Africa’s banking institutions are planning to ramp up their investment in artificial intelligence (AI) despite many lacking formal return on investment (ROI) measurements in place, according to a new study by Backbase.

This finding indicates that banking institutions in the region consider AI a strategic necessity but also also highlights a gap in value assessment and performance measurement.

The survey, which polled 277 senior banking executives across 37 African nations, revealed that 82% of respondents who currently lack formal ROI measurement intend to expand AI spending over the next 12 months. This underscores how executives perceive AI adoption as a business imperative driven by the fear of falling behind and the promise of improved performance. It also suggests that organizations are lacking robust frameworks to assess the financial and operational impact of these investments, which can be substantial.

In particular, the study found that the executives responsible for investment decisions are the least likely to track AI ROI. Only 50% of C-suite are measuring AI ROI, compared to 82% of finance teams, which are responsible for managing profit and loss.

This disconnect present a significant governance risk because those with the authority to allocate capital are not holding themselves accountable for measuring whether those investments deliver returns. Meanwhile, those who must manage the financial consequences are left monitoring initiatives they didn’t originate or approve.

Top challenges to AI adoption at African banks

Besides measurement gaps, the study identified several obstacles hindering the adoption of AI at African banks. These include technological limitations, data privacy concerns, and a talent shortage.

Integration with existing systems emerged as the most significant impediment to AI adoption, cited by 50.2% of all respondents. Legacy architecture also hinders the measurement of AI success, with close to 58% of respondents who do not currently measure AI ROI citing integration with legacy systems as their greatest challenge to scaling AI use internally.

After technological challenges, data privacy emerged as the second most cited internal obstacle to AI adoption, cited by 48.5% of respondents, closely followed by risk and regulatory compliance at 40.2%. The proximity of these figures suggests that the legal boundaries around data are both rigidly defined and actively enforced.

Africa’s fragmented regulatory landscape presents a unique challenge. Different African jurisdictions impose distinct mandates on how customer financial data is stored, processed, and transferred. Across the region, cross-border data flows are heavily conditional, requiring robust local adequacy assessments or sovereign data mirroring.

Finally, the third most significant internal obstacle cited by respondents at 42.3% was the lack of skilled talent. This finding aligns with other research. Gallagher’s 2026 AI Adoption and Risk Survey found that skills gaps and recruitment challenges are the primary barrier to AI implementation this year, citied by half of the businesses polled.

This year, AI skills have surpassed traditional IT and engineering to become the most sought-after capabilities globally, according to ManpowerGroup’s 2026 Talent Shortage Survey.

AI model and application development (20%) and AI literacy (19%) now lead the global ranking of hard-to-find skills, followed by engineering (19%), sales and marketing (18%), and manufacturing and production (17%). Together, these AI capabilities displace traditional IT and data skills, which fell to seventh place (17%), underscoring a realignment of strategic talent investment toward AI-driven capabilities.

Despite the talent shortage, banking executives in Africa are confident in their team’s ability to adapt. Over 56% of the respondents polled by Backbase and African Banker expressed either very or extreme confidence in their current team’s ability to meet the new demands, risks, and opportunities presented by agentic AI. For over 80% of respondents, re-skilling or upskilling their teams to adapt to these will be a top priority over the next one to two years.

The state of AI adoption in Africa’s banking sector

In Africa’s banking industry, AI adoption is steadily increasing, although most organizations are still in the early stages of implementation. According to the Backbase and African Banker study, 45.5% of respondents identified themselves as Early Adopters, and are currently implementing AI at the workflow level. Another 28% of respondents self-identified as the Early Majority and are currently piloting AI across their teams. Finally, a significant minority, 26.5%, self-identified as Innovators, who are spearheading transformative adoption at the organizational level.

The study found that while conversational AI is the most commonly adopted AI application, deployed by 49% of respondents, the one identified as most impactful is actually fraud detection and transaction monitoring. This use case also has the most directly measurable ROI, the report stresses.

The second most impactful use case for AI is credit scoring and alternative credit assessment. Though financial inclusion has improved remarkably in Africa over the past years, the credit gap remains significant.

In 2021, 49% of adults in Sub-Saharan African owned a financial account, a rate that more than doubled since 2011, according to the World Bank. However, domestic credit to the private sector stood at 29.4% of GDP in 2022. In contrast, that figure stood at 187.1% in the US, 126.1% in the UK, and 128.4% in Singapore. This highlights the low penetration of credit to African households.

Finally, conversational AI and chatbots emerged as the third most impactful AI use cases. An example of these implementations is Nedbank’s integration of Kasisto’s KAI platform and conversational AI technology to power its intelligent digital assistant Enbi. The integration allowed Nedbank, one of the four largest banking and financial services groups in South Africa, to reduce live chat volumes by more than 70% while increasing client satisfaction.

The survey revealed that among those who measure AI ROI, over 52% reported returns exceeding their expectations, while over 30% states they are broadly on target. In contrast, a minority of just under 15% claimed that AI is not meeting their projected returns. This highlights that despite early AI adoption, the technology is already delivering tangible benefits to African banks.

Featured image: Edited by Fintech News Africa, based on image by geetaroy via Magnific