Technology is automating much of what information management professionals have traditionally done: classifying, tagging, labeling, maintaining. That's not a threat if we're willing to evolve. The ability to absorb change, identify new opportunities, and play the human in the loop is going to define who thrives and who gets left behind.
I think about skills as a confluence of three things: technical skills, domain knowledge, and soft skills. Information professionals need all three.
AI is non-negotiable. When I say AI, I mean generative AI and agentic AI specifically.
Information professionals deal with workflows and processes where an agent can handle the heavy lifting while we serve as the human in the loop. Generative AI matters because the ability to prompt well is essential, especially in a field with extensive documentation, standards, and regulatory requirements. How do we use AI to work smarter within that environment? That's the question.
Beyond AI, I'd add visualization and reporting. Being comfortable with tools like Power BI or Tableau, whatever your organization uses, matters. The ability to translate a complex information landscape into something simple enough for leadership to notice and act on is an important skill.
The second pillar is the core business of information management: records management, classification, data sensitivity, data labeling. Whether you work in energy, banking, or telecom, you need to understand what information means for your specific organization. What's sensitive? What's confidential? These answers differ by region and by company.
I always encourage my team to develop both technical skills and domain knowledge together.
The third pillar is soft skills, and I consider this one critical.
Information management professionals are different from software engineers who receive a requirement, write code, and deliver. Our output isn't just contextualized information. It's influencing the business to consider that information important enough to act on.
Where are we using more storage than we should? Where are we being inefficient? How can we improve? These conversations happen with senior people. Influencing skills, negotiation skills, and the ability to articulate what you're doing and why it matters are essential.
It's not just AI literacy. It's also data literacy, information literacy, and what I'd call "people literacy."
If you can't translate concepts for other people, connect with their needs, and meet them at their level of understanding, your AI skills will fall flat. Everyone has a different comfort level with AI. How do we find common ground? That's where people literacy comes in.
I often tell my team that information management is highly critical, much needed, and very little understood.
A lot of what we need to do, whether we work with information management professionals or as information management professionals, is build awareness of why this work matters. You can have confidence in your data and control over your governance, but if you don't have context, your information isn't reusable. You can use it once, but you can't build it into a sustainable product or solution.
Organizations thrive on sustainability. Making information sustainable is what information management does.
The views expressed by Subhadra Dutta are her own and do not necessarily reflect the views of her employer.
This blog post is based on an original AIIM OnAir podcast. 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.