
Bynder’s “State of DAM 2026 Report” is available for download here. (Registration required.)
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