A new KPMG survey says many Africa-based chief executives are confident about their own companies while remaining cautious about the wider operating environment. The 2026 Africa CEO Outlook, released on Thursday, October 22, questioned 176 chief executives in Africa between August 11 and September 21 as part of a 1,400-person global survey. Its results are a snapshot of executive expectations, not audited company accounts or a forecast guaranteed to come true.
The report found that 79% of the Africa respondents were confident in their organisation’s growth prospects and 86% said their business had recorded revenue growth in its latest financial year. But only 58% expected average annual earnings growth of at least 2.5% over the next three years, compared with 68% in the global sample. That gap suggests confidence is being tempered by costs, financing conditions and external risks rather than translating automatically into rapid profit growth.
Confidence is high, but earnings expectations are more restrained
Cybersecurity and data security were named by 31% of the Africa respondents as a leading threat to growth, tied with supply-chain resilience. KPMG also reports that geopolitical complexity, regulation and economic uncertainty are influencing strategy. These are executives’ risk assessments; the percentages do not establish that every African market or company faces the same exposure.
Artificial intelligence is nevertheless a major spending priority. Seventy-two per cent of the Africa respondents identified AI as a leading investment priority. Yet only 14% said their organisations were keeping pace with or ahead of AI developments, compared with 66% of the global sample. The 58-percentage-point difference between the Africa respondents’ stated investment priority and their self-assessed readiness is a sign of an execution challenge, not proof that any particular AI project has failed.
Investment appetite is running ahead of AI readiness
Expected payback is also slower. Forty-eight per cent of the Africa respondents expected a return on AI investment within one to three years, while 42% expected returns only after more than three years. That makes data quality, cybersecurity, reliable infrastructure, staff capability and governance central business questions: a company can buy software quickly, but it cannot assume that useful deployment, trustworthy results and measurable returns will arrive at the same speed.
For customers, investors and regulators, the readiness gap also raises practical questions about safeguards. Organisations adopting AI need to know which data a system uses, who can challenge an automated decision, how errors are corrected and whether sensitive information is protected. The survey does not evaluate individual systems, so its aggregate figures should not be treated as an endorsement of any vendor or deployment.
The workforce findings point to restructuring rather than a simple jobs boom. Eighty-four per cent of the Africa respondents expected their organisation’s headcount to increase over the next three years, 86% planned to retain and retrain high-potential staff, and 74% said they were hiring people with AI and broader technology skills. Those intentions may create opportunities, but they are not job offers and do not guarantee hiring by a named employer.
Hiring and retraining can happen alongside selective job cuts
At the same time, KPMG says 56% anticipated reducing jobs in selected areas. The two findings can coexist if employers automate some tasks while adding different roles elsewhere. Workers should therefore read broad hiring percentages cautiously and look for first-party vacancy pages, precise locations, stated deadlines and real job descriptions before investing time or sharing personal information.
For businesses, the useful takeaway is to separate ambition from operating readiness. A credible AI plan should identify a specific business problem, the data and infrastructure required, the people responsible for oversight, the measurable benefit expected and the point at which a project should be changed or stopped. Spending alone is not evidence of productivity.
What businesses and workers can usefully take from the survey
For workers and students, the results support building transferable skills rather than chasing a single tool. Data literacy, cybersecurity awareness, sector knowledge, communication and the ability to check machine-generated work remain useful across changing platforms. Retraining promises should also be tested against actual course access, protected learning time and whether staff can move into the roles being created.
The report covers a cross-section of senior leaders across African regions, but 176 responses cannot represent every country, industry, informal business or worker on the continent. It records what CEOs said during a six-week survey window and does not independently verify revenue, investment budgets or future staffing. The strongest conclusion is therefore narrow: AI has become a central boardroom priority for many respondents, while their own answers show that capability, governance and returns are still catching up.
