Giving employees access to AI tools does not mean business results improve at the same pace. Generating text, producing summaries, and preparing presentations are now routine tasks. In an AI-Native company, AI is considered alongside business processes, decision-making practices, and team capabilities.
The difference between a company that uses AI and an AI-Native company
In an AI-Native company, AI goes beyond being an individual shortcut. The company deliberately identifies where to use it in problem definition, generating alternatives, decision-making, and implementation. To understand whether a company is AI-Native, you need to look at how its teams think and work as well as its list of tools.
The capabilities that determine output quality
The quality of a result from AI depends largely on the capabilities of the person asking the question. A team that struggles to frame a problem may get superficial answers even from an advanced model. Problem solving, creative thinking, critical thinking, judgment in decision-making, and defining business needs are among the foundational capabilities of AI-Native transformation. Methods such as TRIZ and design thinking can also help structure thinking when working with AI.
How does a company become AI-Native?
Transformation can be approached in four steps. First, examine teams' current capabilities and AI use. Next, develop the capabilities found to be lacking. In the third step, apply these capabilities to real business problems using AI tools. In the final step, turn the result into a measurable business output.
In this setup, training continues beyond knowledge transfer into practice. Each session begins with a problem from the team's own work and ends with an improved output. When these sessions continue regularly, AI use can become part of everyday work.
Starting small and maintaining consistency
A large, lengthy program is not a prerequisite for getting started. A short session focused on a single business need can help the team see how it achieves results with AI. Further development can then be spread over time according to need.
Kaykayoğlu has worked on this transformation with organizations ranging from manufacturing to academia and from R&D teams to the service sector. For example, he ran an organization-wide AI capability program for SNOP Groupe Türkiye production teams and organized an AI-Native development program for academics at Kapadokya Üniversitesi.
This text was prepared by reviewing the relevant sources and drawing on their findings.
