Dimmy Kanyankole: Data, Boda-Bodas, and M-Pesa. What Nairobi Taught Bolt About Emerging Markets.
As African cities expand, transport is becoming more than a convenience business. It is becoming a data, infrastructure and productivity question. In Nairobi, where traffic patterns can change within minutes and a short trip can take far longer than expected, ride-hailing platforms are being tested in real time.
For Bolt, Nairobi is not just another market. It is a live learning environment for how technology, pricing, driver supply and consumer behaviour can work in fast-growing African cities. Techfolio spoke with Dimmy Kanyankole, Senior General Manager for Rides in East Africa at Bolt, on how artificial intelligence is shaping urban mobility and what Nairobi can teach other emerging markets.
Dimmy Kanyankole! How is Bolt using AI and predictive analytics to improve pricing, routing and driver utilisation in Nairobi?
At the heart of our business is a marketplace. On one side, you have riders who want a fast, safe and affordable trip. On the other side, you have drivers who want strong earnings and efficient use of their time. AI helps us balance both sides better.
We use machine learning in areas such as driver-rider matching, pricing, routing and demand prediction. For example, the system looks for the closest suitable driver so that pickup times are reduced. That matters a lot in Nairobi because time is unpredictable. A five-kilometre trip can take 15 minutes or 50 minutes depending on traffic, weather, road works or the time of day.
Routing is also important. We do not only look at distance. We also look at real traffic behaviour and historical movement patterns. This helps us give better estimated arrival times and improve the overall trip experience.
On pricing, our systems respond to real-time demand and supply. When demand rises in one part of the city and there are fewer drivers, pricing adjusts to attract more drivers to that area. This supports availability for riders and better earning opportunities for drivers.
We also use predictive analytics to identify where demand is likely to grow. For example, the CBD during evening peak hours, entertainment areas at night, airports, malls, or venues during events. This allows drivers to make smarter decisions on where to position themselves instead of waiting blindly.
What has Nairobi taught Bolt that could shape mobility platforms in other emerging markets?
Nairobi teaches you that mobility solutions must be practical. You cannot design only for perfect roads, perfect traffic or one payment method. The product must fit the reality on the ground.
One major lesson is payment flexibility. Nairobi remains a market where cash and mobile money are very important. We support cash, M-Pesa and card payments because riders need choice. A platform that ignores mobile money in Kenya would miss how people actually transact.
The second lesson is price sensitivity. Customers are very aware of value. That means we have to build efficiency into the whole system. You cannot depend only on discounts. The product itself has to work better, reduce waiting time and offer fair pricing.
The third lesson is the role of two-wheelers. Boda rides are not just an add-on. They are a serious mobility solution for affordability, speed and last-mile access. In many African cities, two-wheelers can connect areas that cars cannot serve efficiently.
Can ride-hailing platforms become smart-city infrastructure partners?
Yes, but that role has to be earned. Platforms like Bolt generate useful mobility insights. We can see anonymised demand patterns, congestion points, preferred routes and how people move at different times of the day.
This kind of data can help cities plan better roads, improve public transport corridors, manage events and understand where mobility gaps exist. But it must be done responsibly. Privacy is non-negotiable.
We are open to working with city authorities where there is clear public benefit, strong data protection and a partnership mindset. We do not see ourselves replacing public infrastructure. We see ourselves as a technology partner that can help cities make better transport decisions.
