Institutional knowledge (IK) refers to the collective experience, processes, insights, and expertise that exists within an organization but often isn’t formally documented. It includes:
- The accumulated understanding of “how things really work” that employees develop over time
- Unwritten workflows and problem-solving approaches
- Historical context about past decisions, projects, and relationships
- Cultural norms and informal networks
- Technical knowledge specific to the organization’s systems and processes
- Understanding of what has and hasn’t worked in the past
This knowledge is particularly valuable because it’s unique to each organization and difficult to replicate, especially in the realm of sales and marketing. However, it’s also vulnerable to loss when employees leave the company. This is why many organizations try to capture sales and marketing IK through:
- Documentation and knowledge bases
- CRM and ERP systems
- Mentorship programs and cross-training initiatives
- Regular knowledge-sharing sessions
- Process mapping exercises
- Recordings of phone calls and video meetings
The challenge is that much IK is difficult to verbalize or document because it comes from personal experience and context. This is where AI has evolved to enable what was not possible before, or at least not easily accomplished. AI systems can scan and analyze existing documentation, emails, reports, and internal communications to extract and model key information, processes, and decision patterns. AI systems can be built from the input, and converted to an output system capable of representing the “collective” working knowledge of an entire company.
How the evolution of AI enables the digitization of Institutional Knowledge
Evolution: AI systems can adapt and update as new knowledge is added, keeping information fresh and relevant.
Scalability: AI can process and organize vast amounts of information much faster than manual methods, making it feasible to capture knowledge across large organizations.
Consistency: AI systems apply consistent methods to knowledge capture, ensuring uniform quality and organization.
Accessibility: Modern AI tools can make knowledge more discoverable through advanced search and recommendation systems.
Preservation: AI helps prevent knowledge loss when employees leave by continuously capturing and organizing information.
It can be argued that the value of an organization’s IK—from a cash-generation perspective—is as valuable as its IP portfolio or good will. The company’s IP is the brain and goodwill is its reputation, whereas IK is the heart and body of an organization. In sales and marketing, IK directs the customer service teams to the best approach for working with customers and solving issues that align with the company’s strategic goals with regards to every individual’s customer account.
The decision to build your organization’s IK into an AI library is not a matter of “if”, but when you should begin. This process is accretive, but the benefits are immediately applicable to day-to-day processes once a minimum training plateau is reached. At that point, the system can be deployed process-by-process, to work with your team to recognize patterns, catch errors and other optimizations as defined.
Contact CRSTBL to find out how your organization can start your IK + AI journey.
