In the good old days of paper mediums, dewy decimal systems, and filing cabinets, much of the management and organization of information assets like books and records were heavily dependent on human labor-intensive tasks to store and organize. It was a matter of tucking things away based on multi-tiered system of classification and sub-classification. While digitalization and Information technology has increasingly reduced manual labor and storage footprint of information, the amount of data being created in a rich media society is eclipsing the ability to bring it under control.
It is estimated that 80% of the world’s data is unstructured, private, and classified as cold data – such as emails, documents, records, contracts, images, audio, and video files. Although much of these information assets are infrequently accessed, they are continually retained for its purpose – often for years longer than the expected lifetimes of the storage medium. In 2027, the amount of storage forecasted to be in demand and shipped by manufacturers is about 6 Zettabytes. At an organizational level, the shear amount of storage needs will overwhelmingly create new problems and risks in security, handling privacy, and data loss. Data loss can be caused by physical or mechanical failures of the storage medium. Other ways to lose data is simply – not to organize it well enough for the data to be used, and complacency with data backup and migration solutions.
The future of intelligent information management will continually evolve as a source of competitive advantage for businesses and individuals. New service capabilities will automate and accelerate the way we learn, understand, adapt, and react to new situations for value creation and reduce exposures to enterprise risks:
- Where and what information assets do I have that is useful to me now or in the future?
- What does my information assets tell me that I may not know about?
- When do I need to migrate or dispose of the data as the storage medium expires?
- How will I retrieve, protect, and use information assets when I or others need it the most?
- How does my IT and information lifecycle management practices contribute to carbon footprints?
What is intelligent information management?
The definition of Intelligent Information Management (IIM) is an array of techniques, programmable processes and underlying technology capabilities that enable enterprises or individuals to progressively organize and automate their growing volumes of unstructured data. This includes but not exclusively on the practices of preparing, archiving, analyzing, distributing, and securing the storage of documents, records, media, data base files, physical and digital assets – with users at the center of the experience.
IIM focuses on how content, its descriptive data, and related policies are applied and governed within organizations and information systems to facilitate the effective and efficient control and use of information assets – both physical and digital. In some cases, it involves the integration of systems and processes to support operational business needs – such as document creation software, content, knowledge, customer management software, and financial systems. In other cases, IIM embody tools and automate the services that enhance the value of information itself – such as the enrichment or extraction of meta descriptions for contextualization, or advanced algorithms and machine learning techniques to analyze and process large amounts of data and present it in a useful and meaningful way to users.
The use of information assets differs across industries and applications, but the objectives remain the same: information assets must be easy to find, relevant for the user, protected, and stored from unwanted threats. IIM helps organizations to manage and utilize their information assets, improve (internal and external) efficiency and productivity, and make more sense out of unstructured data more effectively. Data visualization such as graphs and charts can be a useful tool for IIM, as it can help users see patterns and relationships that may not be immediately apparent.
What’s next?
Intelligent information management is a rapidly evolving set of integrated services, and the future of this technology will be shaped by the advances in the application areas of artificial intelligence, machine learning, and data analytics. Key trends, developments, and predictions include:
- Intelligent information management will assimilate search services: Search can be considered a type of intelligent information management, as it involves indexing and categorization, as well as to process and evaluate queries. Search is just one component of a broader system that will evolve IIM as natural language processing improves to interpret complex and nuanced search queries. Natural language processing interfaces and services will be applied across functional areas of the enterprise.
- Increased application of artificial intelligence and machine learning services: These technologies are likely to play a larger role in intelligent information management systems in the future, as they allow for more automated parameters for data analysis and decision-making – especially in unstructured data files. IIM will become a contextualization engine for many applications and systems inside and outside the business.
- Increased focus on regulation and compliance of laws, ethics, and conduct: As companies and individuals transact in many ways, there will be an increase in measures to prevent or mitigate risk of being sued, financial penalties, and legal consequences. Intelligent information management and immutable storage will become an insurance policy to support record keeping, evidence, legal discovery, and privacy. The collapse of FTX crypto exchange will undoubtedly send regulatory enforcement shockwaves across the financial space as it unfolds in 2023.
- Increased focus on user-centric information governance: As complex information systems get deployed, the need for organizations to establish a consistent and logical framework for employees to handle data through information governance policies and procedures. The frameworks and systems will need to continually adapt to employee behaviors, roles, functions, and new ways of work in conjunction with enterprise security.
- Greater integration of data from multiple sources and locations: As more structured and unstructured data becomes available from a wider range of sources (public or private clouds, data sovereignty mandates), intelligent information management systems will need to be able to integrate and understand data from multiple sources and localities to provide a comprehensive view of online and offline information assets.
- Increased focus on authenticity of information: As the importance of data and the value of digital assets continues to grow, it is important to be able to distinguish authentic information from fake, doctored or misleading information assets (physical and digital). Intelligent information management will help to reveal biases and agendas, AI-generated content, trustworthiness, its owners, and origins.
- Continued development of data visualization tools and interfaces: Data visualization tools and interfaces will continue to evolve and improve, making it easier for people to understand and analyze large amounts of data. This includes the application of spatial visualization and augmented reality in 3D spaces.
Summary
Overall, the future of intelligent information management will evolve to progressively help humans to automate the understanding and use of information assets, as organizations continue to solve the massive amounts of unstructured documents being created, captured, transferred, and stored. It will embody the holistic capabilities that become an enterprises’ timeless memory, and active librarian. It will generate new business use cases to justify storage infrastructure expenditures that are aligned with governance policies, information lifecycle, and enterprise risk.