Nairobi’s Escalating Traffic Crisis Is A Job For AI, Not More Traffic Police Officers

Yesterday evening, while commuting to an event here in Nairobi, I found myself once again — and far too often these days — confronted by the scene in the above photo: complete traffic gridlock.

This was actually the third instance coming from home en route to my destination. Even after this moment, I hit two more choke points that forced me onto back roads — our infamous “panya routes” — in what turned out to be a mostly futile exercise, yielding only marginal gains in commute time.

Having worked remotely since the Covid-19 pandemic five years ago and recently vacated a long-unused office (more on this in a future post), I’ve been spared the agony of commuting. The silver lining? I’ve gained anywhere from 2 to 4 hours of daily productivity. So when I do get stuck in traffic these days, it feels incredibly frustrating.

Our traffic police are out there doing the best they can under incredibly challenging circumstances — directing overlapping matatus, rule-breaking motorists, rogue boda bodas, and everything in between. But the reality is they’re overwhelmed, and commuters are equally exasperated. I wouldn’t be surprised if road rage incidents are on the rise.

Then it hit me: why are we still using humans in the form of traffic police officers to do a robot’s job — literally — when managing Nairobi’s traffic?

Ironically, in South Africa, they call traffic lights “robots” — and perhaps, that’s the future we should be leaning into. Why not deploy actual AI-enabled robots (or smart traffic management systems) to do the job better?

Around the world, cities have already deployed AI-enabled traffic management systems to tackle urban congestion with far more sophistication and scale than any human traffic officer could ever manage. These systems use a mix of real-time data from GPS, sensors, cameras, and mobile phones — combined with predictive analytics — to optimize traffic in ways that are dynamic and context-aware.

Here’s how AI can revolutionize Nairobi’s traffic:

Smart Traffic Signals: AI algorithms adjust traffic light timings dynamically based on real-time traffic conditions, reducing wait times and improving flow. No more fixed-timer systems.

Optimized Routing: Platforms like Google Maps can be integrated via APIs to feed real-time and historical traffic patterns into a centralized AI system — rerouting traffic in real time and evenly distributing congestion across the road network.

Predictive Analytics: Machine learning models can analyze patterns across weeks, months, and years to forecast congestion hotspots — helping the city plan better around rush hours, events, or even weather.

Automated Violation Detection: Many cities already use AI-enabled cameras that detect infractions like speeding, red-light violations, or illegal turns — and automatically fine offenders. No human needed.

Imagine Nairobi’s intersections functioning like intelligent ecosystems — adapting in real-time, learning from the past, and reacting to every traffic condition instantly. That’s the potential impact of AI.

Let traffic police focus on enforcement and safety — not directing chaos at congested junctions. Let smart traffic management systems handle the mundane but important work. The technology exists. The use cases are proven. Nairobi is more than ready.

Don’t give a human a robot’s job. Let robots run the robots.