A well-known definition of Artificial intelligence is “the simulation of human intelligence by software”. Some companies are working on Artificial General Intelligence, trying to create software that should be able to simulate all human intelligence. Our approach at Y.digital is different. Recently, I was in contact with a Principal Analyst from Forrester, Julie Mohr, about our vision. Her reaction was surprisingly affirmative.

Intelligence requires information and knowledge

At Y.digital we create innovative AI solutions on a daily basis, however, we never start with this when a new projects kick off. First, we look at the information that the enterprise processes as well as the explicit, tacit and implicit knowledge of human knowledge workers. We model both information and knowledge in knowledge graphs, one of the classical forms of AI[1]. This ‘knowledge foundation layer’ then serves as a base for applying various traditional and innovative AI technologies, effectively turning the information and knowledge into intelligence. The resulting intelligence can be infused in all business processes, channels and to support humans.

When starting our company in 2020, one of our slogans was Scaling your Knowledge, emphasizing the fact that we capture enterprise knowledge and use the power of computers and software to apply the knowledge at scale. Our approach did not change when Generative AI (genAI) arrived late 2022. Many organisations immediately put Large Language Models in the centre of their AI platform, but we did not. Instead, we added genAI on top of our knowledge foundation layer, thus combining the best of both worlds: a structured enterprise knowledge base, governed and managed by the enterprise’s knowledge experts, and the innovative power of genAI, unleashing the knowledge and creating intelligence.

Knowledge management approaches

One might say: you are innovating the classical approaches of knowledge management. And yes, I think we are. Knowledge management aims to capture the implicit, tacit and explicit knowledge of humans in an enterprise. We all know examples of enterprises that depend heavily on just a few human experts, mostly reaching the age of retirement. So far, the most common way to capture their knowledge was in documents, training material or content management systems. Good enough to train experts, but not suitable for automation purposes. However, our approach does make this possible, thus unleashing the power of traditional knowledge management into the age of intelligence.

Forrester’s view

Recently I contacted Julie Mohr, a well-known Principal Analyst at Forrester’s. She has written interesting research and blogs on the topic of knowledge management and AI. [2] For example, in her blog Unleash The Potential Of Knowledge Management And Generative AI [3] she states ”By embracing the synergy between knowledge management and genAI, organizations can position themselves as champions in the knowledge economy. This transformation requires a shift in mindset, from simply capturing knowledge to actively cocreating it, as well as shifting from finding information to discovering new possibilities. Organizations can unlock unprecedented levels of innovation,collaboration, and business success by empowering their knowledge community, fostering a culture of trust, and leveraging the capabilities of genAI.”

However true this may be, she only mentions genAI, so I asked her:  

1. Hasn’t AI so much more to offer than just genAI?  

2. Why is there still little interest in Knowledge Graphs?

3. Will Knowledge Management System vendors move on, from only offering knowledge to human workers, towards also applying knowledge in automated business processes?

Her answers were spot-on and affirmative. She judges traditional AI-techniques such as machine learning as being too limited and sees genAI vastly improving conversational and generative areas. However, she states that it’s the combination we should be looking for. She also promotes the use of knowledge graphs with the vendors she works with on her KMS Wave project [4]. And she sees some vendors moving towards more collaborative approaches as others are still ignoring it.

Stay in control of AI

We live in fascinating times,in which AI is quickly impacting our enterprises and society. This raises important questions, one of them being: how do you remain in control of the ways your enterprise’s knowledge and intelligence are captured and applied by AI? Our approach, which leverages traditional knowledge management, can serve as a starting point. If you want to know more or share your opinion on this, feel free to contact me at art@y.digital.

[1] Methodically speaking, e.g. the DIKW-approach: intelligence of wisdom is based on data, information and knowledge.

[2] See https://www.forrester.com/analyst-bio/julie-mohr/BIO17705

[3] Seehttps://www.forrester.com/blogs/unleash-the-potential-of-knowledge-management-and-generative-ai/

[4] See https://www.forrester.com/report/the-forrester-wave-tm-knowledge-management-solutions-q4-2024/RES181704

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