Curious and ready—but not yet embedded

Workers in East Africa (EA) have two distinct strengths compared to their global counterparts: greater job optimism and higher AI exposure. However, translating these strengths into GenAI adoption and structured upskilling pathways remains a work in progress. The region’s foundations of trust, psychological safety, and clear strategic alignment offer leaders a path to accelerate readiness for this.

This year’s survey - one of the largest of its kind, with nearly 50,000 global respondents, in 48 major economies - also includes valuable regional insights. More than 200 participants from East Africa contributed their perspectives, offering an important local lens on how workers are experiencing and anticipating AI driven change.

Global context. Across PwC’s global survey, 54% of workers say that they used AI for their job in the last year, but only 14% use GenAI daily; emotions skew positive, with curiosity and excitement about AI roughly twice as prevalent as worry or confusion. In the global sample, just 53% feel strongly optimistic about the future of their role—signalling an opportunity for leaders to strengthen confidence. 

A focus on East Africa (EA):

EA workers show strong optimism and AI exposure, but usage remains uneven—signalling enthusiasm for AI’s potential rather than full integration into everyday work.

• Optimism about role: 61% of workers in EA say they’re optimistic to a large or very large extent—~8 percentage points higher than the global 53%. 
• AI exposure: 72% of workers in EA reported using AI in the last 12 months, vs 54% globally.
• Daily GenAI: 38% report daily use of GenAI tools; 28% use weekly.
• AI emotions: EA workers are far more curious (68%) and excited (53%) than worried (28%) or confused (18%) about AI’s workplace impact—mirroring the global positivity bias. 

AI outcomes (EA): Among those who used AI at work, quality (94%), productivity (87%), and creativity (78%) show strong net increases over the last 12 months—closely tracking the global pattern where frequent GenAI users report outsized performance gains. Looking forward to the next three years, workers in EA expect further gains in quality (88%) and productivity (85%), with salary (42%) and job security (45%) also trending upward.

Implication: East Africa’s workforce shows a strong readiness and willingness: they’re optimistic, engaged with AI, and increasingly seeing tangible benefits. Leaders can harness this momentum by widening access, deepening daily usage, and communicating clear role‑level impacts.

Global context. Upskilling remains uneven: globally, non‑managers are much less likely to report access to learning resources (51%) compared with senior executives (72%). And despite rising awareness, only 14% of workers use GenAI daily—an adoption gap that risks muting value creation. 

EA strengths and gaps:

Strong learning momentum and access in EA create a solid foundation, yet impact will hinge on translating skills into roles, processes, and performance as AI reshapes work.

• Learning impact: 77% say they learned new skills in the last 12 months that help their career. 
• Access to learning and development (L&D): 71% report access to the learning resources they need at work—encouraging, but uneven by role and function. Access to L&D is broadly available across levels, but softer conviction among entry level workers signals a relevance and integration gap—particularly for early career and manual/professional roles—rather than a lack of access. The platform is there; the payoff depends on shifting from generic scale to role specific learning where it matters most.
• Manager support: 66% feel supported by their manager to build new capabilities—solid, yet with room to grow. 
• Skill relevance horizon: Only 12% expect ≤50% of their skills to remain relevant in three years—suggesting that most anticipate significant skill carryover but still need targeted pathways to keep pace with AI. 

Implication: EA shows strong appetite and access—a good platform to scale GenAI literacy and agentic AI capabilities. The next step is to tighten the link between learning and real work, so newly acquired skills are embedded in roles, processes, and KPIs.

Global context: Evidence from the global report points to six motivation levers that power innovation and growth: 

1. Acknowledge uncertainty
2. Address trust gaps
3. Clarify strategy and alignment
4. Create skill pathways
5. Build psychological safety and meaning
6. Treat pay/security as core motivators 

Below are EA‑specific moves mapped to those levers. 

What EA leaders should do next

• Publish an “AI at Work” roadmap with quarterly updates, covering near‑term pilots, role changes, and redeployment pathways (attrition‑first where feasible). Transparency lifts trust—especially in functions anticipating automation.
• Scale daily GenAI use via enablement sprints: Dedicate 4–6 weeks per cohort to practice prompts, automate routine tasks, and embed outputs into process metrics (quality, turnaround, customer experience).
• Tie skills to rewards. Launch micro‑credentials and skill badges that unlock pay steps or bonuses—especially for agentic AI proficiency—so learning converts into motivation and retention.
• Strengthen psychological safety. Run monthly retrospectives, publish a rotating “failed‑but‑useful” case, and celebrate well‑run experiments. EA’s strong baseline means you can move faster on reinvention.
• Make strategy tangible. Keep EA’s high alignment by cascading long‑term goals into team‑level objectives and key results and role‑level outcomes. Refresh every quarter as AI use‑cases evolve.
• Reduce financial friction. Offer confidential, easy‑access financial wellness resources; publicise them to destigmatise uptake. Link AI skill growth to compensation to offset strain and sustain change‑readiness.

The findings across East Africa make one thing clear: the opportunity ahead isn’t just to implement AI, but to prepare people to succeed in an Intelligence Age that is already taking shape. East Africa workers are optimistic, highly exposed to AI, and eager to learn—yet motivation depends on whether they can see a future for themselves, trust leadership, work in psychologically safe environments, and feel financially supported. These factors mirror the six motivation levers highlighted in the global survey and carry even greater weight in East Africa, where daily GenAI adoption is rising, but financial strain is acute.

For leaders, the path forward is practical and urgent: clarify AI strategy, strengthen trust, build real skill pathways tied to rewards, and embed psychological safety into how teams learn and experiment. With these foundations in place, East Africa organisations can turn today’s momentum into sustained readiness—transforming uncertainty into a confident, skilled, and motivated workforce ready to power the next era of growth.