72% of African CEOs Prioritise AI, but Only 10% in West Africa Feel Ready

Seventy-two percent of African chief executives rank artificial intelligence as a top investment priority, yet only 10 percent of CEOs in West Africa believe their organisations are keeping pace with AI developments. That gap — between intent and readiness — is the central finding of the 2026 KPMG Africa CEO Outlook, and it frames the practical problem facing product and technology leaders across the continent: money is flowing into AI pilots faster than the data foundations and workforce skills needed to make them pay off.

The readiness figure splits sharply by region. In Southern Africa, 20 percent of CEOs say their organisations are keeping up with AI developments — double the West African figure. The report describes companies struggling to move beyond pilot projects and embed the technology into daily operations.

What separates African CEOs from their global peers?

African chief executives trail global counterparts on both ambition and payback expectations:

• 72 percent of African CEOs call AI a top investment priority, versus 79 percent globally.
• 48 percent of African CEOs expect returns on AI investments within one to three years, compared with 71 percent globally.

The report attributes this disparity to the economic pressures and operational constraints businesses face across the continent. Confidence, however, remains high: 79 percent of surveyed CEOs expressed confidence in their companies' growth prospects, 72 percent were optimistic about their domestic economies, and 86 percent recorded revenue growth in their most recent financial year.

Shamit Govind, AI Lead at KPMG One Africa, argues that confidence and investment intentions alone will not secure long-term growth unless businesses translate technology adoption into practical results.

Where does execution break down?

Data readiness is the biggest obstacle. Roughly 60 percent of business leaders in West and East Africa identified it as a challenge. The specific failures span poor data quality, limited data access, weak governance and difficulty integrating information across systems. These weaknesses directly undermine the reliability of AI applications — a model built on fragmented, ungoverned data produces unreliable output, regardless of the sophistication of the tool.

The report's prescription is concrete: move from experimentation to practical deployment, with each AI project tied to a defined business objective. Named candidates include reducing operating costs, improving customer service, strengthening cybersecurity and making supply chains more efficient. Companies must also build the systems for collecting, storing and using data, and design operating models that let AI support core business activities rather than sit alongside them.

Workforce capacity is the second failure mode. Employees need the skills and confidence to work alongside AI systems, and managers must guide staff through changes to processes and responsibilities. Without investment in people, the report warns, companies risk adopting technology that never integrates into operations.

What positions a company to succeed?

Govind sees significant opportunity for West African businesses specifically, citing the region's expanding digital infrastructure, entrepreneurial activity and growing interest in technology-driven solutions. He argues that organisations which strengthen data foundations, develop workforce capabilities and establish effective governance frameworks will be better placed to move beyond AI trials and generate sustainable business value.

The tradeoff is stark. The conditions under which AI investment converts into returns — clean integrated data, defined business objectives per project, staff equipped to work with the systems — are precisely the conditions the majority of surveyed African companies lack. For product managers on the continent, the report reads as a sequencing instruction: fix the data layer and the skills base before scaling pilots, or the 72 percent investment priority produces pilots that never reach production.

As AI spending rises across Africa, KPMG's findings point to a shift in how success gets measured — less on projects launched, more on measurable impact on productivity, efficiency and competitiveness.