New Harvard Business Review Analytic Services Research Exposes the Gap Between AI Ambition and Enterprise Readiness

Study finds most organizations recognize the need for connected data, content, and workflows, but few have built the operational foundation required to scale AI

CLEVELAND, April 29, 2026 /PRNewswire/ -- Hyland, a global leader in enterprise content management (ECM) and the pioneer of AI-driven content intelligence with the Content Innovation Cloud , today announced new research from Harvard Business Review Analytic Services, Bridging the Readiness Gap to the Agentic Enterprise, showing that enterprise AI ambition is advancing faster than enterprise readiness. While organizations increasingly recognize that AI success depends on connected data, content, and workflows, most have not yet built the operational foundation required to scale it.

The gap is especially visible in how organizations are managing enterprise information. While nearly all (94%) of respondents say well-connected data, processes, and applications are highly important to successful AI adoption, less than a third (27%) say those elements are well connected in their organization today. And although 65% say their structured data is somewhat or fully prepared for AI use, only 39% say the same about their unstructured data, including emails, PDFs, images, video, and other document-based content that make up much of the information businesses rely on every day.

Untapped Opportunity in Unstructured Data

For many organizations, the issue is not a lack of data. It is that much of the most operationally important information remains trapped in unstructured data spread across repositories, applications, and workflows. The report suggests that closing this gap will require more than deploying new AI tools. It will depend on building a stronger foundation for governance, access, and workflow execution, especially as organizations move toward more agentic forms of AI.

"As organizations move into the next phase of AI, the challenge is no longer just access to models, but whether the business is ready to operationalize AI in a way that is governed, contextual, and trusted," said Jitesh S. Ghai, CEO of Hyland. "The agentic enterprise takes shape when AI is embedded into real operational workflows, grounded in the content, data, and controls the business already depends on. For many organizations, unstructured data is both the most overlooked asset and the biggest obstacle to scaling AI effectively."

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