Companies that systematically record, organise and share their knowledge secure a competitive advantage. Across departments and locations, employees have access to sound knowledge on the company intranet, for example, which can be increased and deepened and remain within the organisation even after staff departures. To turn unstructured information into valuable knowledge, data from various sources must be merged, linked and embedded in an existing, meaningful context. Machine learning can support this process and track down and analyse information and recognise patterns and correlations. Generative AI goes even further and presents existing knowledge in a meaningful context. This not only creates a solid basis for day-to-day collaboration in companies, but also for strategic decisions - and ultimately for business success.

Generating knowledge with AI

If information is available in machine-readable form, AI can generate relevant knowledge from it. Machine learning can be used to summarise texts and evaluate and combine information from different channels. If the right frame of reference is then established - through semantic relationships between data sources, correlations and topic complexes - we are talking about knowledge generation. 

Knowledge management is about disseminating a lot of substantial knowledge in the best possible way (e.g. in intranets). Tagging documents is advisable so that this knowledge can be found by users. With the help of AI systems, it is easy to generate metadata and thus facilitate the search. Virtual assistants, such as chatbots, also provide good services when it comes to answering frequently asked questions. In doing so, they utilise internal company knowledge. By interacting with users, they expand this knowledge and bring it into the organisation.

AI could become a game changer in the field of predictive modelling: Machine learning can be used to search through enormous amounts of data and gain meaningful insights for predictions. Forecasts created on this basis in the form of predictive analytics help to prepare business decisions. Generative AI takes these predictions of the future based on the past to a higher level because it processes and analyses data much more efficiently than before. Within seconds, it develops fictitious scenarios and thus helps with forecasts and decision-making. AI technology is thus further developing the entire field of predictive analytics. At this point at the latest, it becomes clear how relevant AI is not only for the field of knowledge management, but far beyond. 

Opportunities and challenges

In summary, AI fulfils six main tasks in knowledge management:

• Preparing the content of knowledge using existing data sources, such as product texts, training documents and tickets
• Enhance knowledge by finding and correcting errors, supplementing existing information and archiving outdated information
• Accessing existing knowledge quickly and intuitively, e.g. via chatbots
• Making new knowledge accessible by systematically combining, summarising and preparing content for different areas of the company
• Creating attractive content, for example through personalised content, adapted to regions/languages and thus tailored to users
• Solve problems by analysing patterns in data, such as recurring problems and their solutions

Artificial intelligence can make a difference in both operational and strategic knowledge management. In operational knowledge management, it optimises the use of knowledge in business operations. Strategic knowledge management focuses on the future, promotes action-relevant knowledge and creates the best learning conditions in companies. It also prevents the loss of valuable expertise and experience during generational change. 

In general, the following conditions should be met when using AI solutions:

• Security and data protection must be guaranteed.
• The quality and accuracy of the output must always be critically scrutinised and checked (traceability).
• Consistent training (e.g. by using relevant data sets) must rule out imprecise results due to data distortion.

Full control over company data

In the field of AI-based development and integration, we cooperate with various companies in order to offer our clients optimal solutions for their requirements. In the knowledge management segment, we use an open source solution from Comma Soft AG that utilises large language models. Based on Llama 3, it delivers comprehensible results with references. We enrich the data basis via Retrieval Augmented Generation (RAG) so that LLM can access internal company data.  The organisation itself decides where to host and operate the system in accordance with its data protection and compliance requirements. Comma Soft offers an on-premise model for hosting the application without passing on data to third parties, which also fulfils high data protection requirements. This means that data does not get out, but remains within the company.

AI-supported knowledge management for your business success

Knowledge is a competitive factor for every company - regardless of industry and size. With the help of artificial intelligence, it can be processed, accessed and anchored in the organisation even more efficiently than before. We can help you with this,

Gain an overview of your processes and their potential for AI optimisation.

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