Peanut butter + jelly. Rock + roll. Barbie + KenGreta Gerwig. These pairings are recognized crowd pleasers, but what’s the latest match made in heaven?
AI + enterprise search.
This combination of generative AI and internal search powers knowledge discovery like never before. By introducing artificial intelligence and machine learning to your company’s data sources, you get better, more relevant results than traditional search.
Chances are, you already believe in the positive impacts of generative AI – just like 97% of business owners who think ChatGPT will benefit their business. But maybe you don’t yet know what that impact will look like.
The list below offers clarity. It explains the strategic benefits provided by AI-powered enterprise search and ties specific features to powerful outcomes.
This article is Part 2 of our guide on enterprise search tools. For an introduction to enterprise search and how it works, check out Part 1 on enterprise search as a service.
Must-have features of enterprise search
Any worthwhile enterprise search platform has to keep up with big search engines’ features. Google has set the standard for UX and UI, as well as for powerful AI that uses searcher intent to provide relevant results. Here are some of those must-have features.
- Relevance rankings: automatically display most relevant search results first
- Faceted search: refine your search by filters, such as date created, owner, or file type
- Predictive suggestions: get recommended answers before you finish typing your query
- Related search suggestions: view similar questions and phrases people search for
- Semantic search: return results that are contextually related to the search query
- Natural language processing: engage in a more conversational search experience
These features enable easy, intuitive search across multiple sources of information. Learn how your company can leverage these capabilities to reap the full benefits of AI enterprise search.
How you can benefit from AI-powered enterprise search
1. Find what you need with relevant, conversational search 🔎
Traditional search requires specific keywords and queries adapted to computer syntax, so you have to know exactly what you’re looking for. Instead, AI-driven enterprise search interprets human language to surface relevant insights. Here’s an example:
- Traditional lexical search: “customer story AND Chegg AND Pat”
- AI enterprise search: “Where can I find an interview with someone who achieved productivity gains using our product?”
- Both return a customer story about Pat, a fast-paced marketer at Chegg
This ability is built off ever-advancing semantic search.
What is semantic search?
Semantic search is AI-driven search with a human-like understanding of intent, meaning, and relevance. It relies on natural language processing (NLP) to analyze semantic context and decipher intent behind the search query, and it can use vector search to improve semantic accuracy. This powers faster, more relevant information retrieval.
2. Put time & productivity toward better work – not busy-work ⏱️
There are countless ways to save time with AI-powered enterprise search. It enables faster retrieval of relevant data and requires less manual searching. As seen in the example above, semantic search helps users find what they need without knowing exact keywords and filenames. Don’t waste time down search rabbit holes; get what you need and move on to more critical tasks.
Another way AI boosts productivity? It surfaces relevant insights. Related search suggestions are only one way AI improves discoverability. It can also compile information from multiple sources to give a comprehensive answer.
This helps you brainstorm better, iterate faster, and stay focused on critical tasks. For another key enterprise productivity tool, read about GoLinks for enterprises.
3. Access information from all your integrated sources 🗃️
With AI enterprise search, you can access data across all content sources, including cloud storage, knowledge bases, intranets, and more. This gives you a unified search experience.
Most search platforms can access structured data, which is clearly organized into a computer-readable format. But AI lets you search unstructured data – such as docs, videos, and emails – just as effectively, powering access to relevant information no matter where it lives or how it’s formatted.
4. Ensure your growing business stays competitive at scale 📈
Enterprise companies need room to grow. AI-powered search systems can handle high volumes of data and heavy traffic, allowing you to scale-up seamlessly.
AI also helps you maintain a competitive advantage. A survey from August found that the majority of organizations will be using generative AI within 12 months. In other words, organizations that don’t adopt AI will be left behind.
Learn about 10 generative AI tools that can help you keep up in today’s market.
5. Lock down data with powerful privacy & security 🔐
Sometimes you don’t want every piece of information accessible – like personnel files or private emails. AI lets you implement varied access policies, which equates to better protection.
For instance, with permission-aware access, AI can determine the underlying permissions of a data source and enforce appropriate access restrictions. So a search for “Paula’s exit interview” will only return results to Imran in HR. Otherwise, the information is private and inaccessible to other employees.
6. Gain insights and analytics to inform company decisions 🔮
In-depth analytics provide insight into users’ search behavior, which can shape business strategies and clarify content needs. Access to accurate and up-to-date information improves decision-making and generates actionable insights at every step of the company ladder.
Resource analytics clarify what people are using and highlight content gaps. For instance, popular queries that yield few results indicate room for improvement. If many people are searching for “WFH guidelines,” HR should write a guide that provides quick answers and asynchronous support.
7. Improve users’ experience (and their output) 🦾
Even at the enterprise scale, the individual’s experience is crucial. AI enterprise search helps deliver more personalized content to users based on their search history, preferences, access permissions, or even job title. Powerful GenAI chat remembers earlier parts of the conversation, so you get follow-up answers with context.
Person-level customization ensures the system works for everyone, with AI enabling individual data connections that stay private. That means you can connect and search your email records, but nobody else can.
AI-powered enterprise search FAQ
- How does AI-powered enterprise search handle data privacy concerns, particularly in terms of accessing and retrieving sensitive information like personnel files or private emails?
AI-powered enterprise search addresses data privacy concerns through features like permission-aware access, which allows organizations to implement varied access policies. For instance, the system can determine underlying permissions of data sources and enforce appropriate access restrictions. This means that sensitive information, such as personnel files or private emails, can only be accessed by authorized individuals. For example, a search for “Paula’s exit interview” will only return results to Imran in HR, ensuring that confidential information remains private and inaccessible to other employees.
2. How does AI-powered enterprise search handle data integration and compatibility across various data sources and formats, particularly for businesses with diverse systems and platforms?
AI-powered enterprise search typically addresses data integration and compatibility challenges by offering capabilities to access and search across various data sources and formats. This often involves integrating with existing systems, databases, cloud storage, knowledge bases, intranets, and more. The system is designed to handle structured and unstructured data effectively, enabling users to retrieve relevant information regardless of where it resides or how it’s formatted. However, the specific mechanisms for data integration and compatibility may vary depending on the enterprise search solution and the complexity of the organization’s data ecosystem.
3. What are potential biases or inaccuracies that AI algorithms may introduce, and how these are mitigated in enterprise search solutions?
Although AI-powered enterprise search systems are designed to improve search relevance and productivity, they may still be susceptible to biases or inaccuracies inherent in AI algorithms. These biases can stem from various sources, such as biased training data, algorithmic biases, or inherent limitations in natural language processing (NLP) models. To mitigate these risks, enterprise search providers often employ techniques such as algorithmic transparency, bias detection and correction mechanisms, and ongoing monitoring and refinement of AI models. Additionally, organizations may implement governance frameworks and ethical guidelines to ensure responsible use of AI technologies and minimize potential biases in search results.
How to find an intelligent enterprise search solution
Choosing the right enterprise search software is important – you want a solution that offers the right benefits for your company.
We’ll walk you through the decision in our guide’s final installment on the best enterprise search software. We’ll point out what considerations you need to weigh, and we’ll recommend the right tool for the job.
Spoiler alert: GoSearch has everything you need for powerful knowledge management. Schedule a demo to learn why this intelligent search platform is the peanut-butter-and-jelly sandwich of AI-powered enterprise search.
