The Art of Travelling Alongside AI in a World of Abundant Answers

No artificial intelligence tools were used in writing this article. After a long break, I am writing for Başlangıç Noktası again. I am still proud of the journey of this platform, which I co-founded in 2018. Since then I have followed the development of artificial intelligence closely. The more it can do, the more I question how we think. In 2019, in “Emotional Resilience in Individuals and the Competencies of the Future”, and in 2020, in “Covid-19, Remote Work and Corporate Culture”, I asked how people can keep pace with change. Today a new question joins that one: when answers come this easily, how much room do we leave for our own judgement? With AI tools we can produce analyses, strategies and even life-shaping recommendations in a few sentences. Change the question slightly, and the same system can defend the opposite of its previous answer with the same confidence. It has never been so easy to find someone to applaud your own opinion. An explanation that sounds reasonable is not, on its own, evidence. Fluency, logical consistency, grounding in evidence and fit with the context of the decision are separate criteria; success in the first two does not automatically guarantee the other two. As output multiplies, the real issue becomes judging which of it we can trust, and why. How we ask also matters. If we embed an assumption we take to be true in the question, the system can produce reasons that support that framing. Without realising it, we can start collecting answers that confirm our own views. That is why, when we begin an analysis, we should also look at which assumptions we carry into the question. This is why curiosity, resilience and adaptability matter far more. McKinsey Global Institute’s US workforce report of 29 September 2026 addresses these competencies together with the willingness to learn and the ability to work with AI. The World Economic Forum’s scenario report of 7 January 2026 likewise considers agility, learning by experimenting and context-based judgement together with AI literacy. According to Bain’s report, domain expertise, empathy and decision accountability stand out. What I take from this: (1) knowing the subject lets us question the output; (2) understanding the other person lets us see whom the answer serves; (3) curiosity and adaptability let us change our minds when new evidence arrives. This year, at the “Return to Analogue” panel, I had the opportunity to share the stage with Mr Faruk Eczacıbaşı, President of the Turkish Informatics Foundation, who led the founding of Başlangıç Noktası and has illuminated our country with nearly forty years of experience in digital transformation. His emphasis was the same: preserving our “analogue”, that is, human strengths such as thinking, questioning, creativity and decision-making is non-negotiable for humankind in the world of AI. In short, AI can suggest different paths; it is still we who will live with the consequences of a decision and take responsibility for it. We must set the limits of delegation according to our capacity to evaluate the output and the consequences of an error. We need to protect the time we devote to critical thinking. Just because the answer comes quickly does not mean we have to finish thinking just as quickly. What do I suggest? Clarify what you are deciding. Separate verified information, interpretation and assumption; examine how the outcome changes when a critical assumption changes. Express uncertain inputs as ranges. Verify t…