Learn everything you need to know about what intelligent data management it is, why it’s useful, and what to look for in your data management...
Intelligence Abounds: AI and Machine Learning Find Another Home in IIM
Learn everything you need to know about intelligent information management (IIM), why it’s useful, and what to look for in your data management platform.
Intelligent Information Management, or IIM, has gone from a digital record keeper to a data powerhouse. Today, IIM can automate and optimize internal processes beyond the need for human interaction.
Artificial Intelligence Is a Large Discipline With Many Subfields
Artificial intelligence refers to the notion that a computer system can do more than exactly what it is told — it can take action in a “smart,” self-directed way that imitates human behavior. Here are a few of the techniques and capabilities that contribute to AI:
Machine Learning: This term describes the ability of a computer to generate insights from data without being explicitly designed to look for certain information or seek certain conclusions. In a sense, it automates the building of an analytical model because the computer will use neural networks, statistics and other methods to uncover its own insights and teach itself what to do.
Neural Networks: AI inspired by the inner workings of the human brain is a neural network. The computer will consist of interconnected elements that process data by responding to inputs from manual entry or the environment, much like the neurons in the brain. The more passes it gets at the data, the more connections it will make and the more meaning it will derive, the same way repetition teaches the brain.
Deep Learning: Deep learning utilizes today’s advanced computing power and AI training methods to learn incredibly complex patterns in enormous quantities of data. This typically involves immense neural networks with multiple layers. AI that focuses on image and speech recognition relies on deep learning to analyze large datasets of example inputs.
Computer Vision: When a computer system can recognize what is in a picture or a video, that’s computer vision. It depends on deep learning and advanced pattern recognition in a large dataset of visual media. An AI that can process, identify, and analyze images makes it possible to interpret visual data in real time — for example, so that the computer can capture images or videos and understand its surroundings while in motion, as with driverless cars.
Natural Language Processing: The popular ChatGPT large-scale language model is an example of an AI with advanced natural language processing capabilities. This field encompasses AI that can understand and generate natural human language, or even interact in natural language, so that humans can communicate directly with the computer with casual, colloquial speech to give it direction.
Why AI and Machine Learning Work So Well with Data Management
Every organization — from government to manufacturing, retail or even education — has begun to produce mass amounts of freeform data. This data is often so rich that it can’t be structured in an easily searchable way for the end user. New IIM smart technologies aim to tackle that problem. Even the oldest of organization systems can adopt these capabilities. Peggy Winton, President & CEO of AIIM, talks about this in more detail in the new eBook.
“This [need to structure data] is especially the case where organizations are receiving documents through a variety of delivery channels. Organizations are realizing that processes simply cannot be automated until the unstructured information that underlies them is in a machine-comprehensible form.”
AI excels in handling these vast amounts of unstructured data with pattern recognition. The machine’s analysis allows it to find new meanings behind each form and data point. When you apply machine learning to AI, it’s possible to create entirely new sets of data on which to base decisions.
AI Makes Decisions Driven by Data and User Interaction
Existing users should still be able to utilize all systems as proficiently as before. When you start to implement AI and machine learning into your IIM strategy, focus on proper integration of the same or similar interfaces to what they’ve already grown accustomed to. The backend, however, can be fully upgraded and operate with more processing power than ever before.
Another key to successfully implementing IIM technologies is that the AI and machine learning systems shouldn’t need any additional maintenance or actions from the end user. The learning technology simply picks up on the patterns and insights needed to operate at maximum capacity.
Leveraging AI Requires Technological Insight
Our Intelligent Data Management Cycle technology is powered by easy.forward. It’s simple to plug in for users and properly integrate your existing data. Expert help is also available as needed. These AI systems operate fully on their own, but getting the most out of them will require the assistance of a team dedicated to providing your organization with the most efficient intelligent information management.
Most ready-to-use, AI-based solutions struggle to provide the same level of accuracy and efficiency as Scan-Optics because there really isn’t a universal solution to IIM. Every organization has unique needs. We take the time to get to know your organization’s nuances to create a strategy that checks every box. Don’t let your team struggle to keep up with forms and processes. Get started on a solution today.