Artificial intelligence (AI) and algorithmic decision-making have reinforced data as the new currency of economic and social power.
Dhesen Ramsamy, group chief technology and data officer at Old Mutual, talks data, value, governance and citizen trust.
AI’s reliance on software, skills, and vast quantities of data places it at the heart of economic activity and makes it a critical intangible asset for companies and economies, says an analysis of the AI by the Financial Stability Board (FSB).
Data is the foundation for developing powerful AI models and deploying them at scale, and those companies with access to significant quantities of high-quality data can more effectively train their AI and gain the benefits of productivity, innovation, and market growth. While the tools for collecting, storing, and analysing data have never been more advanced, the question that remains for Africa is far more foundational – who will benefit?
The continent is not short of data. Every transaction, mobile interaction, GPS ping, healthcare visit and financial record is part of an expanding tapestry of African data. The lack is not in the volume, but in the infrastructure, regulation and awareness required to ensure the data benefits people and communities and countries on the continent. Left unchecked, Africa risks becomes rich in data that is poor in value – people and communities paying with their personal privacy while international companies harvest the rewards.
Africa’s data future must be designed by the models it builds. The applications it creates which are relevant to the local context and return value to citizens. And moving in the direction of Africa-centricity starts with reframing how data is perceived and leveraged. It is not just a byproduct of digital living, it is a co-created asset, and citizens are participants in an ecosystem which needs to be accountable as well as inclusive and fair.
Creating equitable data economies starts with education. People need to understand their rights when it comes to data creation and collection and the role they play in the data ecosystem. However, awareness is not enough, there also need to be mechanisms which hold data collectors and users to account.
This is particularly important in environments where regulation is often weak or absent. In regions lacking strong AI or data protection laws companies can provide ethical guidelines and oversight frameworks which offer structure to data and accountability, but there are risks around enforceability and oversight.
While the African Union (AU) has adopted its first Continental AI Strategy with 15 strategic recommendations to drive a unified approach to AI governance and development across the continent, there are still significant legal and institutional gaps.
These need to be addressed so the right protections are put in place to ensure algorithmic accountability and to mitigate the risk of bias.
Making this move towards cohesive regulations and transparent data practices also requires a clear commitment to uniformity. Inconsistent data classification, privacy or retention policies can erode trust before it is earned. When consistent governance frameworks are applied across regions, companies can create stability, fairness, and reliability in their data practices.
At Old Mutual’s Africa Regions business, this has meant moving beyond centralised data control and instead developing federated models of enablement. Local entities, regardless of their location, need to own their data strategy and technical capabilities are built centrally. Power is intentionally devolved so local teams are equipped to make decisions, develop talent pipelines, and build data cultures that reflect the markets they serve.
Another factor to consider is the growing opacity of AI itself. As tools become more complex, understanding how decisions are made and what data informs those decisions is increasingly challenging. This is both a technical and a moral problem.
Transparency must be engineered into systems from the start and AI products must be interrogated for their performance and provenance. This transparency requires courage, however.
Data leaders need to challenge vendors and manufacturers when systems are too opaque. And local solutions should take priority over those developed overseas. Local data, local context, and local opacity have the potential to transform both trust and accountability.
By designing for trust, companies are allowing for citizens to see what data is held, how to control its usage and feel confident it is protected. Dashboards that allow customers to view and adjust permissions, governance boards that challenge data usage and hold companies accountable, and feedback loops that inform the public when things go wrong are the building blocks of a data ecosystem where trust is earned.
At Old Mutual, data advisory boards have been introduced within key country operations and carry the authority to audit, challenge and prevent data initiatives, ensuring they are aligned with ethical and transparency standards. This is a vital approach that should be prioritised across the continent to ensure Africa’s participation in the global economy is not built on borrowed infrastructure.
As long as core compute power remains concentrated in global capitals, African data will flow outward, fuel for models and platforms built elsewhere. Initiatives that invest in local cloud, regional data centres and sovereign storage capabilities are essential. Africa does not need to play catch-up. It needs to play its own game. With the right governance, transparency and intent, the continent’s data future can be defined by equity and sovereignty.