A year or two ago, the central question facing most marketing organizations was how widely teams would adopt AI. That debate is largely over. Now, AI is inside nearly every content workflow, and marketing leaders are grappling with how to keep up with the pace of change.

Adoption, it turns out, was only the beginning, as new research from Liferay’s 2026 Digital Content Management Survey, which polled 500 U.S. content managers and digital publishing professionals, reveals. The vast majority of teams have adopted AI, but it’s adding complexity for most. In order to reap the full promise of AI, governance has to become a priority.

Adoption Is Nearly Universal, but Oversight Isn’t

Eighty-six percent of content teams already use AI features in their content tools. Forty-one percent use them extensively. More than half say AI assists at least a quarter of their content output. By any reasonable measure, AI is now part of standard operations.

Whether they trust it is another story altogether. Only 14% of content managers say they completely trust AI to publish content without human review. Another 26% mostly trust it, while 31% trust it somewhat. The remaining 28% don’t trust AI for autonomous publishing much or at all. Despite their widespread use of AI, only a fraction are willing to remove human judgment from the final publishing decision.

Organizations are drawing a distinction, often without explicitly articulating it, between AI as a productivity tool and AI as a decision-maker. Drafting, summarizing, translating, and organizing content are tasks that teams are comfortable delegating to AI. Authorizing the public-facing output of that work requires a different level of judgement, and that’s where most teams are drawing the line.

The leading concern among those who hesitate is accuracy and quality, cited by 34% of respondents. Human review and oversight preferences follow at 30%, as do security and privacy concerns. Marketing teams that operate in regulated industries or manage brand-sensitive content at scale have valid concerns. A confidently incorrect AI output that reaches a customer or prospect before a human reviews it can cause reputational damage that’s hard to undo.

Without Integration, AI Adds Steps Instead of Removing Them

The promise of AI in content workflows is speed and simplicity. The research actually reveals that, without thoughtful implementation, AI tools often add complexity.

Seventy-eight percent of content managers switch between multiple tools to complete a single content task. Among heavy AI users, 31% switch tools very often, compared to just 17% of AI-limited users and 10% of those still piloting AI. The teams using AI most intensively are also managing the most fragmented workflows.

That’s because most teams expand their AI capabilities with features inside specialized tools. They start using a drafting assistant in one system, run localization in another, and perform compliance review in a third platform. Then, the CMS handles publishing as a fourth. Each capability may accelerate its individual step while multiplying the number of handoffs a team has to coordinate. AI accelerates individual tasks, but without integration, the end-to-end workflow doesn’t get simpler.

Teams are feeling the stress. Cross-team coordination and tight deadlines tied as the top day-to-day stressors for content managers at 32% each. Among IT and development respondents specifically, 40% pointed to cross-team coordination as their biggest stressor, the highest of any role segment. Twenty-four percent cited too many tools or platforms as a primary source of stress, and 25% pointed to too many manual processes.

These are solvable problems, and the path forward starts with better governance and integration.

Why Governance, Not Adoption, Is the New Mandate for Marketing Leaders

The report describes an enterprise AI environment where adoption has outpaced the infrastructure needed to manage it responsibly. Marketing teams are using AI extensively, maintaining human review at the publishing stage, and hopping between systems to complete tasks. To gain an operational advantage from AI, leaders have to address the coordination challenges it brings.

Conversations are evolving from “How do we get teams to use AI?” toward “How do we govern AI at scale?” That requires a change in approach. Whereas adoption initiatives focus on encouraging changes in individual behavior, governance initiatives focus on system design. They define how AI agents access data, what they’re authorized to do, how their outputs are reviewed, and how activity is tracked and audited across the organization.

Setting these standards enables marketing teams to address their biggest concerns. Security and trust rank as the top factors when content managers evaluate new business technology, cited by 27% of respondents, which is nearly twice the 14% who prioritize innovation or AI capabilities. Integration with existing systems ranks fourth, ahead of AI features. The teams closest to the work are telling their organizations, through their purchasing preferences, that they need AI environments that fit into governed workflows rather than AI features that require new governance to be built around them.

Several enterprise software vendors are beginning to respond. The broader product movement is toward governed AI environments. With these tools, AI agents operate within existing security and access control frameworks, their work is automatically captured in audit trails, and organizations can connect AI capabilities to their own data without rebuilding compliance infrastructure from scratch. The value proposition is less about what individual AI tools can do and more about whether AI activity can be managed, traced, and controlled.

What Marketers Should Be Watching

The vast majority—93%—of content managers draft content outside their primary content platform. They start in Microsoft Word, Google Docs, asset platforms, and project management tools, then migrate it into the CMS for publishing and governance. Every handoff creates an opportunity for metadata, brand standards, accessibility requirements, and any AI work done during drafting to degrade or disappear entirely before publication.

With many marketing teams managing content at scale across multiple channels, languages, and teams, the handoff problem is also a governance problem. The AI assistance applied during drafting may not carry through to the publishing system. The human review intended to catch AI errors may be reviewing a version of the content that’s already been through several migrations. The audit trail for what AI contributed to a piece of content may be incomplete or nonexistent.

The next evolution of enterprise content management will need to address this directly. Features will still matter, but marketing teams will also evaluate them on their ability to maintain governance and human oversight across the full content lifecycle.

AI strategies that primarily focus on acquiring new capabilities are already out-of-date. The competitive advantage lies in the ability to adopt tools that can be managed, traced, and trusted at enterprise scale. That’s a system design question that most organizations are only beginning to grapple with seriously.

About The Author Of This Article

Bryan Cheung is Co-Founder & CMO at Liferay

About Liferay

Liferay helps organizations build for the future by enabling them to create, manage, and scale powerful solutions on the world’s most flexible Digital Experience Platform (DXP).