Nermin Zejnilović: In the Age of AI, Better Questions Matter More Than Faster Answers
Nermin Zejnilović is a behavioural strategist, systems thinker and AI advisor whose work connects human behaviour, organisational decision-making and emerging technology. Through education, advisory projects and digital prototyping, he helps organisations move beyond the question of which AI tool to use and examine the people, decisions and systems that technology is expected to improve.
He is also developing Kvestology, a framework for understanding how questions shape attention, assumptions and decisions. For i-platform, Zejnilović speaks about the quality of thinking in the age of artificial intelligence, the human side of technological change and the potential of stronger connections between Switzerland and Bosnia and Herzegovina.
Your work connects behavioural psychology, systems thinking and technology. What brings these seemingly different fields together?
Human behaviour connects them.
Technology does not enter an abstract space. It enters organisations containing people, relationships, habits, interests, unwritten rules and different interpretations of the same problem. We can build a technically excellent solution, but if we do not understand the system in which it will operate, it may never be adopted or may produce consequences we did not anticipate.
Behavioural psychology helps me understand how people actually make decisions, what attracts their attention and why behaviour frequently differs from declared intentions. Systems thinking expands the view towards relationships, rules, feedback loops and structures that shape that behaviour.
Technology is the third layer. It can reinforce the existing system or help us redesign it. I am therefore less interested in what a particular tool can do than in what will change when people begin using it.
You are developing a concept called Kvestology. What does it represent?
Kvestology is a developing framework concerned with the architecture of questions, how questions direct attention, establish the boundaries of a problem and influence the decisions we consider possible.
Every question contains assumptions. When a company asks how it can introduce AI more quickly, it has already assumed that speed is the central problem and that implementing AI is necessarily the desired objective.
If we change the question to “Which decisions in our system could become better with the support of AI?”, a different field of inquiry emerges. We must discuss data quality, responsibility, human judgement, risk and what we actually mean by a better decision.
Kvestology does not claim that there is one perfect question. It attempts to develop ways of identifying hidden assumptions, excluded perspectives and the consequences of how a problem has been framed.
Why do questions become more important when AI can provide an answer within seconds?
Because answers have become cheaper, while judgement has not.
Generative artificial intelligence can produce a highly persuasive response to a poorly framed question. It can neatly structure the wrong problem, accelerate a process that should not be accelerated or produce ten variations of a solution without understanding the wider context.
In the past, much of our effort went into finding information and producing an initial answer. Today, value is shifting towards choosing the problem, evaluating the response and understanding its consequences.
This is why I believe the ability to formulate better questions will become one of the central competencies of the AI era. Not because questions sound intellectual, but because they determine what technology will attempt to optimise.
What do organisations most frequently misunderstand when they begin adopting AI?
They usually begin with the tool.
The discussion becomes: which model should we use, which licence should we purchase or which process can we automate? The technical component can often be demonstrated relatively quickly. The greater challenge is organisational and human.
Who is responsible for the output? Which data can we trust? When is verification necessary? Who has the authority to make the final decision? Do employees understand the system’s limitations? Will the new solution actually be used, or will it become another platform that exists primarily in management presentations?
AI adoption is not merely a technology project. It changes behaviour, responsibility and the way an organisation produces knowledge. If we do not design those changes consciously, technology will still change them, only without our full understanding or control.
How does behavioural strategy change the way we approach digital transformation?
Traditional approaches often assume that people will adopt a new system once they are shown that it is more efficient. People, however, do not evaluate change solely through rational benefit.
A change can threaten someone’s sense of competence, status, autonomy or professional identity. A new process may technically require less effort while creating greater psychological uncertainty. Employees may not openly reject the technology, but they may continue using old procedures, duplicate work or avoid responsibility.
Behavioural strategy therefore examines what people actually do, not only what they say they will do. It considers incentives, friction, uncertainty, social norms and how choices are presented.
Digital transformation succeeds only when the technical solution fits the real behavioural context.
Through the Swiss-Balkan Design Bridge and other initiatives, you work between Bosnia and Herzegovina and Switzerland. What can these contexts learn from one another?
I try not to idealise either context.
Switzerland demonstrates the value of continuity, institutional trust, process and long-term planning. In the Balkans, we often see remarkable adaptability, resourcefulness and an ability to work under conditions of high uncertainty.
The problem begins when we equate Swiss structure with slowness and Balkan improvisation with innovation. Structure can enable innovation, while improvisation without a system frequently remains a method of survival rather than a basis for development.
Programmes such as the Swiss-Balkan Design Bridge are valuable because they do not simply attempt to transfer a solution from one society into another. They create a space in which different experiences can work together on concrete problems.
The most interesting solutions frequently emerge between perspectives rather than entirely within one of them.
What role can the diaspora play in this relationship?
The diaspora is often discussed primarily in terms of money, investment or return. I believe its equally important role is translation between systems.
People familiar with several social and professional contexts can explain not only what is done differently in another country, but why a particular model functions there. They can recognise what can be transferred, what must be adapted and what would be entirely inappropriate to copy.
This is particularly important in technology and innovation. We do not need replicas of trends from Switzerland, Germany or the United States. We need people capable of connecting international knowledge with the actual needs of local organisations and communities.
Platforms such as i-platform can play an important role precisely as infrastructure for this form of connection.
Can AI help the Western Balkans make a developmental leap?
It can, but technology alone will not change institutional patterns.
AI can help smaller companies access knowledge, develop prototypes, improve services and become more competitive. Public institutions can simplify certain processes. Education can become more accessible and responsive to individual needs.
The same tools can also increase superficiality, centralise power, automate poor procedures and create the appearance of modernisation without meaningful change.
A developmental leap will not depend only on how quickly we adopt AI. It will depend on the quality of our institutions, education, trust and the questions we ask about the future we want to build.
Technology can increase our capacity. It cannot decide what that capacity should serve.
What comes next for Kvestology?
I want to develop it as a practical and research-oriented framework rather than merely an interesting term.
This includes methods for analysing questions, tools that can be used inside organisations, educational programmes and content connecting philosophy, behavioural science, language, systems thinking and technology.
I am particularly interested in the relationship between humans and AI: how technology affects our attention, how it changes our sense of authorship and whether we will use it as a substitute for thinking or as a partner that helps us recognise our own assumptions.
For me, Kvestology is not a search for a final answer. It is an attempt to develop a better discipline for arriving at questions that deserve our attention.
What is one question every leader should ask before introducing AI?
“Which decision are we trying to improve and what would have to be true for us to know that AI is genuinely helping?”
This question forces us to define the problem, responsibility and criteria for success before we are seduced by the speed of a demonstration.