How can South African organisations fast-track their AI initiatives?

Issue 2 2025 AI & Data Analytics, Security Services & Risk Management


Michael Langeveld.

Early adopters of cloud computing were, for the most part, driven by its potential. Promising scalability, cost savings, security and flexibility, many South African businesses moved to the public cloud hoping to access a better way to manage their IT resources and enable innovation. Because these businesses were navigating unchartered IT territory, they often lacked a clear game plan to realise the true promise of cloud.

Even now, though cloud technology has evolved significantly and is currently being used across most industries, many organisations still find themselves needing to relook and fine-tune their cloud strategies.

Fast-forward to 2025, and we are seeing a similar progression with the incredible rise in attention around artificial intelligence (AI) and generative AI (GenAI) in particular. While the AI market in South Africa is anticipated to grow by nearly 30% annually over the next five years, according to Statista, culminating in a market volume of $4 billion by 2030, tapping into the promise and potential of AI is not easy.

As HPE executive vice president Neil MacDonald noted before, there are multiple reasons why AI proof of concepts (POCs) bear little fruit. A failure to address real-world business needs is one of them. Other stumbling blocks, according to MacDonald, include prohibitive costs, data challenges and misaligned goals. As was the case in the early days of cloud, if businesses are making AI investment without a clear goal and strategy in place, it is not terribly surprising that their pilots never make it into production.

At the same time, a 2024 report from PwC found that the majority of South African CEOs recognise the benefits that a tool like GenAI can bring to their business, with some 63% fully expecting it to affect how they deliver value (https://tinyurl.com/yedy4a7s).

So how can businesses make sure that they get this right? The first step is ensuring that all relevant stakeholders within the organisation work together to define what their GenAI future looks like and how they will get there. Here are three key questions you need to answer before embarking on any AI initiatives.

1. Are you an AI enabler or an AI disruptor?

In the future, every company that hopes to remain competitive will be an AI-savvy company. The question is, what kind?

For most enterprises, it boils down to a choice between two options. You can be an AI-enabled enterprise, or you can be an AI disruptor. Until now, a disproportionate amount of public attention has been focused on the disruptors – the organisations that are spending billions to develop their own large language models (LLMs).

In reality, these organisations represent a fraction of companies working with GenAI today. The vast majority of organisations do not have the resources or the expertise to be disruptive at an industry or market level. Most are simply looking to take existing LLMs and augment them with their own unique enterprise data. A few more ambitious organisations will be looking to use GenAI to disrupt their internal operating models or re-engineer how they deliver goods and services. The more data-driven the organisation, the greater the impact this technology will have on how it operates.

At this stage of the game, a lot of corporate interest in GenAI is driven by fear of missing out. Companies do not know exactly what advantages they will gain by deploying GenAI, but they are afraid their competitors will figure it out before they do. Deciding what kind of AI company you want to be, and the kinds of benefits you hope to gain from this technology, is the first step toward moving from experimentation to execution.

2. What problems can AI solve for you?

Next, you will need to tackle the following questions: What are the most pressing problems your business is facing today? Where can GenAI have the greatest impact in solving them? Only after determining what use cases you want to address with AI should you move on to technical questions: Does your company have enough clean data for GenAI to produce actionable insights for the use cases you have identified? Do you have sufficient guardrails in place to protect against bias, misuse of intellectual property, or data leaks? And do you have the necessary technology assets in place to make your GenAI dreams a reality?

Despite high adoption rates of AI, successfully completing AI projects remains a challenge for South African businesses. Companies have a wealth of data, but they have struggled to unlock its full potential. It is about turning that mountain of data into actionable insights that drive real change.

3. Where should you start when building your AI ecosystem?

That brings us to the third big challenge: How do you pick the right partners to fast-track your GenAI initiatives? The easy answer is to look for those with an AI-first mentality. Does the provider offer AI-embedded outcomes in their offerings? Do these help your organisation operate in a leaner and more cost-effective way?

Working with vendors that offer AI tools in a standardised and pre-integrated way will allow IT teams to bring GenAI workflows into production more quickly, without having to build everything themselves or figure out which tools work best together. Especially for organisations with no AI experience, finding the right partners will be a key step, be it to pick the appropriate model, implement quality data pipelines, or deploy applications on the right platforms.

Are you ready to take the next leap forward?

As enterprises experiment with GenAI, they are gaining valuable experience about what works and what does not, as well as where they need better data or improved governance. They are also figuring out which use cases can truly drive the company forward and how to minimise risk while maximising value.

However, to be able to enjoy the enormous productivity gains that come with using these technologies, they need to prioritise strategic and well-planned deployments.




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