Artificial Intelligence is Reviving the 'Corporate Mind'

In the business world, the so-called Polanyi’s paradox has long explained a simple truth: we know more than we can put into words. In retail and logistics, this "tacit knowledge" is often hidden within the daily practices, intuitive decisions, and shortcuts that employees use to simplify their workflows. Research suggests that up to 85% of corporate knowledge exists in this informal form, remaining inaccessible to traditional manuals.

The New Economy of Knowledge

Traditionally, companies attempted to standardize workflows through a "top-down" approach, which was often disconnected from reality. However, the introduction of AI agents has changed this landscape. Modern systems allow rank-and-file employees—whether a warehouse worker or a consultant—to directly identify flaws or suggest optimization methods.

In this process, the AI agent acts as a "nervous system," collecting information provided by employees and transforming it into a centralized knowledge base. As a result, companies are moving from one-off training sessions to a continuous updating process known as "everboarding." This not only simplifies the adaptation of new employees but also protects the organization from losing institutional knowledge when experienced staff members leave.

Multimodal AI and Practical Benefits

Modern artificial intelligence is no longer limited to text documents. Multimodal agents work with audio, video, and photographs. For example, an employee can take a photo of a shelf, and the AI can automatically compare it to a plan and indicate what needs to be changed. Thanks to small-scale models, this data is often processed directly on the device, ensuring high security and immediate response times.

According to MIT economist David Autor, tasks that require flexibility, judgment, and common sense are difficult for artificial intelligence to master. However, the goal of AI should not be to replace these skills, but to complement and strengthen them.

Cultural Transformation

Technological implementation alone is not enough. Research shows that the main prerequisite for success is not just algorithms, but corporate culture. Companies that encourage experimentation and allow employees the freedom to make mistakes achieve significantly better results when implementing AI.

For the Georgian market, where the service and logistics sectors are actively developing, this approach could become a key lever for increasing efficiency. When a company begins to listen to its employees' experiences and structure them through AI, it gains not only optimized processes but also a more motivated team that feels like an integral part of the process.