By Akhona Nkalitshane, Business Development Manager, Altron Arrow
South African companies are currently in a position of having to decide whether to adopt open or closed artificial intelligence (AI) systems, a decision that goes beyond price or technical merit and includes regulatory considerations.
The risks of choosing the wrong solution are serious.
One of the biggest dangers lies in how open AI platforms handle proprietary data. Many companies opt for AI for speed and efficiency, but few stop to consider whether their implementation creates hidden risks to their most valuable asset: intellectual property.
Open AI platforms promise convenience and low costs, yet every upload of proprietary data feeds an opaque system that could be repurposed, resold, or turned against you. In trust-critical sectors like finance, healthcare, legal, and infrastructure, this isn’t just compliance – it’s a strategic threat to security and long-term resilience.
Data is not just an IT asset; it is arguably the most valuable currency an organisation holds. And when that data leaks, the cost is not measured in IT spend; it’s measured in ransom payments, regulatory fines, and irreparable reputational damage. The irony is shocking – businesses save money by using free or open AI platforms, but those “savings” are dwarfed the moment a breach occurs. The math is simple: you cannot protect what you do not own, and you cannot control what you outsource.
Serious consideration should be given to whether an open AI platform used to process sensitive customer data could potentially result in a breach of emerging compliance standards. Increasingly, laws are emerging that specify the geographic location of data, with many countries leaning towards data sovereignty. This raises critical questions around accountability, security, and the long-term risks of outsourcing data processing to external platforms.
Recently, the South African Reserve Bank announced that it would establish frameworks to regulate emerging technologies, including crypto assets, AI, data offshoring, and cloud computing. Companies need to be forward-thinking, anticipating as much regulatory change as possible, because the questions executives have are the ones that lawmakers will seek to resolve.
As these regulatory pressures mount, the local infrastructure gap that once justified open AI is also closing. Until recently, South African enterprises had a legitimate reason to use open AI. Building closed AI systems required hardware capabilities that simply weren’t available locally.
That barrier no longer exists because enterprise-grade AI infrastructure is here, making it possible for businesses to deploy closed systems that protect their data while still unlocking competitive AI advantages. With the introduction of such infrastructure and the associated software, companies can and must now develop AI models on their own terms, scaling with business needs while maintaining control over sensitive data.
In doing so, they move from dependency to control, from short-term convenience to long-term resilience. The opportunity in front of South African enterprises is unprecedented.
Owning infrastructure is not just about performance; it is about strategy. Closed AI systems force organisations to treat AI as a core business capability rather than an operational expense that doesn’t seem to deliver serious value.
Closed AI also enables companies to maintain a stronger cybersecurity posture, as it provides complete control over how data is accessed, utilised, and transmitted.
This requires more than policy; it demands knowledge and understanding of the risks associated with cybersecurity when AI is used to fast-track workflows and processes. The strongest implementations are built on layered security architectures that combine on-premises control with selective cloud integration. In this model, AI infrastructure doesn’t just automate processes; it reinforces the enterprise’s ability to withstand cyber threats while adapting to evolving digital demands.
Executives need to act by confronting three urgent questions. Can the business withstand the strategic risk of external AI platforms? Do they control their AI capabilities enough to adapt as requirements shift? And is their use of open AI platforms strengthening their competitive edge or exposing it? The answers will shape decisions that protect intellectual property, secure operations, and safeguard long-term competitiveness.
Company leaders must act now to deploy AI securely, strategically, and sustainably, using the right hardware and expertise. The next wave of competitive advantage will belong to organisations that build closed, protected AI systems – not just to innovate, but to lead. In AI, data is the most valuable asset. It’s when companies treat AI infrastructure as a fortress for that data, not a gateway of convenience, that they mitigate risk, gaining advantage by being ahead not only of competitors, but also of pending regulations. This ability to innovate and lead will become a long-term competitive strength.
