Enterprise Search Challenges: Why It’s Getting Harder to Find Information—Even With AI

Who this article is for: This article is for intranet owners, digital workplace teams, knowledge managers, internal communications, HR, and IT leaders responsible for improving information access, search, and employee productivity.

What this article helps with: It explains why AI alone does not solve findability problems—and how intranets must evolve to act as trusted, governed knowledge layers that support both people and AI. 

AI-powered search, assistants, and agents are spreading rapidly across digital workplaces. Employees can now ask questions in collaboration tools, business applications, intranets, standalone AI assistants, and more—and receive instant answers.

Yet for many organizations, finding the right information still feels harder than it should.

Despite increased investment in AI, employees continue to struggle with fragmented information, inconsistent answers, and declining trust in what they find. The report Gartner’s Predicts 2026: Intelligent Applications Shape the Future of Work highlights a growing gap between AI capability and everyday employee experience.

This article explains why findability is getting worse—not better—and what intranets must do to restore clarity, trust, and structure in an AI-driven workplace.

Learn more: Download the 2025 Gartner Magic Quadrant for Intranet Packaged Solutions to learn more about the intranet space and how vendors compare.

The challenges below explain why enterprise search often gets worse—not better—as AI is introduced. Without a trusted, governed knowledge layer, more AI simply means more noise.

Learn more: Check this blog post out for an overview how intranet search are evolving in 2026 and how organizations should evaluate search capabilities when planning a new intranet.

Employees now encounter search and AI assistants in intranets, collaboration platforms, business applications, and standalone tools. Instead of one clear place to search, they must first decide where to look—adding friction before work even begins.

Gartner highlights this growing complexity clearly, noting that organizations are deploying “multiple enterprise AI search and AI assistant platforms within a single organization,” creating more entry points—but less clarity for employees. 

Most AI search tools and assistants operate within application silos. Each tool sees only a slice of enterprise information, which limits context and produces incomplete answers.

According to Gartner, “embedded AI remains siloed within individual applications,” preventing organizationwide intelligence sharing and reinforcing fragmentation rather than reducing it.

AI relies entirely on the quality of the information it retrieves. When content is outdated, duplicated, poorly structured, or unmanaged, AI-powered search amplifies these weaknesses instead of fixing them.

Gartner warns that poor information quality “pollutes search results with redundant, obsolete, and trivial information,” directly undermining both human decision-making and AI reliability.

Different AI tools often return different answers to the same question. Over time, this inconsistency weakens confidence in search and pushes employees back toward informal channels like chat, email, or asking colleagues directly.

As Gartner observes, employees increasingly feel “lost in a sea of information,” even as AI investments grow—because answers lack consistency, context, and authority.

Employees frequently don’t know which source is authoritative. Without a trusted reference point, search becomes guesswork rather than reliable decision support.

Gartner stresses that many enterprises lack “a shared foundation for information quality and governance,” making it difficult for employees—or AI—to determine what should be trusted.

AI-generated answers often lack transparency around sources, ownership, and validity. Yet employees remain accountable for decisions based on those answers.

Gartner describes this as an emerging “moral crumple zone,” where workers are held responsible for AI errors despite having limited ability to verify, challenge, or correct the output.

Many organizations invest in AI tools without addressing information architecture, ownership, lifecycle management, and governance. As a result, findability degrades over time—even as technology improves.

Gartner consistently emphasizes that search and AI cannot succeed without strong information governance, warning that “if search does not work for humans, it will not work for machines either.”

This is where the intranet becomes strategically important again. In Gartner’s view, organizations need trusted knowledge foundations to ground AI, assistants, and agents. For most enterprises, the intranet is the only platform positioned to play that role.

When designed well, the intranet can:

✔ Access to knowledge: Provide curated, governed entry points to enterprise knowledge.

✔ Information structure: Establish a shared information structure across systems.

✔ Surface the right information: Surface authoritative content for both people and AI.

✔ Coordinate and unify: Reduce fragmentation by acting as a coordination layer.

Rather than competing with AI search tools, the intranet should anchor them—ensuring that answers are grounded in trusted, maintained information. This aligns with a broader shift highlighted in Gartner’s research: moving from scattered information access toward fluid knowledge, where content, context, and governance travel together. 

Learn more: Read this blog for 10 practical intranet search tips to help you deliver an improved search experience.

Gartner’s findings point to a clear set of priorities for organizations struggling with findability:

✔ First, stop treating search as a feature. Findability is an experience outcome that depends on information quality, structure, and governance.

✔ Second, reduce fragmentation by clarifying where authoritative information lives—and how AI tools should access it.

✔ Third, invest in governance as an enabler, not a constraint. Metadata, lifecycle rules, and ownership models are prerequisites for AI success.

✔ Finally, use the intranet deliberately as a trusted knowledge layer—not just a publishing channel or link hub.

Organizations that take this approach are better positioned to improve findability for employees today and create a reliable foundation for AI-driven experiences tomorrow.

Learn more: Study this blog post to learn more about content governance and findability: AI Intranet Search: Why Content Governance Is Essential.

AI-powered search and assistants promise faster access to information—but without structure, they often deliver the opposite. Gartner’s Predicts 2026 research makes it clear that findability is getting harder, not easier, as AI tools multiply.

The root cause is not lack of intelligence, but lack of governance. For intranet and digital workplace leaders, the implication is clear: improving findability in an AI-driven workplace requires investing in information quality, trusted sources, and coherent experience design. When intranets evolve into governed knowledge layers that support both people and AI, clarity—and trust—can be restored. 

Ready to discuss enterprise search in the AI-powered intranet? Welcome to setup a personalized demo of Omnia to see real-world examples and discuss your challenges.