Average exposure score
Kenya sits higher on the baseline country-conditioned exposure measure.
Kenya1.675
Zambia1.446
Comparative diagnostic
Kenya and Zambia: similar regional setting, different exposure structure
Two lower-middle-income countries in Sub-Saharan Africa show a similar broad mode of exposure, but not the same position in the atlas.
Kenya and Zambia make a useful first comparison because they share a regional setting and income tier, but not the same place in the exposure distribution. Kenya sits above Zambia on average task exposure and on the share of tasks in the high-exposure range. Even so, both countries still lean more toward augmentation than substitution.
Within a similar regional and income setting, what changes when one country sits meaningfully above the other in average task exposure, but both still remain augmentation-heavy rather than substitution-dominant?
At a glance
The baseline comparison is clear.
At the headline level, Kenya is the more exposed of the two countries. Its average exposure score is 1.675, compared with 1.446 in Zambia. Its high-exposure share is 67.2%, compared with 53.0% in Zambia. That baseline matters, but it is only the beginning of the comparison. The atlas becomes more informative once we ask what kind of exposure is rising, and through which tasks and roles the difference appears.
Atlas proof point
The atlas becomes more informative once we move beneath a single country average and ask how exposed tasks are distributed across roles and pathways.
Why the average is not the whole story
Both countries still remain augmentation-heavy.
Kenya is more exposed, but it has not crossed into a qualitatively different regime. Kenya's substitution share is 61.1%, but its augmentation share is larger at 93.1%. Zambia shows the same broad direction, with substitution at 48.9% and augmentation at 88.2%. The more useful reading is therefore not that Zambia is an augmentation story and Kenya a replacement story. It is that Kenya carries a denser and more strongly exposed bundle of tasks within a still broadly augmentation-heavy profile.
Where the signals concentrate
The difference shows up inside a similar broad family of work.
The standout signals in both countries are concentrated in service-support and information-handling work rather than in one isolated sector. Kenya's top occupation highlight is Tellers, while Zambia's is Billing and Posting Clerks. The top skill highlights again point toward transactional and clerical routines. Kenya's higher exposure does not appear to come from an entirely different world of work. It appears to come from a more strongly exposed version of a broadly similar service and support profile.
Kenya
Tellers
- Occupation
- Tellers
- Industry
- Reproduction of recorded media
- Skill
- Collect public transportation fares and return correct change
Zambia
Billing and Posting Clerks
- Occupation
- Billing and Posting Clerks
- Industry
- Reproduction of recorded media
- Skill
- Type texts accurately at high speed
What to remember
Higher exposure does not automatically imply a replacement-heavy story.
The main lesson is not that Kenya is simply more exposed and Zambia less exposed. The more useful lesson is that higher measured exposure within a similar regional and income setting does not automatically translate into a replacement-heavy narrative. The relevant policy conversation is therefore not only about shielding workers from direct replacement. It is also about how clerical, administrative, and digitally mediated service work is changing, what kinds of software and workflow tools are being absorbed into jobs, and which skills help workers move within or alongside that transition.
Kenya sits higher in the exposure distribution
Kenya is above Zambia both on average exposure and on the share of tasks in the paper's high-exposure range.
Both countries still look augmentation-heavy
In both cases, augmentation-oriented exposure remains larger than substitution-oriented exposure.
The strongest signals cluster in service and support work
The top occupations and skills in both countries point toward administrative, clerical, and digitally mediated tasks rather than one narrow manufacturing story.
What to compare next
Keep the comparison moving.
The comparative diagnostics should open back out into the atlas rather than end on a single story page. These are the most useful next steps from this pair.