How Your Brain Responds to AI — and Why It Matters

1. Your brain responds to uncertainty with fear, ignorance, or curiosity. Fear narrows thinking and blocks learning. Ignorance keeps us out of the conversation. Curiosity opens the door to learning, understanding and new opportunities. 
2. Early chatbots frustrated people because they did not understand natural communication. Newer AI systems are better at recognising context and intent, which is why the experience feels different. 
3. AI can find patterns, but humans still decide what they mean. Judgment — whether the output makes sense and whether we are solving the right problem — remains human work.  
4. In roles where trust matters, the human relationship is essential. In important financial decisions, customers need more than correct information. They need confidence, responsibility, and human connection. 
5. Learning keeps the brain adaptable. Every new thing we learn creates new neural connections. Neuroplasticity is not a metaphor, the brain can rewire at any age, and curiosity helps sustain the motivation to keep learning. 

At first glance, Ivana’s career may seem like an unlikely mix of disciplines: computer science, neuroscience, digital transformation, and now conversational AI at RBI. But she sees a clear thread running through all of it. 

"Honestly, I was always doing the same thing," she says. "I was using technology to find meaningful patterns — to solve human problems and serve people." At one point it meant building a bridge between 5G technology and hospitals. Earlier, during her PhD, it meant analysing EEG signals and brain imaging to better understand the health of preterm babies. Now at RBI, it means building systems that help machines understand how humans communicate. 

Every field she has worked in required understanding what people actually need from a system, not just what the system is technically capable of doing. That question, held consistently across roles, is what makes her perspective on AI both grounded and unusually broad. 

When people encounter something new and uncertain, such as AI, a new job, or an unfamiliar environment, the brain often responds in one of three ways, depending on the person and their state of mind. 

Fear activates the threat response. "It narrows and blocks our thinking," Ivana says. Ignorance is different in form but similar in outcome — it avoids engaging with the unfamiliar and treats it as irrelevant. Both states may feel safe in the short term, but they are not beneficial for learning in the long term. 

Curiosity is the third option, and it generates questions and builds understanding. "At the point when curiosity takes over, everything changes," Ivana says. This is not only a motivational idea — it reflects how the brain works. Curiosity can reduce the threat response and activate brain systems linked to learning and reward. In that state, people are more able to explore, ask questions and build understanding — exactly the mindset needed to adapt to AI. 

The frustration people felt with early chatbots was not irrational. Those systems were mostly built on libraries of frequently asked questions, with predefined answers matched to recognised inputs. When users spoke naturally, with different wording, dialects, or unexpected phrasing, the systems often failed. 

Large language models changed that experience. They made it possible for AI to understand more of the context behind a question, not only the exact words used. This is what makes today’s virtual assistants more useful: they can better recognise intent, guide users through a process step by step, and provide more relevant support. 

What comes next is what Ivana describes as intelligent companions. These are agentic systems that do not only assist or explain, but can increasingly act on behalf of the user, within clearly defined, secure and trusted boundaries. Instead of asking the customer to navigate every step, an intelligent companion could support actions such as blocking a lost card, initiating a transaction, or completing a defined task after the customer gives clear instruction or confirmation.  

These systems are expected to become more proactive and more personalised. They will not only respond to what a customer asks but also use context to understand what the customer may need next, offer relevant guidance, and reduce unnecessary effort in the journey. 

But in banking, this shift from answering to acting must be handled carefully. The question is not only what AI is technically capable of doing. It is also where AI should be allowed to act, where human involvement remains necessary, and how these experiences can be designed responsibly when decisions affect people’s financial lives.  

“We need to approach it with security and trust,” Ivana says. 

Roles that are mainly task-based will change more than roles built on human connection. Customer-facing roles in banking are more complex. A relationship manager does not only read account data — they understand a customer’s situation, needs and circumstances.  

In moments when important financial decisions need to be made, people need more than information. They need trust. And that kind of trust is built through human connection.  

This is why technology can change the way banking works, but it does not remove the need for people. It can make processes faster, simpler, and more personalised. But in moments where trust, responsibility and judgment matter, human relationships remain essential. 

"Judgment is also very important," Ivana says. "AI can find patterns amazingly well. But we are here to decide whether they make sense." 

For anyone anxious about their professional future in an AI-driven world, Ivana’s advice is to start with how the brain works. “Whenever we learn new things, we create new connections in the brain,” she says. The point is simple: our capacity to adapt does not disappear after our mid-twenties — it stays with us as long as we keep learning. Neuroplasticity means that the brain can keep changing, learning and creating new connections throughout life. 

Curiosity helps us stay motivated to learn. And the more we learn, the more flexible we become in dealing with what comes next. 

So the advice is simple: keep learning, keep experimenting and stay curious. This helps us stay relevant in our careers and keeps the brain adaptable over time.