We hope this list of Readers' Choice Awards winners will be a resource to help you choose wisely when looking for new solutions. As the field continues to evolve, recognizing excellence and innovation remains a constant, even as how knowledge sharing is accomplished morphs in tune with technology changes.
Marydee Ojala //
04 Nov 2024
There is undeniable potential in generative AI and large language models, but these tools alone come with significant gaps and challenges. AI often needs additional technologies to create guardrails around data security and response accuracy.
Matthew Payne //
04 Nov 2024
The eGain Knowledge Hub is a rich, "whole-product" AI knowledge solution that has created transformational value at speed and scale for Global 1000 companies and government agencies alike.
Anand Subramaniam //
04 Nov 2024
AllegroGraph is designed to seamlessly integrate with LLMs, providing the most secure and scalable AI solution for enterprises. AllegroGraph offers a comprehensive solution platform including Large Language Models (LLMs), Vector generation and storage, Graph Neural Networks, Graph Virtualization, GraphQL, Apache Spark graph analytics, and Kafka streaming graph pipelines.
Jans Aasman //
04 Nov 2024
AI continues to disrupt the knowledge management space and experts in the field predict that it's a trend that still hasn't reached its full potential, yet. In 2025 there's more room for improvement.
Stephanie Simone //
06 Dec 2024
One thing is clear: The widespread adoption of GenAI will not lead to fewer knowledge jobs, but rather, it will pave the way for their growth and evolution.
Egor Kraev //
04 Nov 2024
What organizations that depend on dynamic documents really need are solutions that work seamlessly across all platforms. This way, organizations can eliminate compatibility issues and reduce most—if not all—of the costs that are associated with restricted formats.
Huy Tran //
04 Nov 2024
The need for comprehensive data management will always be important, and there are many other benefits of digital transformation, but CIOs don't need to delay GenAI projects until the completion of a giant data centralization effort. By adopting a more flexible approach that incorporates GenAI and next-generation BI tools, businesses can navigate the complexities of modern data ecosystems while driving innovation and maintaining a competitive edge in an AI-driven world.
Saurabh Abhyankar //
09 Sep 2024
We are in the earliest stages of Agentic AI, and, much like the early days of RPA and GenAI, there's a lot of excitement but also a lot of uncertainty. While the potential benefits are enormous— streamlined operations, lower costs, fewer human errors—there are equally important concerns about job displacement, bias in AI decision making, and a lack of transparency in how these systems operate.
Alan Pelz-Sharpe //
04 Nov 2024
The citizen developer movement was heralded as a revolution. Like most revolutions, things have sometimes gone differently than planned. The logic is sound, empowering those who know the business best to build the tools and systems needed to do their job. Ah, if only things were that simple …
Alan Pelz-Sharpe //
09 Sep 2024
While process mining started years ago as a mainly data-driven exercise, its stated goal is to be knowledge-driven. Given KM's multidisciplinary scope, we can play a major role in achieving that goal. Any process, no matter how simple, has the potential to reach across an entire business ecosystem, including all stakeholders. This seems like a perfect match for collaborative workflow, AI/ML, knowledge graphs, human sensemaking, and many of the other arrows in our KM quiver.
Art Murray, D.Sc. //
09 Sep 2024
The third place I alluded to goes far beyond mechanistic KM or curated knowledge and takes us into the actual world of tacit knowledge. Here, knowledge comes from and often remains as personal experience, impressions, and intuition; it's undocumented and often hidden and elusive.
Alan Pelz-Sharpe //
02 May 2024