AI KNOWLEDGE
Build enterprise knowledge
In this sphere, you will find practices that promote the transformation of tacit knowledge into explicit knowledge. This transformation is strategic for being able to train your AI systems with maximum value. It essentially involves documenting the know-how of your operators. This work represents a significant investment, but the return on investment, thanks to AI, is immediate. The more you formalize and accumulate knowledge over time, the more you can create AI assistants that are available on demand, as well as integrate them into your operational processes to enhance the overall performance of the company.
Knowledge management to power AI
In the company, only about 20% to 40% of knowledge is formalized in the form of databases and documents. The remaining 60% to 80% of knowledge remains trapped in the minds of employees. However, all this knowledge is necessary to train AI. Therefore, programs must be initiated to transform tacit knowledge into explicit knowledge and to improve the quality of these information reserves. They are strategic for the success of AI and for achieving the expected productivity gains.
Most of the time, the company lacks precise self-awareness. Documentation is scattered across different departments, databases contain only a small portion of the manipulated information, team turnover leads to losses in certain practices, and overall quality is unsatisfactory. However, in the realm of AI, all this knowledge is essential for training. Therefore, it is crucial to not only improve the quality of existing data management but also to extend this management to encompass all tacit knowledge.
Personal Knowledge: To level up AI, enhancing knowledge management systems to capture and organize explicit knowledge is crucial. This ensures that information is accessible and up-to-date. Simultaneously, tapping into the rich reservoir of individual tacit know-how can unlock innovative solutions and creative strategies. The motivation to convert personal tacit knowledge into explicit form is twofold: firstly, to assert human expertise in an era increasingly dominated by artificial intelligence, and secondly, to facilitate the systematic accumulation of knowledge. By articulating and sharing personal insights, individuals not only contribute to the collective intelligence but also provide valuable data and knowledge that can be used to train AI systems. This symbiotic relationship between personal knowledge and AI can lead to more sophisticated and intuitive technology that complements human capabilities, fostering a collaborative environment where both can thrive.
Collective Knowledge: Collective knowledge within an organization is a powerful asset, formed by aggregating the explicit and tacit knowledge of individuals within departments and across interdepartmental boundaries. The amalgamation of this knowledge is essential for enterprises, as it fosters innovation, efficiency, and competitive advantage. It is estimated that a significant percentage of an organization’s knowledge is tacit, residing in the minds of its employees, and remains unexploited. Accumulating this vast reservoir of implicit understanding is vital for organizational growth and adaptability. Artificial intelligence stands as both the conduit and the repository for this knowledge, capable of capturing, analyzing, and disseminating insights throughout the organization. AI systems help transform tacit knowledge into explicit knowledge, making it accessible and actionable, thereby solidifying the foundation of collective intelligence within an enterprise.
Enterprise Architecture: At the organizational level, cultivating a mindset that values and facilitates knowledge accumulation is paramount. Enterprise Architecture (EA) serves as the technical scaffold, enabling the scaling of knowledge from individual contributors to the organizational tapestry. Together, these elements not only empower AI integration within enterprises but also amplify its application and adoption, ensuring that AI solutions are both innovative and in sync with human expertise.
Soft skills are the bedrock of professional development, with critical thinking at the forefront. To bolster critical thinking, one must focus on enhancing writing skills for clear communication, honing analytical abilities to decipher complex issues, fostering innovation to navigate and create change, and promoting a culture of sharing to disseminate knowledge. In an AI-enabled enterprise, where human and AI co-work, critical thinking and writing skills are even more essential as they help achieve the best combination of human and machine intelligence. AI needs clear guidance and instruction from human co-workers to produce its best results, which are subsequently validated by humans (human-AI feedback loop).
In conclusion, mastering the art of writing, analyzing, sharing, and innovating is critical to harness the full potential of AI. Effective knowledge management, particularly the transformation of tacit knowledge into explicit knowledge, is essential for training AI and advancing organizational intelligence. This is the WASI effect. You can read more about the WASI effect HERE.
In this figure, you have an example of transforming tacit knowledge into explicit knowledge to enhance AI training. Here, the user is asked to formalize their knowledge on the critical use of a standard process described by the company, as well as to explain the use cases of this process in order to adapt it to real-world situations. All this written knowledge is then given to the AI to obtain a critical analysis of the standard process, thereby identifying areas for improvement. This principle of formalizing tacit knowledge can be repeated regularly (weekly, monthly, biannually, annually) to establish a continuous process improvement loop. Without AI, formalizing all this knowledge would be pointless as manual exploitation would be too costly. AI removes the barriers to knowledge accumulation, thus also promoting better practice sharing among participants, including new employees who need to be trained.
Fragmented knowledge
In a world where knowledge is consumed massively in a fragmented way, the lack of formalization of knowledge in writing is a hindrance to success. META framework is a good way to organize in this pool of knowledge in order to better exploit it. It is also important to keep control of intelligence artificial by writing relevant prompts.
Attitude at work
The individual or organization that uses META framework reduces the use of the trial-and-error approach in favor of a greater formalization of knowledge in order to accelerate analysis.
This approach adapts better to a world that is changing under the effect of hyper-knowledge brought about by digitalization, big data and artificial intelligence.
To achieve this, the individual or the organization must improve on these indispensable qualities: the culture of formalization in writing to capitalize on fundamental knowledge, the taste for rapid and relevant analysis, and the desire to share and innovate: this is the WASI process (Write, Analyze, Share and Innovate).
Finally, the META framework is akin to scientific thinking to increase your chances of succeeding in a complex world, by adopting better knowledge management over time.
