How the company reduced processing time and costs by more than 50%

Using an AI-powered Enterprise Content Management (ECM) system, companies can reduce processing time and costs by more than 50% and make it easier for employees to find relevant information. Let's take a look at AI use cases in ECM, such as document/process automation, facilitating collaboration and content management.

With an AI-powered enterprise content management (ECM) system, companies can simplify processing, reduce costs by more than 50%, while also making it easier for employees to find essential information. Let’s take a look at AI use cases in ECM, such as document/process automation, facilitating collaboration, and content management.

What AI applications are available in ECM?

Document Processing

Documents are everywhere. Some of them are semi-structured data. Documents of a particular type contain some specific data. Like, invoices include the sender and the recipient, and contracts include the parties of the agreement, the terms, the date, etc.

Companies, individuals, and governments use documents to contact each other. Documents are a crucial part of communication.

Bill splitting

Companies often collect multiple documents from their clients and combine them in a single file. For example, a visa application agency may need copies of your ID, passport, bank details, etc., and scan all of these documents into one file dedicated to your application process. ECM splits these documents into separate files and categorizes them in the same folder to be processed.

Document Classification

Different documents have different processing. For example, invoices need to be paid to suppliers, employee receipts as reimbursement payments, etc. Different types of documents can be combined and submitted to the company. For example, a vendor may send a contract with an invoice, and these documents need to be processed in different ways. Therefore, identifying the correct document type is vital to automate document processing.

Artificial intelligence-driven ECM systems can classify documents and store them in a safe and secure environment. Machine learning algorithms learn from existing data to provide more efficient services to companies. Therefore, the information in the company’s existing documents serves as the learning base, and they are stored in the system to provide the database for artificial intelligence. At the same time, depending on the type of document, specific workflows can be triggered for automation.

Document Data Collection

With machine learning models of artificial intelligence, document data capture technology can extract data from documents with high accuracy.

Capture/Extract Data Processing

Once data is captured, it can be analyzed, validated or supplemented to ensure end-to-end process automation. For example, semantic analysis and natural language processing techniques can be used to analyze text data captured from documents.

If you would like to learn more about document processing, please feel free to check out Share Creators‘ articles on document automation and contract automation.

Unstructured Data Processing

Email, video, and audio files are classified as unstructured data because unstructured data does not include any common data other than specific metadata (e.g., emails, except for, e.g., sender, recipient, and email delivery date). This data also needs to be analyzed and processed.

Email

For example, an AI-driven ECM can analyze the semantics used in emails and other unstructured documents to obtain employee, project, and customer relationships by analyzing document contextual information.

Video

Object detection and motion recognition are widely used in the sports industry to analyze games or players. Clubs often set up video recording systems in their training facilities to extract training data, which helps coaches develop strategies and tactics for real games in a data-driven manner.  Analyze training/game videos to identify information about a player’s health status or attributes. It can provide players with personalized training or diet plans.

Video is also widely used for business and communication purposes. However, many industries cannot extract data from videos and analyze these videos. Companies can use AI-integrated ECM to better understand their customers, employees, or business processes by analyzing video content.

Other

Artificial intelligence technologies such as image recognition and speech recognition can extract information from images and audio files. For example, images uploaded to the ECM system can be automatically tagged by the image recognition system. The content of the images can be tagged as text without human intervention. Similarly, audio files can be transcribed into text files.

Content Management

Advanced Content Protection

Personally, identifiable information is strictly protected through multi-level encryption, and the company protects sensitive customer data and privacy through ECM. ECM, powered by artificial intelligence and data masking technology, helps protect content stored in the system and minimizes the risk of data breaches.

The AI-based ECM system identifies sensitive data, such as a customer’s bank account or tax documents, and makes recommendations for changes. Identifying sensitive data and confidential documents also helps ECM differentiate between these contents and automatically store them in an environment with better protection.

Recycled Content

Companies typically store a variety of data in information silos, and as time passes, some content is discarded in those silos where data or file formats are outdated. According to Gartner, 80% of enterprise data is unstructured. An ECM system with AI integration can read and process this unstructured data, update the format and extract information. As a result, old data can be converted into a searchable format, and new insights can be derived from historical data by integrating AI into the ECM system.

Share Creators‘ AI services enable users to automate key document processing workflows and extract valuable knowledge from these documents by employing natural language classification, optical character recognition, semantic reasoning, and others.

Comprehensive Capabilities

Collaboration

With version control and search capabilities, ECM improves collaboration among employees from different departments. Artificial intelligence-driven ECM can take this collaboration a step further.

Improved Search Functionality

ECM systems also help employees retrieve the information or documents they are looking for. According to Gartner, voice-driven search queries will become the dominant search paradigm, and artificial intelligence-driven ECM systems can provide this service.

Process automation

AI-integrated ECM systems also enable companies to automate their business processes, such as invoice processing. To better understand process automation.

What are some sample case studies of companies that are using AI in their ECM systems?

In particular, large companies with complex documents and data benefit from adopting AI technology in their ECM. We are compiling a list of such case studies.

How are ECM vendors integrating AI into their solutions?

Share Creators Orange.

Share Creators Orange is an AI-powered ECM and enables enterprise-class search through AI technology. Share Creators Orange applies machine learning algorithms to discover documents, classify documents, perform content analysis and deploy pattern analysis.

Share Creators Orange skills.

– Custom Image Insights

– Customize document insights with Share Creators Orange, allowing documents to be automatically tagged based on concepts, entities, or keywords.

With Share Creators Orange, organizations can improve digital asset management through video conversion. Share Creators Orange also offers improvements to document search and selection.

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