AI is already here, whether we notice it or not.
From Ada Lovelace's 1843 algorithm to the facial recognition on your phone this morning – artificial intelligence isn't new, it just finally has the data and computing power to work.
Did you unlock your phone with facial recognition this morning? Check a transport app to plan your commute? Look at the weather forecast to decide between sunscreen and an umbrella? In many cases, we are no longer actively deciding to use AI, it is already there, subtly shaping the information we receive and the decisions we make.
That quiet, pervasive presence is exactly why we can no longer afford to ignore it.
An idea 150 years older than we think
Here’s something that surprises most people: the idea behind AI is not new at all. You can trace it back to 1843 before electricity, before the internal combustion engine, when Germany had barely laid its first steam locomotive line.
It was then that Ada Lovelace and Charles Babbage worked together on what they called an “analytical engine.” Ada wrote detailed, step-by-step instructions for the machine, a logical sequence for calculating Bernoulli numbers, where one result fed into the next. What she described, we now call the first algorithm.
More remarkably, she already imagined that if numbers could represent things, the machine could one day process music, text, or patterns. The concept of machine intelligence was there in 1843. It only took another 150 years for the hardware to catch up.
The term “artificial intelligence” itself didn’t appear until 1956, at a conference in Dartmouth, USA, where researchers gathered around a deceptively simple thesis: if you can describe thinking sufficiently, a machine can simulate it. No feelings, no consciousness — just the formalization of the processes of deciding, solving, and processing.
The idea was right. What was missing was data, computing power, and connectivity.
AI is not new. The only new thing is that it now works.
Why rail is perfectly positioned for AI
The rail industry, for all its complexity, is actually predestined for AI support. Rail is an industry defined by complex systems, scarce resources, and a reality that almost never matches the plan. Disruptions are the rule, not the exception. Capacity is chronically tight. Coordination across dozens of players is the norm.
Those are precisely the conditions where AI can provide meaningful support, not as a gimmick, but as a genuine operational tool.
And yet, despite all this potential, rail has been slow to act. The conversations keep circling. The pilots stay small. The silos stay intact.
The right time is now
There’s a moment in the development of any transformative technology when market shares can shift rapidly, when the advantages go to those who move early, not to the largest or the oldest players. Rail is at that inflection point right now.
That means bringing together operators, freight railway companies, technology providers, innovators, and leaders, not to agree on everything, but to think together, challenge assumptions, and then get to work.
Because if there’s one thing we know, it’s this: the machine sets the pace. And the only response to that is not panic, it’s preparation, curiosity, and the courage to take the first step.
There’s a crucial difference between Innovation Now and Innovation Eventually. The first demands something from all of us: openness and a willingness to try.
Babette Müller-Reichenwallner is Co-Director Germany at PROSE GmbH. She was a moderator at railXchange 2026 in Frankfurt.
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