The takeaways
African business leaders have learned to make strategic decisions under constraints. Capital constraints, infrastructure gaps, skills scarcity, currency volatility, and the need to protect fragile operating performance have made building resilience a business imperative. As AI reshapes competition, companies with higher AI fitness are realising outsized returns, which may widen the gap in market leadership and profitability over time. In today’s business environment, African CEOs cannot afford to let constraints slow reinvention, as delay may limit their ability to compete for emerging sources of growth.
PwC’s AI performance study shows the companies seeing the biggest returns from AI are not simply chasing improved productivity or cost savings. They are making bold decisions, using AI to drive growth and new value creation. The study surveyed 1,217 large companies globally, including 85 in Africa, and found that the top 20% capture 74% of AI-driven financial returns. The highest performers do three things consistently: they aim AI at growth and reinvention, build fit-for-purpose foundations, and embed AI across the enterprise.
Average AI Fitness Index score by region, out of 10
- Source: PwC's AI performance study.
Africa’s AI Fitness Index sits at the global median, yet the region trails AI leaders across every major dimension of AI-driven performance. This gap suggests that the challenge is not adoption, but execution at scale. The opportunity for the region is not to do more AI. It is to scale the right AI, deliberately and decisively.
PwC’s AI performance study shows that organisations generating ROI from AI make a distinct set of strategic choices. For business leaders in Africa, the opportunity now is to apply these lessons.
Current reality in Africa: Many organisations are realising early AI value in productivity and cost savings.
What leaders should do: Use AI to drive revenue, new business models and market expansion; not only cost reduction. In Africa this includes reaching underserved markets, reworking value chains and targeting emerging growth areas.
Current reality in Africa: High participation in AI pilots has not been translated to enterprise-wide scaling.
What leaders should do: Concentrate investment on a limited number of high value use cases, track business impact and scale proven solutions across the enterprise rather than running disconnected pilots.
Current reality in Africa: AI investment levels remain below AI leaders and many organisations report investment constraints.
What leaders should do: Leading organisations invest more in AI but do so with discipline, reallocating resources toward higher-value opportunities and funding long term returns even when short term ROI is unclear.
Current reality in Africa: Gaps remain in data and technology readiness, workforce capability and investment sufficiency.
What leaders should do: Upgrade data, technology and operating capabilities specifically to support priority AI use cases instead of pursuing wide transformation programmes without clear focus.
Current reality in Africa: Governance maturity remains uneven and many organisations lack formal Responsible AI structures.
What leaders should do: Apply governance risk and trust frameworks to build confidence in AI driven decisions, reduce friction and enable faster, safer scaling.
Current reality in Africa: Workforce participation in AI is rising, but trust in AI-driven decision making remains below AI leaders.
What leaders should do: Invest in skills, role redesign and decision support to convert workforce openness to AI into adoption trust and measurable business impact.
Current reality in Africa: Organisations in Africa are less likely than AI leaders to use AI for sector convergence.
What leaders should do: Use AI to address cross industry challenges, build ecosystem partnerships, and capture shifting value pools that sit across traditional sector boundaries.
of CEOs who have invested in AI reported revenue increases, while 25% reported cost reductions over the past year.
Africa’s organisations are not lacking in ambition for AI. Across PwC’s research, the intent is visible in CEO optimism, workforce readiness to adopt AI, and the growing use of AI for revenue, trust and productivity.
Yet ambition is not translating into ROI from AI at the pace seen among global AI leaders. Many organisations remain in pilot mode, move cautiously on reinventing their business models and underinvest in the capabilities required to scale.
The organisations generating the highest returns are not experimenting with AI at the margins. They are using it to drive revenue, reinvent business models and reshape how value is created. In PwC’s AI performance study, the most AI-fit companies generate 7.2 times greater AI-driven performance than others. These leaders also scale selectively, building only the capabilities needed to deliver on their objectives, avoiding broad, unguided transformations.
The decision facing CEOs in Africa is whether to continue treating AI as a set of experiments—or to treat it as an engine of growth and reinvention. There is a sharp fork in the road: Use AI to defend today’s margins, or to shape tomorrow’s markets.
Africa’s organisations are not lacking in ambition for AI. Across PwC’s research, the intent is visible in CEO optimism, workforce readiness to adopt AI, and the growing use of AI for revenue, trust and productivity.
Download the full report to confidently navigate the sharp fork in the road: Use AI to defend today’s margins, or to shape tomorrow’s markets.
PwC’s AI performance study gathered survey responses from 1,217 senior executives—all director-level or above—primarily from publicly listed companies (91% of the sample) with US$1 billion or more in revenue (76% of the sample) in 25 sectors across Africa, Asia, Europe, the Middle East, North America, and South America. Fieldwork was conducted in late July 2025, concluding in early September of the same year.
We analysed the companies’ AI-driven performance, defined as the revenue and efficiency/cost gains derived from AI and adjusted so each company was compared against its industry’s median. We then tested the effect of 60 areas of management and investment practice on AI-driven performance. We grouped these practices into nine factors across two categories: AI foundations (the capabilities that make AI reliable and scalable) and AI use (how broadly, deeply, and sophisticatedly AI is applied, and whether it is pointed at growth opportunities). These categories make up our AI fitness index—their sum equates to the AI fitness index score.
Percentages shown in charts may not add up to 100% due to rounding, multi-select response formats, and the exclusion of certain categories (e.g. “Other,” “Not applicable,” “Don’t know”).
Consulting & Risk Services Leader, PwC Nigeria
Director | Africa AI Leader, PwC South Africa
PwC's Africa Cloud and Digital Leader, PwC South Africa
Partner | Technology Leader, PwC Kenya
Chief AI Officer, PwC Nigeria
Findings highlight themes such as AI adoption in Africa, evolving workforce priorities and career intentions, skills relevance, job security, and the employee experience. This year’s report translates these perspectives into actionable strategies for leaders, emphasising transformation in the African workforce.
Africa's business leaders demonstrate striking optimism forged through years of navigating currency fluctuations, political uncertainty, and infrastructure challenges.