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Bora Kaykayoğlu: Being AI-Native means becoming aware of your own capabilities
AI tools are now in everyone's hands. What separates two professionals using the same tools is how the person using them thinks. Bora Kaykayoğlu was a guest on Scrolli's Dijital Güç programme and spoke about originality, problem definition, the company brain and agents.
Who is an AI-Native professional?
Being AI-Native means a professional becomes aware of their own capabilities, strengthens their way of thinking and gets stronger output from AI. The focus is the human. AI is a secondary support, like an annex next to the main building.
For someone who asks each morning how to solve problems better, decide better and raise the quality of their work, AI is a highly valuable tool. If these areas are weak, what needs questioning is not the tool but the originality of the capability.
The capabilities that stand out
They vary by sector, but the common areas are clear. Making decisions, asking the right question, defining, discovering and solving problems, and thinking creatively and human-centrically.
BCG's research also places solution generation, evaluation, creative thinking and judgement where both the risk of skill loss and importance are highest. We need to talk about human bias as much as AI hallucinations. That is why the human stays in the loop.
Experience or AI skills?
For an employer, what matters is not seniority but the value a person adds. One year or twenty years of experience does not make the difference alone. When added value, risk and loss are defined with the right formula, it becomes clear who stands out.
I do not treat AI as the first choice. I analyse the areas where I spend the most time and need speed, and bring the tool in only there. Everyone's thinking algorithm is unique. The path to becoming AI-Native runs through self-discovery.
How do organisations become AI-Native?
Becoming an AI-Native firm, family business or university is a strong vision. It requires courage, a strong strategy and measurement. Thinking competence is not measured as often as technical competence. It should be measured regularly and linked to processes and KPIs.
Samsung requires engineers to run a TRIZ project, not just attend TRIZ training, to be promoted. Organisations should rehearse their own problems the way they run fire drills. A mind without method is hard to trigger.
A symptom is not the problem
We cannot solve what we cannot define. A machine's warning light is a symptom, not the problem. We suppress a headache with medicine, yet the real cause may be lack of sleep. That is why we separate problem definition from problem solving in our work.
There are fifty or sixty methods, and methods differ from models. Design thinking and the double diamond are models. Getting the right result requires knowing the method that fits the sector.
The company brain and agents
By adding company, sector and country knowledge on top of individual knowledge, a company brain or problem-solving brain can be built. Three questions are enough for a personal AI operating system. Where am I going, how will I get there, what do I need?
Agents are the future of AI. People are looking for tools tailored to their needs, and agent stores will spread. At KEIP Works we developed an agent that aims to solve company problems more effectively and turn them into inventions. Everyone should ask themselves what their own agent would do.
Implementation steps
Make your teams' problem definition and solving competence visible.
Plan short problem-solving drills for your own problems.
Start gathering company and sector knowledge into a company brain.
Resources
This text was prepared by reviewing relevant sources and drawing on their findings.