The company’s Group CEO says 80% of its code is AI-assisted and sprint cycles have compressed from two weeks to three days. The first claim explains how the second might be possible. Both demand scrutiny.
Bayo Adedeji did not bury the lead. In a LinkedIn post, the Group CEO of Wakanow announced that the company has restructured its engineering function around AI-assisted development, compressing its sprint cycle from two weeks to three days. He called it the beginning of a full AI transformation. The framing is confident. The strategic signal, if it holds, is significant.
The two claims are related, and the distinction matters.
The 80% AI-assisted figure is the structural one. It describes a change to how Wakanow builds: developers working with AI tooling across the majority of the codebase, removing enough of the manual burden that the pace of output has materially increased. That is plausible. It is also the condition that makes the sprint compression claim worth taking seriously rather than dismissing outright.
But the sprint number still invites scrutiny. Two weeks to three days is not a marginal efficiency gain. It is a different rhythm of work, and that kind of compression does not happen purely because code gets written faster. In practice, it typically reflects one of two dynamics: genuine end-to-end acceleration, where AI tooling has shortened the full cycle from scoping to deployment, or a redefinition of sprint scope, with larger workstreams broken into smaller modular releases that each clear in three days. Both outcomes represent progress. They are not the same outcome, and Adedeji’s post does not specify which is driving the number. That distinction is worth watching as Wakanow begins publishing its promised weekly updates.
What is already clear is the strategic implication of the shift.
Wakanow operates where airline inventory, payment infrastructure, and customer experience converge. Each of those surfaces has historically moved at the pace of its slowest upstream dependency: NDC connectivity timelines, payment gateway integrations, fare display logic that breaks when a carrier restructures its ancillary offering. These are not problems that yield to careful iteration on a two-week cycle. At three days, the constraint changes.
This is the more important insight buried in Adedeji’s announcement. When AI removes the coding bottleneck, the binding constraint moves upstream. The question shifts from how fast engineers can build to how fast leadership can decide. That is a harder problem, and one that does not resolve itself through tooling adoption. Organizations that accelerate their build capacity without accelerating their decision architecture tend to produce volume, not velocity.
African OTAs have historically prioritized resilience over speed, and for good reason. Fragmented payment infrastructure, variable connectivity, and carriers with limited API sophistication rewarded methodical operators. Wakanow is now signaling that it intends to be both methodical and fast. Whether its internal decision-making can sustain that pace is the question the market cannot yet answer.
Adedeji committed to weekly updates on shipped improvements. That is either a sign of genuine organizational readiness or an overcommitment that will become visible quickly. Wakanow’s booking engine, payment flows, and partner-facing tools are observable. The improvements will either materialize or they will not.
What is already settled is that the announcement has reset expectations across the sector. For Wakanow’s competitors, the challenge is not to replicate the AI transformation story. It is to decide, with urgency, whether they have a credible answer to what a leading African OTA just put on the table.
Travel Distribution News covers airline distribution, travel technology, and emerging markets with a focus on Africa.
