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The Central Bank of Kenya (CBK) has identified almost 300 areas where it plans to use artificial intelligence across 14 departments, including economic forecasting, inflation monitoring and payments, and has already started implementing some of them, CBK Director of Research Prof Robert Mudida said on Saturday, October 31, 2026, as reported by The Kenya Times.
“So we got almost 300 use cases from the 14 departments. And now what we’re doing is we’re implementing them,” Mudida said.
Four levels of AI at CBK
| Level | What CBK says it is doing |
|---|---|
| Routine automation | Already in use in banking, payments and research, cutting tasks that took hours |
| Machine learning | Used by the Research Department to improve economic forecasts |
| Generative AI | Being explored to turn satellite images and other data into text assessments |
| Agentic AI | Listed as one of the four levels under study |
Better inflation forecasts
Mudida pointed to the inflation forecasting errors after the energy crisis that began in late February 2026. Machine learning models can learn from past misses: if a forecast underestimated the second-round effects of a shock, the system can give those effects more weight next time. CBK says it is combining these models with its traditional forecasting tools, not replacing them.
“AI augments intelligence. So you still need human judgment in a very critical way,” he said.
The timing matters. Kenya’s inflation rose to 7.3% in October 2026, the highest since July 2023, putting more pressure on the Monetary Policy Committee (MPC) to read the economy accurately.
Nowcasting before GDP data is out
The Kenya National Bureau of Statistics (KNBS) publishes GDP with about a one-quarter delay. Second-quarter 2026 GDP, for example, was released only in early October. That means the MPC can be setting interest rates with data that does not reflect the current economy.
To close that gap, CBK is studying “nowcasting”, estimating current activity from data that arrives faster:
- Satellite night lights as a clue to industrial activity and electricity use.
- Vegetation changes in satellite images to track agricultural activity.
- Mobile payments data to estimate how much economic activity is happening in real time.
Generative AI could then summarise what the images show into written assessments that researchers use alongside official statistics.
What it means for businesses and borrowers
- Faster policy reactions. If CBK can see a slowdown or price spike earlier, interest rate decisions may respond sooner. That affects loan rates, T-bill yields and savings returns.
- Payments and fraud. AI in payments oversight could help spot fraud patterns earlier as card and mobile fraud grows.
- Data privacy questions. Using mobile money data for economic estimates raises questions about anonymisation. CBK has not published details of how such data would be handled, so this is one to watch.
What we do not know yet
CBK has not published the list of 300 use cases, a budget, vendors or a timeline. It is not clear which use cases are live beyond routine automation and the forecasting work described. We will update this page if the bank releases a formal AI strategy or policy paper.
For related CBK coverage, see how Kenyan firms are handling input costs, according to CBK surveys, and how to complain to CBK about a bank.
Related: 73% of Kenyan firms lack mature tech skills despite digital push, Moringa survey says
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