Organisations across Africa are rapidly embracing artificial intelligence, but most are struggling to translate early adoption into measurable business impact, according to new research by PwC that points to widening gaps between the continent and global AI leaders.
The study found that more than 82 per cent of African organisations are already running artificial intelligence pilots or experimentation programmes. However, relatively few have succeeded in scaling the technology across their businesses in ways that generate sustained growth, operational reinvention or competitive advantage.
Chief Executive Officer of PwC Africa, Dion Shango, said the continent’s challenge is no longer simply whether companies are willing to adopt AI but whether they can implement it quickly and effectively enough to remain competitive globally.
“Africa’s challenge is both adopting AI at scale and implementing it fast enough to remain competitive,” Shango said.
He added, “While more than 82 per cent of organisations are running AI pilots, this is not yet translating into enterprise-wide impact.
The organisations that will win are not those running the most pilots but those that scale the right AI to transform how they create value.”
The research surveyed 1,217 senior executives across 25 sectors in Africa, Asia, Europe, the Middle East, North America and South America. Most respondents were director-level executives or higher from publicly listed companies with annual revenues exceeding $1bn.
According to the report, many African organisations continue to treat AI as a collection of isolated experiments rather than embedding it into core operations, customer systems and long-term growth strategies.
PwC warned that while experimentation helps companies build familiarity with emerging technologies, pilot-heavy approaches often fail to deliver transformation unless supported by stronger governance frameworks, infrastructure investment and organisational redesign.
The report found that most early AI gains in Africa remain concentrated around efficiency improvements, automation and cost reduction.
Consulting and Risk Services Leader at PwC West Market, Olufemi Osinubi, said African companies risk limiting the value of AI if they focus solely on operational efficiency rather than growth.
“Focusing AI only on efficiency is a narrowing strategy,” Osinubi said. “The real opportunity lies in using AI to unlock growth, expand into underserved markets, and create entirely new business models.”
PwC also identified industry convergence as one of Africa’s most underutilised opportunities in artificial intelligence deployment.
Compared with global peers, organisations across the continent are less likely to collaborate across industries to create digital ecosystems spanning sectors such as healthcare, agriculture, financial services, logistics and energy.
Chief AI officer at PwC Nigeria, Christopher Ogirri, said Africa’s structural challenges could create favourable conditions for cross-sector AI collaboration if businesses adopt ecosystem-driven approaches.
“Africa’s structural complexity, fragmented markets, infrastructure gaps, and a growing youth population position it well for AI-enabled convergence, if organisations design for ecosystems rather than sectors,” Ogirri said.
Many of Africa’s most pressing economic problems, including financial inclusion, healthcare access, agricultural productivity and energy distribution, cut across multiple industries and institutions.
According to PwC, artificial intelligence offers an opportunity to address such interconnected challenges more effectively, although ecosystem-based adoption remains limited.
The report also identified foundational weaknesses as a major obstacle preventing organisations from scaling AI deployments.
Scaling artificial intelligence effectively requires trusted datasets, modern cloud infrastructure, governance systems and access to specialised technical talent areas where many African organisations continue to face significant gaps.
Only 32 per cent of organisations surveyed said they believed their AI investment levels were sufficient to support long-term competitiveness.
Africa Cloud and Digital Leader at PwC South Africa, Mark Allderman, said gaps in cloud adoption, data modernisation and investment continue to limit enterprise-wide AI deployment.
The report nevertheless identified workforce readiness as one of Africa’s strongest advantages in artificial intelligence adoption.
According to PwC’s findings, 64 per cent of workers surveyed across the continent are already using artificial intelligence tools within their roles, reflecting growing openness to AI adoption among employees.
Partner for technology consulting at PwC Kenya, Laolu Akindele, stated employees in many organisations appear more prepared for AI integration than leadership teams.
“The workforce is ahead of the organisation in many cases,” Akindele said. “Employees are ready to use AI, but leaders are still building trust in AI-driven decisions. Bridging that gap is critical to scaling adoption.”
The findings come as companies globally accelerate investments in generative AI, automation and digital transformation amid concerns that businesses slow to adapt could lose competitiveness over the next decade.
Across Africa, however, organisations continue to face challenges, including unreliable infrastructure, limited computing resources, fragmented regulatory systems and shortages of specialised AI talent.
PwC warned that unless African businesses move rapidly from experimentation to execution, the gap between the continent and global AI leaders could widen significantly.
The consultancy urged organisations to prioritise growth-oriented AI use cases, strengthen digital infrastructure, modernise data systems and invest more aggressively in workforce development and governance frameworks.
AI Africa leader at PwC South Africa, Christiaan Nel, noted that turning AI ambition into measurable business impact would require more disciplined investment and stronger strategic focus.
“Turning AI ambition into measurable impact requires focus and discipline,” Nel said. “Leaders must invest with intent, prioritise growth, and create the conditions for AI to scale, combining strong foundations with workforce readiness and ecosystem thinking.”
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