Hyland CommunityLive 2026 was held in Orlando last week, bringing Hyland customers together from across its product portfolio – OnBase, Alfresco, Nuxeo, and Perceptive. CEO Jitesh Ghai, CTO Tim McIntire, and CPO Michael Campbell delivered the next iteration of Hyland’s vision and roadmap, evolving its positioning of the Content Innovation Cloud (CIC) and Hyland’s role in helping customers transform into a “content-powered agentic enterprise”. Our analysts were there and here is our analysis of their announcements.

Cheryl McKinnon

Principal Analyst

Hyland sees content platforms playing a foundational role in making AI useful, particularly in operational workflows. AI agents grounded in enterprise content, business processes, governance, and industry-specific contexts are better equipped to automate activities and perform actions.

Enterprise Agent Mesh: Now Generally Available

The enterprise agent mesh, announced at CommunityLive 2025, is the top layer in Hyland’s CIC stack. Hyland describes this agent mesh as the orchestration environment for agents, automation, lifecycle management, orchestration, and acts as the control tower for AI agents. The enterprise agent mesh sits on top of an AI-native data and content fabric that includes the Enterprise Context Engine (curation, knowledge enrichment, knowledge graphs, and vertical-specific ontologies to be built by Hyland for its core industries). These AI capabilities leverage the content foundations, composed of Onbase, Alfresco, Nuxeo, Perceptive, along with intelligent document processing (IDP) and federation services to tap into content and data sources from other enterprise applications.

Making It Real for Hyland Customers

With three mainstage demos, Hyland did a good job painting the picture of what could be the near future for the ECM program leaders in the audience. Scenarios depicting the “agentic hospital”, “agentic bank”, and a horizontal accounts payable workflow highlighted how agents, grounded in enterprise content such as policies, operating procedures, patient records, invoices, and loan applications, were able to not only automate manual tasks and speed up routine approvals, but reveal insights that humans likely wouldn’t have seen. To Hyland’s credit, each demo scenario clearly outline which Hyland products were included in the demos, making it real for the customers in the audience. A clear path from a customer’s current investment to the components that could help fulfill their own agentic enterprise vision.

A Call To Action: Use Your Moat and Be a Data Hero

CEO Jitesh Ghai threw down the gauntlet and challenged the customers in the room to get ECM on the radar of their AI and data leaders. While unstructured data (aka documents) are gold for AI agents and assistants, ECM deployments are often off the radar for AI leaders in enterprises. Well-governed, curated content is a safe starting point for AI initiatives, when vendors like Hyland ensure that permission structures are respected, and the context of workflows, metadata, audit trails enrich an agent’s understanding of its environment.

However, Chief Data Officers and AI leaders are often steeped in the world of structured data, and may lack awareness of the content repositories already existing in their enterprises. ECM program leaders must step up and engage with their AI and data leaders and bring their content management expertise to AI initiatives and help identify workflows and use cases to deliver meaningful outcomes and value.

Julie Mohr

Principal Analyst

Industry Knowledge As A Competitive Advantage

Hyland’s wager is that the company already holding an enterprise’s documents holds the shortest path to its knowledge. The Content Innovation Cloud stacks three layers: content at the base, a context and enrichment layer of knowledge graphs and industry ontologies in the middle, and agents at the top. Moving from the content layer to the context layer is what matters for knowledge management. Owning the inputs (claims files, patient letters, loan packages, and case records) stored for decades in regulated industries is real leverage. Hyland is converting 20 years of OnBase metadata and workflow models into the ontologies that give those inputs meaning.

The approach separates Hyland from how the rest of the market pursues the same goal. Hyperscalers and frontier labs start from the model and must acquire the enterprise context. Platform service management incumbents such as ServiceNow and Atlassian start from the workflow and the system of record. The data-and-analytics camp pipes unstructured content into a lake. Hyland starts from governed content itself, and in regulated verticals where provenance and auditability are not optional, starting there is a defensible position rather than a marketing ploy.

The limits are the ones knowledge management has wrestled with for decades, and packaging them as agentic does not remove them. Ontologies and knowledge graphs codify explicit knowledge, the kind already written into documents, while the tacit judgment a senior adjuster applies but never records stays outside the graph. Agents built on flawed content reproduce those flaws at scale.

Governance With Human In The Loop

Hyland’s answer to both is governance plus human feedback loops that pull decisions back into the graph over time. The approach is a more credible story than the build-it-yourself-on-a-foundation-model temptation its customers face, and a more grounded one than rivals selling agents with no enterprise context underneath. The market test is whether Hyland can hold the context layer as larger platforms move into it. Microsoft and OpenText can embed comparable governance and context features into their tech stacks. The standalone advantage erodes once governed context ships as a default feature inside a suite that buyers already own.

For now, Hyland’s industry-specific ontologies, its 30-year depth in regulated content, its open-source repository commitment, and its willingness to run hybrid and on-premise give it a narrower but more durable claim than the broad coverage its larger competitors offer. The proof is turning that claim into a result a buyer can measure, a claim settled in minutes instead of the days an underwriter once needed.

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