At a fireside chat in Lisbon, F1 racing legend Rubens Barrichello and Softswiss Founder Ivan Montik discussed why human intuition remains vital for business success when Artificial Intelligence falters in uncertain conditions.
Two figures from different worlds – racing and tech – have joined voices to deliver an urgent message for business: AI, for all its strength in learning patterns, struggles when the world shifts unexpectedly.
Rubens Barrichello, the winner of eleven Grands Prix across nineteen seasons, described how Machine Learning models excel at what has already happened while human judgement dominates in moments of chaos, unpredictability or ‘concept drift’.
Speaking in Lisbon, Barrichello, who is also a Non-Executive Director for Latin America at Softswiss – a leading provider of tech for iGaming – drew on his long racing career that includes competing in F1 to illustrate this issue.
He spoke of telemetry and patterns, sharing the stage with Softswiss Founder Ivan Montik. In a fireside chat with Barrichello, Montik discussed what these takeaways about human capacity versus AI mean for business visionaries today.
Lessons from the racetrack
Numerous studies show that AI systems perform well in expected or familiar conditions but drop in performance during edge cases – for example during black swan events or sudden changes to physical conditions. The gap between humans and machines often arises because AI models are trained on historical data, so when features shift (for example lighting, geometry, speed, rain, human behaviour) that training may not cover new combinations.
Barrichello shared his experience from Silverstone back in 2008 that highlighted the difference between numbers and instinct.
“If I’m on the racetrack and the track is wet but getting drier, the only way for me to go faster is with the engineer knowing the numbers, the telemetry and everything else. Coming in for slick tires is a must,” he said. “If I’m on the racetrack on slick tires and it’s getting wet, then it’s my call because I’m the only one who will know how wet it is.”
The team asked if he wanted intermediate tires and Barrichello said, “No, I need wets,” leaving the engineers wondering how he knew this.
“Because the rain was so strong and moving like this; normally, with the speed, you have the rain coming this way or that way. Although it’s an open cockpit, my hands were getting soaked and I said, this must be strong, heavy rain. So I went for the right tires because of instinct,” he said.
The call was correct and, for Barrichello, it was a lasting reminder that instinct can sense what backwards-looking data cannot. In other words, AI alone cannot be trusted, at least not yet, when hard-to-predict shifts in external conditions occur.
Positioning for business success in any weather
Montik said this is a powerful lesson to learn not just for athletes but also for companies operating in any sector of the economy.
“It’s 2025 and many organisations are effectively driving on changing tarmac themselves: sudden demand shocks, new fraud vectors, tech innovation, fast-moving regulatory and geopolitical shifts have invalidated yesterday’s playbook.
Machine Learning models are, by design, trained on historical data. When the underlying data distribution changes – a phenomenon known as concept drift or non-stationarity – their performance degrades, often fast. While it may be fashionable for C-suite decision-makers to incorporate AI across all areas of work, it is important to remember that AI is still just a tool for people to shed repetitive tasks and concentrate on the work that requires more creativity and “out-of-the-box thinking.”
Montik argued that companies must design their operations with this interplay in mind.
“AI is a powerful engine for efficiency but it should never replace human intuition,” he said. “I strongly believe in the process of constant reinvention and improvement – of products, of processes, of ourselves. Only by questioning what worked and what faltered today can we create better outcomes tomorrow.”
His words echoed Barrichello’s racing instinct: to use human instinct to recognise when conditions have changed and adjust course before it is too late.
For all the promise of Machine Learning, the future still belongs to companies that combine AI’s ability to learn from patterns with the human capacity to sense when the patterns no longer apply. Just as a driver knows when slicks won’t hold in the rain, decision-makers must be ready to override the model, trust their instincts and then retrain for the new reality.
The winners in 2025 and beyond will not be those who rely on AI alone but those who build resilient teams where human judgment and Artificial Intelligence drive together, ready for any weather.
