By Ria Pinto, GM and Technology Leader, IBM South Africa

According to PwC’s 28th annual global CEO study, AI is expected to contribute 14% to global GDP ($15.7 trillion) by 2030. In South Africa, the interest in AI has surged over the years, and major corporations, businesses and individuals alike are all beginning to recognize the technologies potential to enhance productivity, improve customer experiences, and drive growth. According to IBM’s Institute for Business Value CDOs study, 77% of MEA chief data offices (CDOs) surveyed prioritize investments that accelerate AI capabilities, initiatives, roadmap and infrastructure. This is a 55% leap from 2023, where only 25% were confident that their data could support new AI-enabled revenue streams.

As AI rapidly becomes a core driver of global economies and competitiveness, the question is no longer whether companies should adopt AI, but how they can do it productively, responsibly, and at scale.

Today, as organizations accelerate their adoption of generative AI, a new imperative is emerging. That is, AI for Business - the disciplined, enterprise-grade application of AI that transforms workflows and unlocks measurable economic value.

Fragmentation, not capability, is the real barrier

Across African markets, organizations face the same pattern: siloed pilots, duplicated AI efforts across departments, and disconnected data estates. 67% CDOs have made significant strides in integrating data strategy with technology planning, yet only 28% feel their data is ready to support AI-driven revenue. This AI-readiness gap is especially visible in South Africa, where legacy systems, inconsistent data standards, and limited governance continue to impede scale.

This is precisely why the move toward AI for Business has become essential. It emphasises not experimentation but integration, bringing together data, governance, and workflows into a unified architecture capable of scaling across departments and generating measurable impact.

Trust and transparency remain critical. Highly regulated industries such as banking, insurance, telecommunications, and public services cannot fully utilise AI without clear insight into how models are trained and the data used. As a result, the lack of transparent and governed data is slowing down responsible deployment. With only 1% of enterprise data currently residing within large language models, organizations are barely beginning to unlock the insight potential contained in the remaining 99%.

How leading African companies are scaling AI

Enterprises achieving the strongest returns in Africa are those applying AI to core workflows, customer service, claims processing, HR, financial operations, and supply chain. Instead of centralising all data, 75% of MEA CDOs are now bringing AI to the data, enabling faster deployment and more secure handling of sensitive information.

The CDO role is also evolving rapidly. 99% of leaders say business outcomes, not technology outputs, define their success. However, 27% believe they can clearly demonstrate data’s influence on business results. This underscores the growing need for measurable value frameworks, improved talent pipelines, and stronger organizational data cultures. Skills remain a challenge. 79% of MEA CDOs cite advanced data skills as one of their biggest constraints.

AI is shifting from tool to teammate

As agentic AI becomes more mainstream, its impact will be deeper and more transformative than previous AI waves. AI agents capable of reasoning, planning, and acting autonomously will reshape how African enterprises operate. The IBM CDO Study shows overwhelming confidence in their potential, with 75% of MEA leaders believing the benefits outweigh the risks, and 70% comfortable with relying on AI-driven outcomes.

IBM’s Client Zero: Demonstrating AI at scale

IBM has already experienced what effective AI for Business is internally. By deploying watsonx across HR, software development, IT operations, and other enterprise workflows, IBM has saved 3.9 million employee hours in just one year. AskHR now manages 94% of IBM’s HR queries, and Project Bob has boosted developer productivity by 45%.

This transformation is not theoretical, it is the same blueprint being implemented with clients across South Africa and the continent, proving that AI can scale responsibly and deliver meaningful results. IBM defines a transformation strategy and vision: “IBM as Client Zero”.

AI’s economic value for South Africa and the continent

AI has the potential to unlock up to $4.4 trillion globally each year. For South Africa, this value lies in modernizing key industries, including financial services, manufacturing, agriculture, telecommunications, and mining, while driving new efficiencies across public services.

African business leaders are already recognizing clear returns. 78% leaders have reported that AI is improving productivity today, nearly half expect ROI within a year, and 93% expect AI agents to deliver measurable value within a year.

Open Source: Fueling Africa’s innovation future

Open-source innovation is foundational to Africa’s AI trajectory. Closed models restrict access and limit transparency, while open models empower local ecosystems to customise, innovate, and scale solutions on their own terms. IBM’s decision to open-source the Granite model family, launch InstructLab with Red Hat, and co-establish the AI Alliance is creating more equitable access to powerful AI technologies.

For African developers, startups, and public institutions, open-source AI offers a pathway to sovereignty, transparency, and long-term sustainability.

AI is no longer an emerging technology; it is a defining economic force reshaping industries and national competitiveness. For South Africa, the real opportunity lies not in scattered experimentation, but in adopting AI for Business with discipline, trust, and measurable outcomes at the core. This means modernising data foundations, closing the skills gap, and embedding AI directly into the workflows that drive economic value.

With 99% of enterprise data still untouched, the scale of opportunity remains vast. Will South Africa unlock it to shape its own AI future?