Enterprise AI Search for Businesses: What It Is & Its Importance

From chaos to clarity: What AI search brings to enterprise DAM

Enterprises today manage more digital content than ever before, from brand assets and campaign visuals to product shots, training videos, legal documents, and more. As these libraries grow, so does the complexity of keeping them organized. Without a clear structure or powerful search tools in place, organizations can quickly become overwhelmed with proliferating content. This results in teams wasting valuable time searching for the right content, re-creating or re-buying assets they can’t find, or using outdated content that’s no longer in line with brand guidelines.

That’s where enterprise AI search in digital asset management (DAM) comes in. Unlike traditional keyword-based search, AI-powered search can understand context, recognize visual elements, and interpret natural language, making it easier and faster to discover the right content. With AI-powered enterprise search, creative teams, marketers, and stakeholders across the organization can work more efficiently and make better use of the content they already own.

In this blog, we explore what enterprise AI search is, how it works within an AI-powered DAM platform like Bynder, and why it’s becoming an essential solution for organizations managing large-scale content libraries.

Key takeaways

• Enterprise AI search uses artificial intelligence capabilities like machine learning, natural language processing, computer vision, and optical character recognition to deliver more accurate and relevant search results. 
• With AI enterprise search, teams can find the right assets faster with less effort to get content to market faster and deliver more personalized content experiences that drive conversions and engagement.
• Enterprise-level AI search supports content reuse and repurposing, increases content ROI, and enforces brand consistency and compliance.

What is enterprise AI search?

Enterprise AI search is a search solution that uses artificial intelligence to deliver faster, more accurate, and more intuitively obtained results. Unlike traditional search that relies on keyword matching or metadata tags, AI search uses capabilities like machine learning, natural language processing (NLP), optical character recognition (OCR), and computer vision to interpret user intent and the asset context behind what you’re searching for.

In an AI-powered DAM platform like Bynder, AI search solutions can handle complex queries across massive digital libraries, reducing the time needed to find the right content at the right time. One of the benefits of digital asset management powered by AI is the ability to search and retrieve the most relevant files instantly, without needing to know the exact asset name, metadata, or DAM technology structure. For example, rather than searching for an exact file name and having to understand naming conventions, such as “2024_Summer_Sale_Banner.pdf,” you can simply type “last year’s summer promo banner.” AI enterprise search can also recognize visual elements within images, such as logos, labels, or products, extract text from PDFs and similar files, and convert audio into transcripts for easy discoverability.

In large enterprises where content is distributed across departments and even languages, AI-powered DAM serves as a single source of trust that makes it easy for teams to find what they need in seconds rather than hours, breaking down silos and surfacing the right content at the right time. As a result, enterprise teams can enjoy a more connected DAM experience that speeds up workflows and reinforces brand consistency across all digital touchpoints.

AI technologies used in enterprise search

AI in digital asset management uses several artificial intelligence technologies to deliver faster search results. These technologies include:

• Machine learning: AI enterprise search solutions use machine learning to continuously improve search relevance over time based on user behavior and feedback. When you interact with the DAM, whether clicking on results, refining searches, or favoriting assets, it will learn from this behavior and use that feedback to improve the relevance of future search results. As a result, the system will prioritize assets that are most likely to be used based on patterns and context, creating a more personalized and accurate search experience.
• Natural language processing (NLP): NLP is a field of computer science and artificial intelligence that focuses on how computers can understand, interpret, and manipulate natural human language, combining linguistics and machine learning to analyze both written and spoken language to translate languages, recognize speech, summarize text, and analyze sentiment. AI capabilities like Bynder’s Natural Language Search (NLS) use both NLP and computer vision to understand intent and context, not just individual words, making it easier to find what you’re looking for, even if you’re unsure about how an asset was labeled. In DAM, users can use natural, everyday language when searching for assets in their DAM, such as “Show me products from our most recent campaign,” ending the days when users had to remember exact file names or tags.
• Computer vision: Bynder’s AI-powered DAM uses computer vision, which allows the ability to “see” and comprehend the visual content within images. Computer vision can detect objects, scenes, logos, and text within images, allowing you to discover content even if it lacks descriptive metadata.
• Optical character recognition (OCR): OCR allows DAM systems to extract and index text from inside images, PDFs, and scanned documents. This means you can search for words or phrases that appear visually in an asset, even if that text isn’t part of a filename or tag. OCR is especially useful for making content like presentations and product packaging fully discoverable.

Enterprise DAM AI search features

Enterprise teams can use Bynder’s AI Search Experience capabilities to discover more relevant content faster. Key features include:

• Face Recognition: With facial recognition search, users can locate digital assets, such as images, containing a specific individual’s face. This AI-powered search solution automatically tags image assets when faces are identified to reduce time-consuming manual tagging. Once a person’s face is identified and tagged at least once, Face Recognition will automatically tag all existing and future image uploads across the digital library.
• Similarity Search: Image similarity search makes it easy to find visually similar assets. Rather than having to remember filenames, tags, or metadata, users can use Bynder’s Similarity Search solution to analyze the visual content of an image, such as colors, shapes, objects, textures, and patterns, to surface lookalike images within the DAM, whether they’re tagged or not.
• Text-in-Image Search: Enterprise teams can use Bynder’s Text-in-Image Search solution to discover images containing text, such as those containing signs, product packaging, or labels. Using OCR, Text-in-Image Search scans and indexes text inside image files, so users can find assets using specific words or visuals shown in the visuals, not just the metadata or keywords.
• Search by Image: This AI enterprise search solution helps users find similar or related images within their DAM by uploading an image or pasting an external URL instead of typing in keywords. This is helpful when you don’t know how an image was tagged or what keywords to use. Instead, you can upload a reference image to find what you need and avoid buying the same or similar stock images.
• Natural Language Search (NLS): Bynder’s Natural Language Search solution allows users to search for assets using everyday, natural language. NLS is able to interpret keywords and understand the visual content of an asset, making the search process more intuitive and faster.
• Speech-to-Text: Enterprises with vast digital libraries consisting of multiple languages can benefit from Speech-to-Text, which automatically transcribes spoken words in videos and audio files, making the content discoverable by text. This means users can type in a phrase or keyword that was said in a recording, and relevant clips where those words were spoken will be surfaced.
• Agentic AI: Bynder created the first DAM AI agents, which is a system that can understand conversational human language to perform tasks and end-to-end workflows autonomously. One of the many tasks AI agents can do is enrich assets with metadata, which helps improve the discoverability of content. For example, enrichment agents can identify exact materials in product photos or specific dog breeds in image assets to help teams find the exact content they’re looking for. This allows for faster adoption and quicker training, especially for global organizations. 

Benefits of enterprise AI search in DAM

AI-powered search brings a range of benefits for enterprise teams managing large digital asset libraries. Here’s how AI-powered enterprise search supports better workflows, promotes stronger branding, and ensures smarter content use:

• Enhanced asset discoverability: AI search enables teams to find the right content at the right time, even when users are unsure of what they’re looking for. By understanding the context behind a search, recognizing visuals, and interpreting natural language, users can quickly surface assets they need that traditional search might miss.
• Improved productivity: The ability to find assets faster means busy enterprise teams can spend less time on admin and more time on strategic business initiatives. By identifying the necessary assets, whether for a campaign or newsletter, teams can create more personalized content experiences, push content to market faster, drive conversions, and boost engagement.
• Content reusability: AI search helps prevent duplicate work by making assets easier to find and reuse. This way, enterprise teams can locate assets in their DAM that may be hidden or forgotten without having to recreate them from scratch or purchase new ones.
• Increased content ROI: AI search uncovers underutilized or forgotten content and brings it back into circulation, extending the life of content, improving usage rates, and increasing ROI across your content library.
• Compliance and brand consistency: With AI enterprise search solutions, enterprises can implement an effective governance strategy and maintain control over their digital assets, ensuring that usage rights and expiration dates are monitored. Consider world-renowned tea brand Lipton, for example. Lipton used Bynder’s Search-by-Image solution to locate 600 assets among the 95,000 in the DAM without relying on metadata to deliver a website update in one month rather than the estimated six. AI enterprise search solutions help brands save on both internal and external resources due to greater efficiency.

Examples of enterprise AI search

Enterprise teams can benefit from AI search in more ways than one. When large organizations are spread across time zones and continents, AI search facilitates global collaboration and enables various teams to find the necessary assets to complete their tasks. Take a marketing team, for example. When preparing for an upcoming summer sales campaign, marketing teams can use AI search solutions like Natural Language Search and type “last year’s summer campaign banner.” Bynder’s AI-powered DAM will quickly surface relevant assets, allowing teams to draw inspiration from previous campaigns within seconds.

Consider a real-world example with Sauber, a Formula 1 racing team that takes thousands of photos on race day. Using Bynder’s AI-powered search solutions, Sauber was able to quickly discover and distribute omnichannel content experiences from thousands of race-day photos without manually reviewing them one by one. Using Face Recognition, Sauber is now able to automatically detect individual racers in photos upon upload, quickly finding and sharing content featuring specific team members across platforms. As a result, Sauber can create more personalized, character-driven storytelling that captivates their audience.

From AI in content marketing to AI in digital marketing, enterprises can quickly discover assets and drive meaningful business results, including delivering more personalized content that converts, increasing team productivity, and improving content ROI.

Learn how Sauber uses AI-powered search to deliver personalized omnichannel experiences

Enterprise AI search FAQs

How do you choose the best enterprise AI search solution for your team?

Choosing the right enterprise-grade search solution requires careful consideration. Keep these factors in mind as you choose the best enterprise AI search solution for your team:

• Scalability: Your AI-powered DAM should be able to handle a growing volume of assets and users without slowing down. Scalability ensures you can easily manage thousands or millions of files with AI search performing consistently and reliably.
• Security: Enterprise-level content often includes sensitive or restricted materials. Make sure your AI search solution supports user roles, permissions, and secure access to ensure the right people see the right assets. Bynder’s DAM is AI-powered and human-approved, keeping humans in the driver’s seat to allow for responsible AI usage.
• User-friendliness: Even the most powerful AI search won’t help if it’s hard to use. Bynder’s user-friendly interface makes it easy for users to adopt, thanks to natural language support, clear filters, and easy navigation.
• Integrations: AI search should work smoothly with the rest of your martech stack. Bynder’s AI-powered DAM serves as a system of record at the heart of your tech stack, easily integrating with PIM, CMS, CRM, and project management systems to keep daily workflows moving effortlessly.

What are the different types of enterprise search?

As organizations accumulate more content across platforms and departments, finding the right information becomes increasingly complex. Over time, enterprise search solutions have evolved to address these challenges. Take a look:

• Siloed: In a siloed setup, each system, such as a shared drive or CMS, has its own separate search function where users have to know where to look and run individual searches across platforms.
• Federated: Federated search improves on siloes by allowing users to search across multiple platforms at once, pulling results from each source and showing them in a single view.
• Unified: With unified enterprise search, data is aggregated and indexed from all connected systems into one centralized search experience and delivers a singular set of results.
• AI-powered search: AI-powered search builds on unified search by adding intelligence and machine learning, where systems can understand natural language, recognize images, and learn from user behavior. As a result, teams can benefit from the most advanced and efficient search solution for managing large volumes of content.

How does enterprise AI search differ from traditional keyword search?

When looking at the evolution of digital asset management, it began as a straightforward solution that enterprises could use to store their digital assets easily. They could then add metadata and keywords to those files to make them discoverable. Traditional keyword search relies on matching exact words or phrases in file names, metadata, or tags. If users don’t have the right terms, they might not find what they need. 

Fast forward to 2016, Bynder became the first to integrate AI into digital asset management. Today, Bynder’s AI-powered, enterprise-grade DAM can understand the meaning behind a user’s query, interpreting the context, intent, and related concepts to deliver accurate results. Enterprise AI search is more intuitive, allowing users to search for assets even if exact keywords aren’t used in filenames, tags, or metadata.

Improving asset discoverability with enterprise AI search

AI search is no longer a luxury for enterprises; it’s a necessity for organizations that need to manage large and complex digital asset libraries. AI-powered search delivers faster, smarter, and more relevant search results that help teams work more efficiently, reuse and repurpose valuable assets, and maintain brand consistency.

Bynder’s AI-powered DAM is designed for enterprises seeking a solution that can manage their growing content. With AI search solutions like Face Recognition, Text-in-Image Search, Similarity Search, and more, teams can make the most of their content to deliver measurable business results that drive engagement. Book a demo today to learn more.