Documents Are the Overlooked Layer of Enterprise AI Strategy

AI budgets keep flowing to models, agents, and the infrastructure that runs them, yet the documents that hold a company’s knowledge rarely get the same attention. Contracts, playbooks, specs, and records show how a company really works, but they stay invisible to AI until someone connects them. And while 62% of enterprises now run AI for enterprise search or knowledge management in production or pilot, according to ETR, access alone does not make an answer trustworthy.

Trust has not kept pace with adoption. Among companies building their own AI, 67% name data quality as their biggest barrier, according to ETR, and Futurum Research finds only 15.8% of organizations report sustained ROI at scale from AI built in-house. An AI answer needs context: where it came from, how current it is, and whether it matches the original text. Without that context, more documents just mean more work to check.

In our latest thought leadership brief, Documents Are the Overlooked Layer of Enterprise AI Strategy, completed in partnership with Adobe, Futurum Research examines why AI strategies rarely reach the documents they depend on, and how Adobe Acrobat Studio helps enterprises reason across whole document sets, trace every answer to its source, and carry that trusted intelligence into new content and the systems where work already happens.

In this brief, you will learn:

• Why AI adoption is outpacing trust in the data and documents behind it
• How fragmented, unverified documents create cost, risk, and unrealized value
• How Adobe Acrobat Studio, PDF Spaces, and Knowledge Base help teams reason across many documents with every answer traced to its source
• How Analyzer moves trusted document intelligence into the ERP, CRM, and CLM systems teams already use

If you are interested in learning more, be sure to download your copy of Documents Are the Overlooked Layer of Enterprise AI Strategy today.