The top 6 content management trends in 2026

1. Generative AI

ECM vendors have increasingly embedded GenAI tools into their repositories, typically in the form of AI assistants. GenAI has many ECM use cases, such as improving enterprise search, surfacing relevant summaries, transforming content from one form to another and creating first drafts. ECM tools with GenAI let users interact with their content repositories in a natural, Q&A style.

Generative AI systems may also start to enable an unstructured holistic content delivery model. This would mean everyone working on a product within the enterprise -- even when they don't think their work is content-related -- may be contributing source material for GenAI to process and deliver to the sales, marketing and technical documentation content teams.

For example, Copilot, Microsoft 365's GenAI assistant lets users design intranet sites and draft text content with natural language prompts from within SharePoint. A user might ask the tool to create an employee directory webpage with a blue and white theme and feature the company logo at the top. Copilot can generate a draft that users can edit.

Many vendors have also enhanced their GenAI assistants to more accurately understand the context in which users work. For instance, these tools can respect the security permissions, access controls and classification labels that organizations use to protect sensitive information.

Additionally, these tools can understand the content structure within specific workspaces, such as different project folders, to offer more relevant responses to prompts. For example, an HR specialist working in a folder with information about employee benefits packages might ask the assistant to summarize the company's health benefits for a new hire. The tool can then use information in that folder to generate a response. This targeted approach may extend to building domain-specific language models to provide users with information most relevant to their own work context.

2. Agentic AI

Some ECM vendors have experimented with agentic AI, which refers to advanced AI models that can make decisions and navigate complex scenarios. By early 2026, organizations can expect more development in this area.

Agentic AI tools, also known as autonomous agents, can take on various personas and act as content management specialists or HR assistants to create and automate ad hoc workflows. For example, Microsoft has added Agent Mode and Office Agent that work across Word, Excel and PowerPoint to create complex content based on textual prompts.

These types of agents can handle specialized tasks, collaborate across departments and work with other AI assistants in third-party tools, such as CRM and ERP systems, to execute complex workflows. Among the applications for agentic AI tools are autonomous content lifecycle management, which can automatically archive content, update metadata or initiate approval workflows for these and other content lifecycle changes, potentially saving time and money and improving compliance.

3. Platform expansion

Most content platforms and ECM systems offer core content management functionalities, like document and records management. However, vendors have started to expand their capabilities into new markets, such as robotic process automation (RPA), intelligent document processing, e-signature and document generation.

This evolution lets organizations replace standalone tools with broader, more integrated capabilities from their existing ECM vendors. For some organizations, this approach can simplify business operations and help employees become more efficient.

RPA uses AI software to perform repetitive tasks such as generating periodic reports, managing data entry or handling customer service inquiries. As these capabilities are added to a content management system (CMS), businesses may find opportunities to turn content creation "cost centers" into "profit centers."

4. Line-of-business involvement

In the past, IT leaders made most of the decisions around ECM purchases and implementation because the systems focused mostly on back-end operations. However, as vendors expand their offerings to include more automation features, organizations have begun to involve other business leaders to identify areas or processes to automate.

For example, an HR rep might want an automation in the ECM system to create and send onboarding documents to new hires. To help that user and other nontechnical staff design custom workflows themselves, organizations can invest in ECM systems that offer low-code and no-code development capabilities. These tools offer intuitive drag-and-drop interfaces to help business users who lack coding knowledge design workflows.

Or, AI models may help the legal and compliance teams trigger legal or compliance reviews based on complex or unexpected criteria, routing customized documents when they are needed. Since this data is often sensitive, enterprise controls will need to be in place, such as workflows requiring management or legal teams to approve the AI-proposed reviews.

Another trend is the deployment of domain-specific generative models, which can create first drafts of sales or marketing content incorporating domain-specific syntax and word choice and building on unstructured content in the ECM repository.

5. Predictive analytics

Many ECM systems offer analytics dashboards to track content usage and compliance. For example, an organization's ECM system might show which HR documents employees view the most and least. These insights can help content managers enhance their strategies and remove redundant, outdated and trivial content.

However, as ECM vendors integrate AI more deeply into their offerings, content managers can expect content analytics to become more predictive and proactive in nature. For example, an AI-powered records management tool might notice employees only refer to past employee performance reviews for three years, yet the retention policy mandates the organization keeps them for seven years. The tool could then suggest the records management team reevaluate the records retention schedule.

Predictive analytics can help organizations optimize their ECM strategies, improve operational efficiency and make data-driven decisions across all content management processes. For example, AI can use standard web content management data, such as dwell time, to forecast content usage and lifecycle events, noticing when stale content needs a human review before the standard schedule makes that determination.

6. Automated information security

OpenText Core Threat Detection and Response detects anomalous behavior and insider threat patterns based on user interaction with content. Look for content management systems to use AI to identify unusual patterns within content sets among specific users or user roles. These findings could identify hacks, successful phishing events and other threats to enterprise content and broader information security.

Enterprises concerned with information security should manage the attack surface of AI systems themselves. ECM systems will likely offer zero-trust and role-based access for their AI systems, just as they do for human users, to limit the effect of any compromised AI systems.

Key takeaways

AI remains a key theme for content management in 2026 and underpins many of the top trends, such as GenAI, agentic AI and predictive analytics. Organizations that have yet to create a GenAI strategy can evaluate the tools and pricing options on the market.

Many vendors license GenAI on a per-user basis, which presents a barrier to entry for some organizations. However, a few vendors added AI assistants directly into their enterprise tier business bundles. Additionally, open source and self-hosted LLMs, such as Llama and Zephyr 7B, can be built into custom services that run on an enterprise's ecosystem and perform analysis and generation of content or chatbot responses, without exposing the source corpus to customers or third-party partners.

As ECM systems continue to embed AI capabilities into their offerings, IT and content management professionals should focus on balancing content creator productivity, end-user utility and security controls to find the right mix for their enterprises.

Jordan Jones is a writer versed in enterprise content management, component content management, web content management and video-on-demand technologies.