The Importance of Tacit Knowledge in AI Workflows

In today’s digital era, Generative AI (GenAI) plays a pivotal role in driving innovation and efficiency in the workplace. However, the success of GenAI integration often hinges on an overlooked yet crucial element: tacit knowledge. This post explores the importance of tacit knowledge in AI workflows and offers practical strategies for integrating it effectively.

Understanding Tacit Knowledge

Tacit knowledge encompasses the insights, experiences, and intuitions that employees acquire over time but are not formally documented. This type of knowledge is subjective and deeply personal, influenced by individual experiences and perspectives. Unlike explicit knowledge, which can be easily recorded and shared, tacit knowledge is context-specific, making it challenging to capture and utilize in AI workflows. It is often acquired through long-term involvement in a job role, continuous interactions with colleagues, and direct experiences with customers.

Examples of tacit knowledge include the nuanced understanding a salesperson has about client preferences, the intuitive decision-making skills of a seasoned project manager, and the creative processes an experienced designer uses to develop innovative solutions. Tacit knowledge manifests in various ways, such as behaviors, actions, habits, routines, instincts, responses, and intuitions.

The Hybrid Work Challenge

With the rise of hybrid work models post-COVID, organizations are rethinking how to capture and share knowledge across their workforce. While remote work disrupts the natural, spontaneous sharing of knowledge that typically occurs in an office setting, the need to effectively capture and utilize tacit knowledge has always been crucial. Even before the pandemic, having robust systems to retain and share this knowledge was essential for maintaining organizational continuity and fostering innovation.

The shift to hybrid work has highlighted and intensified this long-standing challenge, making it even more apparent that companies need to proactively manage tacit knowledge. The dispersion of teams across various locations can lead to information silos, where critical insights and experiences are not shared effectively. This situation underscores the importance of developing strategies and tools to ensure that valuable tacit knowledge is captured, preserved, and made accessible to all employees, regardless of their work environment.

Barriers to Sharing Tacit Knowledge

Even with a wealth of tacit knowledge in an organization, several barriers can prevent its effective sharing:

1. Difficulty of Demonstration: Tacit knowledge is often so ingrained that articulating it can be challenging. For instance, a seasoned salesperson might have a deep understanding of client preferences and the subtleties of closing a deal, which are difficult to convey through standard training materials. While they can describe their approach, the intuition and timing they employ can only be fully understood through direct experience.
2. Situational Application: Tacit knowledge is often recognized only in specific contexts, making proactive sharing difficult. For example, a project manager's ability to navigate complex stakeholder relationships is best learned through direct involvement in those interactions. 
3. Lack of Context: Sharing tacit knowledge requires context-specific examples. Without shared experiences, explaining insights can be difficult, often resulting in misunderstandings. For instance, a marketing professional might struggle to convey the nuances of a successful campaign strategy without a shared understanding of the campaign's specific challenges and audience. 
4. Varied Individual Talent: Different individuals excel in various domains, making the transfer of tacit knowledge across these domains challenging. For example, a financial analyst with a natural aptitude for numbers might find it difficult to convey complex financial concepts to a colleague who excels in creative roles, such as graphic design. This disparity in skill sets can create barriers to effective knowledge transfer, necessitating tailored communication strategies to bridge these gaps.
5. Lack of Time: Sharing tacit knowledge typically requires interaction, observation, and mentoring, which can be time-consuming. Specialists with deep knowledge may not have the time to share their expertise organically,especially during busy periods. Additionally, when these individuals leave the organization, their tacit knowledge often departs with them,leading to significant knowledge gaps.

The Role of Tacit Knowledge in AI Workflows

1. Enhanced Decision-Making: Tacit knowledge provides context and depth to data-driven insights, leading to better decision-making. In Deloitte's Global Human Capital Trends survey for 2021, 3 out of 4 business leaders said that creating and preserving knowledge across evolving workforces is crucial to their success.
2. Improved AI Outputs: Incorporating tacit knowledge can enhance the relevance and accuracy of AI outputs. Integrating human expertise and context-aware, fact-based knowledge databases into the AI search process is a promising approach.
3. Knowledge Retention: Tacit knowledge integration ensures that valuable insights are retained and utilized, even if key employees leave the company. 
4. Enhanced Collaboration: Tacit knowledge fosters better collaboration by providing a deeper understanding of the nuances and contexts that drive decision-making and problem-solving. This leads to more cohesive and effective teamwork.
5. Personalized GenAI outcomes: Tacit knowledge helps in tailoring AI training data to reflect real-world complexities and subtleties, making AI models more robust and applicable to practical scenarios.

Tacit knowledge is essential for addressing complex and non-routine tasks that require a deep understanding of context and subtleties, which AI alone cannot fully grasp. By integrating tacit knowledge into AI workflows, businesses can create AI systems that are more accurate, reliable, and effective in their context and environment. This integration ensures that AI tools are not only technically sound but also contextually aware, enhancing their overall performance and relevance.

Challenges

Capturing tacit knowledge poses significant challenges due to its intangible nature and the resource-intensive process required for continuous input from experts. In Deloitte's Global Human Capital Trends survey, 75% of business leaders said that creating and preserving knowledge across evolving workforces is important to their success. However, only 9% of surveyed organizations felt ready to tackle this challenge. This gap is striking, especially considering that 54% of employees view organizations that prioritize knowledge sharing as more innovative, competitive, and attractive places to work.

Conclusion

Tacit knowledge is a critical component of effective AI workflows. By integrating this valuable knowledge into GenAI systems, businesses can enhance decision-making, improve AI outputs, and retain institutional knowledge. Successfully blending tacit knowledge with AI capabilities positions companies to drive innovation and maintain a competitive edge.

At 100mentors, we understand the importance of combining human expertise with advanced AI technologies. Our platform is designed to help you seamlessly integrate tacit knowledge into your GenAI strategies, ensuring better results and sustained success. Contact us today to learn how we can assist you in securing your organization’s tacit knowledge.

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Resources

1. Taming the Wild West of AI-generated search results, by IBM 
2. What is Tacit Knowledge: Importance, Benefits & Examples, by ProProfs
3. The ultimate guide to capturing and sharing tacit knowledge, by Happeo 
4. The new knowledge management, by Deloitte