Blog / November 10, 2025

Enterprise Search: How AI-Powered Search Breaks Down Application Data Silos

Amy Brennen, Senior Content Marketing Manager

enterprise search silo

Highlights

  • Information silos hurt productivity: They arise from tool sprawl, fragmented knowledge bases, and strict security controls, making it harder for employees to find accurate, up-to-date information.
  • Silos create hidden costs: Employees waste hours searching for data, duplicate work, and miss opportunities for collaboration and innovation, which undermines efficiency and the employee experience.
  • AI-powered enterprise search breaks silos: By unifying data across disparate systems, it uses semantic search and generative AI to deliver contextual, accurate, and personalized answers.
  • AI enhances search by improving the quality of retrieval and creating useful summaries. It uses advanced capabilities like natural language processing to understand the user's intent and context, not just keywords, for more personalized results and can generate concise, easy-to-read summaries of search results.
  • The right solution balances power and usability: Enterprise search platforms should offer natural language understanding, comprehensive connectivity, scalability, granular security, and easy deployment to maximize adoption and value.

Your finance team swears by one expense policy. HR just rolled out another. Meanwhile, sales and marketing each track customer data in their own systems.

The result? Everyone’s working with a different “truth”—the classic symptom of an information silo.

Information silos can arise from a variety of factors, including incompatible systems, lack of communication, or differing (or worse, conflicting) departmental priorities, leading to employee frustration and stalled productivity.

In these instances, each team picks its own collaboration tools, creates separate knowledge bases, and builds workarounds that make finding reliable and relevant information feel like a treasure hunt.

But there's a better approach. 

AI-powered enterprise search tools can change how teams access knowledge by connecting information from different, often departmentally specific, applications while maintaining strict security and compliance. 

Instead of complex manual integrations, search tools using agentic AI and agentic RAG can be used to search and unify knowledge across an entire tech stack, turning scattered data into a single source of truth for decision-making.

We'll discuss the challenges of information silos, how to use enterprise search to help employees find what they need, when they need it, and even take action to resolve their queries (such as filing a PTO request, as opposed to merely looking up PTO policy). 

Why do information silos happen?

Information silos aren't usually intentional. They typically develop organically as organizations grow and departments optimize and focus on their specific needs. Being aware of why and how they form can help you address the root causes, rather than feeling the continued effects of the symptoms.

Tech overload and tool sprawl

Your teams likely use dozens (or even hundreds!) of SaaS applications, as each department has its own unique requirements. Marketing needs design tools, sales wants CRM functionality, and engineering needs development platforms.

This tool sprawl creates disconnected data islands where information lives in isolation—so much so that anywhere from six to 15 hours of productivity may be lost every week. When every department picks its own tools, you might end up with customer data in Salesforce, project updates in Slack, policies in SharePoint, and training materials in your learning management system.

The problem is when information lives in different places, employees have to look in several places to stitch an answer together. This recall tax of knowing where to look and where the answer might be can end up turning into a huge productivity loss.

Fragmented knowledge sources

In many organizations, poor knowledge management creates a critical challenge: a lack of a clear, trusted source of truth. Employees, faced with this vacuum, tend to prioritize speed and convenience over credibility, often relying on unofficial, easily accessible information (like a coworker's shared document) rather than official, business-verified policies from departments like HR, IT, or Finance. 

This tendency to use the most easily available information, regardless of its authority, can lead to misinformation, inconsistencies, or business risks, when the primary source of truth becomes lost in a sea of less-credible, but more easily found, alternatives.

Security and compliance barriers

Security and compliance requirements are a key (yet non-negotiable!) cause of information silos, as they mandate strict access controls to protect sensitive data (e.g., PII, regulated information). With this comes identity and access management sprawl: different legacy systems, clouds, and applications each have unique, often conflicting, permission structures and authentication methods. 

This complexity makes it very difficult to enforce consistent, granular security policies across the enterprise while simultaneously enabling necessary knowledge sharing and ensuring users can only surface and view the answers they are authorized to see.

The impact of information silos

Information silos can create hidden costs that inflate over time, affecting everything from daily employee productivity to strategic initiatives.

Nearly 47% of digital workers struggle to find information to perform their jobs, meaning  employees often waste valuable time just searching  instead of doing meaningful work.

This can often manifest as duplicating efforts when they can't find existing resources, recreating documents that already exist, and delaying projects while waiting for answers.

Silos can also undermine collaboration and innovation. When teams can't easily share knowledge, they miss opportunities to build on each other's work or learn from past successes and failures.

Perhaps most importantly, information silos hurt the employee experience too. New hires struggle to get up to speed, experienced employees feel frustrated by inefficient processes, and everyone loses confidence in the systems they're supposed to be relying on.

How AI enterprise search helps solve information silos 

Enterprise search engines are able to bring together all your systems and content—Slack/Teams/intranet, and more— and ue AI to simplify and accelerate information retrieval and understanding. They go beyond keyword matching to understanding user intent, context, and relationships between different pieces of information.

  1. AI-powered search platforms use natural language understanding (NLU) and semantic search to grasp what employees actually mean — not just what they type.
  2. They perform unified searches across all enterprise systems and knowledge bases, retrieving relevant, verified information instead of a list of links.
  3. Generative and agentic AI then synthesize this information into contextual, actionable summaries that help employees make decisions faster.
  4. The real advantage comes from context: search solutions that personalize results based on business terms, employee roles, permissions, and intent — ensuring every answer is accurate, relevant, and aligned with how work actually gets done.
  5. By connecting fragmented knowledge and delivering insights in seconds, enterprise AI search helps organizations eliminate information silos, speed up decision-making, and keep work in motion.

Employees expect that ChatGPT-like experience now, or still get a traditional Google-like search experience. So having that flexibility to search as users prefer is crucial.

Understanding Agentic RAG

AI and agentic RAG make this possible by understanding intent behind natural language questions, then pulling answers directly from the most relevant and up-to-date sources.

They also adapt results dynamically based on context, role, and prior interactions, ensuring every employee gets both speed and accuracy without needing to know exactly where to look. Here’s how:

  • Agentic AI: Automates smarter, contextual answers: Enterprise search pulls the right results and uses AI to uplevel it (for example, with summarized responses, it can understand your goals and intent). Agentic AI can completely change the way we find information. Agentic AI brings intelligence and autonomous decision making. 
  • Agentic RAG: Specifically for search, agentic retrieval-augmented generation (RAG) combines the strengths of AI agents with RAG to incorporate autonomous reasoning and decision making as part of finding relevant information. This approach allows for managing complex tasks across diverse and extensive datasets.
  • Natural Language Understanding (NLU): Your search solution should understand context, relationships, and the user's intent. Instead of just matching keywords, look for platforms that use NLU to interpret conversational queries like, "What's our policy on remote work equipment?" 

This is where agentic RAG becomes crucial. It allows the search agent to dynamically determine the best retrieval strategy and even refine its search based on user feedback or subsequent actions. This approach is a significant improvement over traditional RAG because the agent can proactively seek out additional context or clarification, leading to more precise and relevant answers.

  • Comprehensive connectivity: A combination of indexing and live APIs ensures your search platform can access the full breadth of systems, knowledge bases, and content types across your organization. 

The more content connectors available, the more comprehensive and effective your agentic search coverage becomes.

  • Enterprise security & scalability: Your solution needs to handle millions of documents, support different file formats and types, and deliver fast results to thousands of users. 

At the same time, it must manage security and permissions effectively, ensuring that AI agents only access information they are authorized to see, maintaining data integrity and compliance.

  • High search quality: The ability to deliver precise answers—rather than just a list of keyword-matched documents—means employees spend less time searching and more time acting. Features like sentence-level embedding and semantic search help surface the most relevant information from across the organization. When users can quickly find what they need, adoption increases and frustration decreases

Learn how to unblock productivity and empower your workforce with Enterprise Search

Break down silos and empower productivity with Moveworks

Eliminating information silos can transform how your organization operates, driving productivity across every department and elevating employee experience.

Moveworks Enterprise Search brings a new approach to enterprise search, delivering AI-powered, context-aware search that lets employees find the right answer, right away, across your applications.

We do this by enhancing retrieval with reasoning and agentic RAG to understand employee goals, creates intelligent strategies, and searches across multiple business systems to deliver accurate, high-quality results.

Here's how Moveworks transforms enterprise search:

  • Agentic RAG for better accuracy: The reasoning engine delivers improved accuracy and reliability of answers, helping drive widespread adoption of search solutions across your organization.
  • Citations: Citations and source linking help solve information distortion through hallucination, so that employees are able to trust the answers they receive.
  • Search plus action: Enterprise Search doesn’t just retrieve answers—it can automate tasks and workflows across enterprise applications, eliminating tool switching and driving productivity.
  • Comprehensive connectivity: Over 50 connectors integrate the Moveworks Enterprise Search system with the most useful information repositories, as well as the ability to add custom content systems.
  • Granular security controls: Strong permissions and access controls enable the right employees have access to the right information while maintaining security rules and standards.
  • Enterprise-scale reliability: The platform scales to support large data volumes and the variety of business objects common in enterprise environments.
  • Actionable analytics: Detailed analytics and metrics can help stakeholders monitor adoption, track usage patterns, and make data and AI-driven decisions to continuously improve the employee user experience.

Together, these capabilities create a solution that's enterprise-ready, with the reliability, scalability, and security that organizations need, to give your employee the intuitive, real-time search experience they need to search and take action—not just return results.

 

Break free from information silos and streamline the way your team accesses internal knowledge. Discover how Moveworks Enterprise Search makes it possible to unlock your organization's collective intelligence with Agentic AI that reasons, plans, and delivers results instantly.

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