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Exploring the top trends in KM for 2024

The innovations of 2023 have started the new year off with exciting prospects, as well as persistent challenges. Going real time, breaking down data silos, and legacy tools and infrastructures continue to be significant obstacles that any enterprise wanting to compete in today’s economy will have to reckon with.

Experts joined KMWorld’s webinar, The Top Trends in KM for 2024, to discuss the ongoing trends, success enablers, and challenges—from knowledge graphs to LLMs, security, compliance, and more—that should be top of mind for knowledge workers in every corner of industry.

John Chmaj, senior director, KM strategy at Verint, appropriately tasked ChatGPT with what the top trends in KM are, yielding the following results:

  • Natural language processing (NLP) and text mining
  • Machine learning (ML) for content recommendation
  • Information retrieval and search algorithms
  • Knowledge graphs
  • Cognitive computing
  • Robotic process automation (RPA)
  • Chatbots and virtual assistants

With these trends in mind, the main things you can do in KM revolve around accessibility, personalization, and simplification. Now, businesses can:

  • Make multiple content sources and repositories commonly accessible through AI
  • Predict and personalize suggested actions and presentation of information
  • Simplify and refine accurate access to relevant information

The exciting new avenues that can be taken in the realm of KM, especially as it relates to AI, are promising—and overwhelming. These trends change every day, if not every hour, and KMers will have to be ready to adapt to them all.

“The future is now…we are sort of living it day to day. What’s happening in the business world around intelligence and artificial intelligence will be different by next week,” said Chmaj.

According to David Seuss, CEO at Northern Light, “I think it’s pretty clear [that] the world changed on November 30, 2022, when OpenAI released ChatGPT to the public.”

This world, as Chmaj noted, has changed remarkably for knowledge workers and that pressure to adopt generative AI (GenAI) is coming from above. According to Accenture’s 2023 Technology Vision report, 97% of global executives agree that foundation models will enable connections across data types, revolutionizing where and how AI is used.

This appeal is born from the fact that use cases for GenAI are expansive, from data analysis to content creation and personal assistants. Northern Light places its emphasis on leveraging the technology for research, providing knowledge management systems for competitive intelligence and market research.

“[Research] is one of the most important applications of generative AI,” said Seuss.

Citing a recent study from Harvard Business school, generative and conversational AI had a dramatic impact on business research and analysis work. Comparing two groups divided by their use of ChatGPT-4 or not, the group using AI finished tasks 40% and with 25% higher quality.

With the promises of success that GenAI poses for knowledge management, Matthew Bennett, senior executive of business development and strategic info solutions at Access, pointed out where that data is held—and how—is equally as important.

The proliferation of work-from-home environments has certainly altered the course of technology and KM for 2024, where access to data, as well as its security and control, is crucial. Integrated information management is additionally important, where the following are essential:

  • Streamlined data access
  • Compliance integration
  • Unified governance framework
  • Automated classification
  • Retention automation
  • Enhanced information security

This information management is often associated with the digitization of records, where indexing and AI can not only incur greater information accessibility but also greater value on that data. While this digitization promotes some success, there are still challenges to be faced, according to Bennett, including the costs, timelines, and organizational alignment of a full-scale digitization project.

Ultimately, Bennet offered these key takeaways:

  • Different digital maturities are normal in an evolving digital landscape.
  • Create a roadmap for that adoption of new technologies.
  • Give employees access to the physical and digital records when, where, and how they need them.
  • Stay on top of new and updated laws and regulations.
  • Aim for a comprehensive, agile information management program.

Atanas Kiryakov, founder and CEO of Ontotext, emphasized that there is a specific opportunity for KM in 2024: Knowledge graphs and LLMs. With the advent of LLMs, knowledge graphs have become easier to build at a lower cost, ultimately ensuring their ongoing existence as they act as the foundation of an LLM.

Furthermore, the exponential growth of data, both in volume and complexity, complements graph technology’s ability to connect information with semantic metadata.

“The inherent complexity of big enterprises is such that the knowledge graph is the simplest model that enables them to ‘connect the dots’ across hundreds of operational IT systems and turn the diversity of their business into a competitive advantage,” explained Kiryakov.

Knowledge graph management platforms will need certain requirements to be met, however, including a database engine with predictable performance across multiple workloads and a text analysis ecosystem that allows for experimentation with multiple text analysis models, evaluation of accuracy, and entity linking between graphs and text.

For an in-depth review of 2024 KM trends, you can view an archived version of the webinar here.

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