The Evolving Information Management Ecosystem

I want to share my thoughts on the relationship between information management and emerging technologies like AI and bots. I'll discuss how I view information management as part of an evolving ecosystem that encompasses various technologies and practices.

Information Management and AI:

When I think about information management in the context of AI and other emerging technologies, I consider all the governance and practices that need to be in place for the technology to be used effectively. It's not just about compliance; it's about ensuring that the technology is implemented in the right place, for the right reasons, and with the necessary checks and balances. Data always needs checks and balances, even in my first job at Bell Telephone Labs, where we were early adopters of Unix and database systems.

The Importance of Data Hygiene:

At Bell Labs, we had what we called "database rules," which is essentially what we now refer to as data hygiene. It's about ensuring the quality and integrity of the information within the database. I believe that many of us fail to recognize the importance of data hygiene, especially in the age of AI. AI depends on good data, good documents, and the authenticity and integrity of the information it consumes. These are not necessarily technologies but practices, and this is where information management comes in - it marries technology with practice.

The Information Management Ecosystem:

I often find myself thinking about the broader information management ecosystem, which encompasses a wide range of technologies and practices. I have a diagram that I use to illustrate this concept, originally developed by Jerry Micalski and later used by New Science Associates (which was acquired by Gartner, where I ended up working). The diagram shows various technologies that we still use today, albeit in different forms. For example, faxing still exists, imaging and capture have evolved, but they're still there.

The Ebb and Flow of Technologies:

I like to think of the information management ecosystem as a garage, where you have all kinds of tools and equipment. You don't take everything out and use it all at once; you select the tools you need for the task at hand. Similarly, in the information management ecosystem, technologies come and go, some get sunsetted, but they don't necessarily disappear completely. The ecosystem is about managing this ebb and flow, embracing new technologies while still carrying forward the necessary practices.

The Role of Capture in the Ecosystem:

As a member of the TWAIN Working Group Advisory Council, I've gained a deeper appreciation for the role of capture in the information management ecosystem. While I'm not a capture expert, I've learned how different groups within the TWAIN community are using the standard to incorporate AI, security, and other technologies into the capture process. Capture, whether mobile or otherwise, is a crucial component of getting information into the system and digitizing it for further use. The process of capturing information doesn’t necessarily go away – it continues to evolve to address both the legacy mechanisms, such as scanning, to incorporating the new technologies and business challenges before us.

Conclusion:

In conclusion, I believe that information management is an evolving ecosystem that encompasses a wide range of technologies and practices. As information management professionals, it's our job to navigate this ecosystem, ensuring that we're using the right tools for the right tasks and maintaining the necessary practices to ensure data quality and integrity. By viewing the ecosystem objectively and embracing both legacy and emerging technologies, we can effectively manage the information that powers our organizations.

This blog post is based on an original AIIM OnAir podcast recorded on March 5, 2024. When recording podcasts, AIIM uses AI-enabled transcription in Zoom. We then use that transcription as part of a prompt with Claude Pro, Anthropic’s AI assistant. AIIM staff (aka humans) then edit the output from Claude for accuracy, completeness, and tone. In this way, we use AI to increase the accessibility of our podcast and extend the value of great content.