The AIIM Blog
Keep your finger on the pulse of Intelligent Information Management with industry news, trends, and best practices.
I get this question a lot: "How do I get started with AI?" My answer always begins with the same principle—don't use AI as a hammer looking for a nail. Instead, understand what processes would benefit by embedding AI, automation, and technology transformation. It all starts with setting a clear strategy and business goal.
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Artificial Intelligence (AI) | Intelligent Information Management (IIM)
We're at a crucible moment in information management, with a lot going on. Here's what information leaders should be focusing on:
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Making an ECM implementation successful requires planning and attention to detail. The best way to create the right solution is to identify organizational goals and priorities. Learn how to manage a successful implementation in our free guide.
AIIM on Air | Artificial Intelligence (AI) | Intelligent Information Management (IIM)
Digital transformation remains a critical journey for organizations, though our research reveals an interesting paradox. While 75% of organizations consider themselves digitally mature, the reality shows many have only scratched the surface of true digital capabilities. In this post, I’ll share some of the biggest obstacles to digital transformation.
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Artificial Intelligence (AI) | Automation | Email Management
The Challenge: Outdated Email Management Practices In the world of information management, we're seeing some wild transformations, especially when it comes to email management. I want to share a recent experience that really highlights how automation and AI are changing the game.
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The rise of sophisticated AI, particularly machine learning and natural language processing, has dramatically increased the valuation of all data—especially unstructured data.
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Artificial Intelligence (AI) | Document Management
Enterprises are adopting GenAI, but most deployments remain disconnected and brittle. Teams build document summarizers, contract analyzers, or chat interfaces as isolated experiments. These efforts don’t scale. They don’t integrate. They can’t be governed. The solution isn’t a better model. It’s a better system structure. This article introduces seven architectural patterns that define how GenAI should operate inside business processes—especially those built around documents, forms, and structured decisions. These patterns are modular, repeatable, and designed for scale.
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