The intersection of artificial intelligence and information management presents both exciting opportunities and unique challenges for organizations across all industries. During our recent pre-conference webinar, I had the pleasure of speaking with two industry experts about how AI is transforming the information management landscape and what attendees can expect at the upcoming AI+IM Global Summit in Atlanta (March 31-April 2).
Joined by Alan Pelz-Sharpe, founder and principal analyst of Deep Analysis, and Max Gerrard, director of Solution Engineering at SER Group, we explored foundational AI concepts, discussed practical use cases, and outlined key considerations for organizations looking to leverage AI in their information management strategy.
To begin our discussion, Pelz-Sharpe provided a straightforward definition of AI: "In the simplest of terms, AI is software that learns." Gerrard expanded on this, noting that AI excels at "being able to make decisions on data sets that humans can't possibly compute themselves in their own mind."
Pelz-Sharpe further explained that while generative AI is able to pull data from various sources and create convincing answers or outputs, agentic AI goes further by completely digitizing a role and making decisions on its own behalf.
AI and information management are deeply interrelated. Information management is key to AI readiness, preparing data for training models and task as well as managing AI output. AI also can enhance and dramatically improve information management processes.
Max highlighted how AI is helping organizations address data volume challenges. He explained that SER Group has a lot of customers who want to scan physical documents, but would have to manually enter metadata for documents. "That's an extremely laborious task that if you add it up can literally take years," Gerrard explained.
Max shared that SER Group calculated that it would take one of their clients 6,000 years to manually enter all the data from their physical documents. AI-driven document management helped the client auto-classify physical documents in months.
Both speakers emphasized the importance of being strategic about where and how to apply AI. Alan noted that rather than focusing on historical data or processes, organizations should consider using AI to address new problems. "Find a process that needs fixing or a new process," he said. "It's an opportunity to rethink, reframe, reimagine the way you do business and potentially start afresh."
Gerrard emphasized the importance of data quality when implementing AI solutions. He warned that building AI systems on poor-quality data creates a dangerous situation where organizations might blindly trust algorithmic outputs rather than examining the underlying information. This misplaced trust, he explained, can ultimately lead to seriously flawed decision-making across the business.
The discussion highlighted several compelling use cases for AI in information management, including:
One of the most compelling use cases discussed was leveraging AI to address the overwhelming volume of stored data that organizations have accumulated over decades.
According to Pelz-Sharpe, organizations have fallen into a pattern of excessive data hoarding. "Nobody wants to take responsibility for deletion," he explained. With AI, information managers can now gain unprecedented insights into their data stores and confidently identify low-value content. He suggested starting with obvious candidates - documents that were opened once a decade ago and never accessed again - when approaching legal departments for disposition approval.
Gerrard confirmed this opportunity, noting that when SER Group conducts data assessment exercises during platform onboarding, clients are consistently surprised to discover that 10-20% of their stored data can be safely eliminated. Beyond compliance benefits, this translates to significant savings in cloud storage fees.
Gerrard emphasized the importance of taking an incremental, experimental approach to AI adoption rather than pursuing large-scale implementations from the outset. He recommended starting with tightly defined use cases, giving teams several weeks to evaluate real-world performance, and being willing to pivot if the expected value doesn't materialize.
"The promise of AI algorithms often sounds impressive in theory," Gerrard noted, "but practical implementation reveals whether they truly deliver meaningful benefits for your specific needs."
For successful implementations, he stressed the importance of carefully selecting appropriate datasets and involving data security stakeholders early in the process.
Gerrard also shared an interesting insight about messaging: when discussing potential projects with clients, he often avoids explicitly using the term "AI" and instead focuses on concrete business outcomes. This approach helps bypass the psychological barriers some organizations have developed around AI initiatives, where they automatically classify such projects as future endeavors rather than addressing immediate operational needs.
Both speakers strongly emphasized that information management professionals are not becoming obsolete in the age of AI - quite the opposite. They possess unique expertise that makes them invaluable for successful AI implementation.
Pelz-Sharpe highlighted how information managers bring foundational knowledge of taxonomy development, metadata structures, and library science principles to AI initiatives. He argued that professionals who combine these traditional skills with newer capabilities like AI prompt engineering become extraordinarily valuable to their organizations. Without their expertise guiding AI systems, organizations risk making dangerous data-handling mistakes.
When discussing retrieval-augmented generation (RAG) and AI agents specifically, Gerrard was unequivocal about information managers' importance. Their comprehensive understanding of organizational content, document types, and information flows makes them essential stakeholders who deserve "a seat at the table" alongside IT security professionals during AI project planning and implementation.
The AI+IM Global Summit will feature numerous sessions exploring these topics in greater depth. Gerrard mentioned two sessions he's particularly excited about:
Pelz-Sharpe emphasized the value of networking at the event, noting how unusual it is to have so many skilled information managers in one place. He encouraged event participants to make the most of the opportunity to network with this unique audience. "Share your challenges, share your experiences," he said. "You might come out of it with a new job, but you're certainly going to come out of it with new friends."
The AI+IM Global Summit (March 31-April 2 in Atlanta) offers a unique opportunity to explore the intersection of AI and information management through workshops, interactive sessions, thought-provoking keynotes, and networking. The event will feature four learning pathways focused on AI, automation, intelligent information management, and leadership and change management.
Don't miss this chance to learn from industry leaders, connect with peers, and gain practical insights to improve your organization's information management strategy in the AI era. Register today!