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  • January 8, 2024
  • By Marydee Ojala Editor in Chief, KMWorld, Conference Program Director, Information Today, Inc.
  • Features

The future of KM is not simply AI

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Perhaps it’s not just the management of knowledge that will be a concern, but also the AI understanding of knowledge. GenAI “knows” only what it has been programmed to know. Its knowledge depends on its training data. Yes, the large language models (LLMs) that ChatGPT, Claude, and others rely upon hold an enormous amount of information. Inside the enterprise, the coupling of these LLMs with internally available knowledge hubs can result in very powerful responses to queries. Pretrained models will become increasingly important going forward as the knowledge on which they are trained becomes tailored to specific industries and environments. Already, models exist for biomedical, financial, and legal scenarios.

Collaborative knowledge sharing

Thanks to the pandemic, companies realized how much information they had squirrelled away in places essentially inaccessible to a remote workforce. This led to an increase in recognition of the value of KM and of collaboration, which has not diminished. What has also not diminished as much as some employers would like is the number of employees working remotely. Although many companies are encouraging or even requiring a return to the office, neither the carrot nor the stick approach to convincing them to leave their home offices has been universally successful. What has emerged is a hybrid workforce, where employees spend only some days, not every day, in the office.

In line with KM basic premises, the need for digital collaboration tools in order to share knowledge was underscored by this trend toward remote and hybrid working. Virtual collaboration spaces, internal social media platforms, and digital whiteboards facilitate real-time sharing and collaborations, transcending any barriers imposed by geography or a hierarchical corporate structure. The value of these approaches to knowledge sharing are likely to continue into the future. It’s not hard to envision two people sitting right next to each other at adjacent desks communicating digitally even though they could easily simply talk to each other. The recognition that they might want to bring someone else into the conversation, someone not at a nearby desk, is one of the lessons learned from remote working.

Future of work

The future of work requires access to information. In fact, the future of KM is integrally tied to the future of work, since KM systems need to adapt to changing patterns in the workforce. As Dion Hinchcliffe, Constellation Research, Inc., noted in his keynote address at the KMWorld 2023 conference, as we move away from yesterday’s “accidental digital employee experience,” the next step is a more designed and holistic approach. This has direct implications for KM as a more coherent approach, with a beginning, middle, and end clearly defined. Hinchliffe sees this new approach as knowledge-centered, data-driven, and big-picture oriented. He also thinks it will be accelerated by technology.

His is not, however, a “let’s change everything all at once” approach. As a key point, he emphasizes the need to fix the basics. Things that may seem extremely simple can actually cause difficulties. At the top of the list of basics is logging onto the system. What’s my username? I forgot my password. Next in line is forgetting a pin number followed by various authentication issues. These are not technical problems, per se, they are human problems.

Hinchcliffe addressed the issue of job dislocation by saying that “AI is unlikely to lead to long-term job loss.” In fact, his belief is that more jobs will be created than will disappear. Yes, temporary dislocations will occur, but an increasing demand for jobs in data science, big data, process automation, digital transformation, business development, and information security will offset the dislocations.

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