Enterprise content management (ECM) technologies assist businesses in maximizing the value of structured and unstructured data. These systems are also known as Content Services Platforms, owing to their expanding breadth (CSPs). Most ECM systems still use rules-based techniques to extract, categorize, and enrich data, even though they used previous artificial intelligence technologies no longer labeled AI.
Companies can execute standard ECM or CSP applications in a more automated manner with greater levels of compliance thanks to developments in artificial intelligence, machine learning, and intense learning. Traditional ECM firms are creating AI skills to catch up as new vendors emerge to supply these capabilities.
What Exactly Is ECM?
ECM enables businesses to derive commercial value from their content and automate content-dependent activities.
Other industry experts use more esoteric terminology:
Enterprise Material Management (ECM) is defined by the Association for Information and Image Management (AIIM) as “the strategies, methods, and technologies used to collect, manage, store, preserve, and transmit content and documents linked to organizational activities.” Thanks to ECM, documents and other business material are structured, classified, meaningful, and easily searchable. ECM is in charge of capturing content streams in various formats, including text, video, audio, databases, etc. ECM stores almost all of the company’s files (Word documents, Excel spreadsheets, PDF files, and so on) so that it can provide them when needed.
ECM is a long-standing idea, and to reflect its expanding breadth, industry experts have coined new names to describe it:
Gartner refers to ECM as a Content Services Platform (CSP). Gartner describes CSP as an integrated platform that provides content-focused services, repositories, APIs, solutions, and business processing tools to enable digital business and transformation.
According to the Association for Information and Image Management (AIIM), companies should adopt new information management techniques beyond standard ECM. They term this more modern approach Intelligent Information Management (IIM).
Distinction Between Content And Knowledge Management
Knowledge management is a single platform that searches for, collects, updates, and stores relevant information. Anyone may generate or edit material in real-time, initiate a conversation, and work with colleagues from other departments. Knowledge management is a subset of content management that focuses on the dissemination of knowledge. For knowledge management, some providers have integrated artificial intelligence systems. One of the knowledge management platforms that use AI-integrated knowledge management is the Maana Knowledge Platform.
What Is An ECM With AI Integration?
By being able to “read” the information on a page, AI takes ECM to the next level. An ECM system driven by AI can identify, classify, analyze, and transmit material in various formats.
Which AI Technologies Are Necessary For ECM Systems To Function?
● Learning Through Computers
A machine learning method like tree-based algorithms (decision trees, random forests), gradient boosting algorithms, neural networks, and clustering algorithms, for example, can be used to train an artificial intelligence integrated ECM to categorize texts. An AI-enabled ECM may learn to recognize document types based on content, classify the document, and determine the best course of action.
Predictive analytics capabilities enabled by machine learning, including time-series analysis, regression analysis, and other forecasting tools, may be used by an AI-powered ECM to extract insights from data.
● Recognition Of images
Images may be auto-tagged upon upload using image recognition technology, and ECM can collect text inside those images without the need for human interaction.
● Transcription And Voice Recognition
More than 500 hours of video were posted to YouTube per minute as of May 2019, equating to over 30,000 hours of new material every hour. That’s why YouTube’s servers are projected to hold more than a billion gigabytes (1 exabyte) of data!
As information is retrieved from audio and video files, speech recognition and transcription technologies play a more significant part in ECMs as the use of video grows in both B2B and B2C communication.
● NLU And NLP
Data and context may be understood deeper, more semantic by AI-powered ECM, enabling data processing. It can decipher the language in emails and other documents. As a result, it may build links between the context of documents, making information more easily retrievable when needed.
AI Apps In ECM
Document processing, unstructured data processing, content management, better search, and collaboration are just a few of the artificial intelligence applications in ECM. Please check our post on AI use cases in ECM for a more in-depth look at AI uses in ECM.
Advantages Of ECM
Cost reductions, quicker procedures, enhanced decision making, increased compliance, and cooperation are all advantages of ECM. Please read our dedicated post on ECM advantages for more information.
Business Functions Using ECM
● Sales: Companies utilize ECM to efficiently retain consumer data and gain insights from it to boost sales.
● Marketing: Content generated for various advertising campaigns is kept in the ECM system and provided when a similar project arises.
● Accounting and Finance: Electronic document management (ECM) automates the processing of documents such as invoices. The removal of such documents speeds up departmental operations.
● Human Resources: ECM streamlines the hiring process and enables HR personnel to create performance assessment reports for current workers in minutes.
● Contract Management: ECM enables contract digitalization, which offers associates benefits such as receiving notifications before contract expiration dates.
● Supply Chain: Because stock data, sales data, financial data, and data given by suppliers are all accessed from the same ECM system, supply chain associates may make better projections.
The need to manage material more efficiently develops in tandem with businesses’ numbers and kinds of information. Applying artificial intelligence and machine learning to content will become one of the most frequently deployed AI use cases over the next several years since it can unlock the insight and value contained within it.