The volume and types of content that enterprises manage continue to increase. It is difficult for humans to keep up with this growth and extract the insights needed to drive business forward.
AI and ECM can help break down silos in an enterprise by automating processes that save time and connect people with the information they need to work efficiently.
What is ECM with AI
AI capabilities within ECM help users find what they need quickly and effortlessly. Voice and visual search capabilities, natural language processing and text analysis technology are all commonplace in many ECM solutions, allowing for easier access to information previously difficult or impossible to find.
ML and NLP technology also allows ECMs to understand data and context on a more semantic level, enabling more intelligent processing of content and the creation of relationships between documents. This can include things like deciphering words and their relationship to account, projects or cases, resulting in better organisation of information and faster retrieval when it is required.
Additionally, emerging semantic technologies will enable automated redaction based on specific patterns that identify sensitive information (such as bank account numbers or tax file numbers). This will reduce manual intervention and increase accuracy for organisations with stringent data regulations such as GDPR and Notifiable Data Breaches.
Many organizations have a wealth of insight locked away in documents, but struggle to get to it. The right ECM solution can unlock that insight and make it accessible to employees, helping them save time and effort when working with business content. Combined with advanced analytics tools, this makes for an intelligent content management system that can transform the way a company works and help accelerate its growth.
How does ECM with AI work
A central challenge for any business is keeping all of their information organized, searchable and accessible. AI is a key tool that can help solve this problem and enable organizations to automate processes, grow business intelligence, and engage their teams with up-to-date knowledge and content.
ECM with AI can help make data more usable by automatically tagging and categorizing documents, enabling users to find what they need without having to know where it is stored. This makes it easier for employees to access information and accelerates workflow processes.
Adding AI to the ECM process also helps reduce the need for manual work and enables more people to focus on high-value tasks. For example, in an educational program, an AI-enabled system could automatically test students to determine whether they have mastered certain concepts and then provide more practice for those who need it.
In addition to tagging and categorizing content, AI can be used to enrich traditional files like documents and scanned images. For example, many financial services firms have large volumes of TIFF image files that they need to convert into PDF documents so they can be indexed and searched. An AI-enabled ECM solution can use a public AI service to OCR the text from the TIFF image, map it back to the original document, and then transform the TIFF into a PDF document.
What are benefits of ECM with AI
In ECM with AI, the software can do some of the work that humans traditionally do, making the system more efficient. It can help organize documents and files into folders based on the information they contain, reduce the risk of human error in entering data and automate processes that are time-consuming for people to execute.
For example, ML models can automatically read documents to understand their contents and extract metadata values. This reduces the effort required to prepare new content for use in an enterprise system. It also improves the consistency with which this task is performed and increases the speed with which it is completed.
Another benefit of ECM with AI is better search functionality. ML models can analyze the contents of documents and identify keywords that are relevant to the search query, which speeds up the search process significantly. Additionally, the technology can flag documents that may violate company rules and policies (such as PII) and route them to a special workflow for processing.
Maureen Geudtner, Laserfiche product marketing manager, says that ECM with AI helps businesses to break down information silos and connect all of their content and repositories into a single view. This allows them to grow business intelligence and engage employees with up-to-date content and knowledge.
What industries use ECM with AI
ECM with AI is a key solution for companies looking to improve their information management processes. By integrating artificial intelligence, enterprise content management systems can automate tasks and provide more actionable data. In addition to simplifying complex operations, AI can also boost productivity and reduce manual errors.
Combined with a unified metadata management system, AI technology can streamline the way incoming files are handled and stored. Incoming emails, invoices and receipts can be automatically categorized based on their layout characteristics, which saves time by eliminating the need to manually classify documents. Invoice numbers, due dates, client names and project data can be added automatically, which ensures that the correct workflow processes are triggered.
Integrated AI in ECM can break down departmental silos that slow down team productivity. For example, an automated chatbot can answer questions that aren’t suitable for email or phone, freeing up team members to focus on other work and increasing customer service levels. Generative AI, another feature of some ECM solutions, can further boost collaboration by minimizing redundancy or prioritizing projects based on needs. This enables teams to collaborate more effectively and get more done in less time. The healthcare, retail and IT telecom industries are expected to drive demand for ECM with AI.
What are popular ECM with AI tools
While traditional ECM platforms are great at managing content, they can’t handle everything. That’s where AI tools come in. These tools automate document-driven processes and improve the overall productivity of users so they can focus on more important work.
Modern ECM with AI tools can integrate a wide range of analytics tools directly into their systems. By doing so, users can glean insights from data without having to manually create reports or navigate multiple systems. This allows them to more efficiently track performance and make changes as needed to boost efficiency.
ML and AI can also help with the mundane tasks that often require manual human intervention, such as cataloging files and assigning metadata. For example, ML models can automatically read documents to determine their contents and extract relevant information that would otherwise be impossible for people to identify. This allows teams to save time and resources while ensuring that documents are properly classified, stored and located.
As the ubiquity of mobile devices continues to grow and remote work models take off, many companies are turning to ECM with AI tools for more scalable and agile collaboration. These tools can offer a variety of features like chatbots that respond to voice commands, and search functionality that pulls up the most recent version of a document. They can also automate workflows to ensure that critical documents, such as invoices and contracts, don’t fall through the cracks.
How does AI improve ECM processes
Finding files quickly and efficiently is critical for organizations to maximize productivity. AI tools can improve ECM processes by precisely reading information and context to make files more visible. AI can also help organizations understand and make sense of large numbers of documents by identifying patterns and correlations that would be impossible for people to discern. It can also automatically sort and tag files, identify potential workflow processes based on document types, and initiate automated responses to incoming documents.
Additionally, AI can improve ECM processes by automating critical business functions and helping to eliminate tedious manual tasks. For example, many businesses still process millions of paper forms every year, most of which are handwritten. An AI-enabled ECM system can use machine learning to identify the contents of each form and then automatically convert them into a usable digital format such as PDF or Excel spreadsheet. This can significantly reduce the time it takes to process each form, as well as reduce human error and frustration.
Finally, AI can also help businesses meet compliance requirements by scanning content for sensitive data and personal identifiable information (PII). M-Files recently secured a $20 million funding round led by Bregal Milestone to add a new feature to its intelligent mission management platform. This will allow M-Files to apply its ML algorithms to metadata across multiple platforms and repositories, including those from direct rivals such as Box and Dropbox.
What challenges does ECM with AI face
For most organisations, capturing and managing content is an ongoing challenge. This is due to the massive amounts of data that are created on a daily basis. The total volume of information is expected to grow by tenfold, leaping from 4.4 zettabytes to 44 zettabytes by 2020.
Adding AI to an ECM system can help with the sheer volume of content by using machine learning to automatically classify and analyse documents. This can make it easier for end users to search and find the content they need. AI can also be used to automate processes within the ECM system, such as scanning, OCR, and document processing. This can save time and improve productivity.
One of the biggest challenges faced by ECM systems is keeping all of the information organised and accessible. AI can help with this by enabling new search methods, such as voice-driven searches and visual search. It can also use ML to identify patterns and insights in the content, making it easier for the system to understand and provide contextualised information to users. AI-powered insight models can also help with compliance by automatically identifying sensitive information and suggesting appropriate redactions. This can minimise the risk of a data breach and comply with regulations such as GDPR and the Notifiable Data Breaches scheme.