South African organisations are showing strong enthusiasm for artificial intelligence, but the rush to adopt AI risks overlooking a more fundamental question: are businesses actually ready to use it effectively?
“In a high-pressure market with lighting-fast technological change leaders need to ask, ‘What exactly do we need to do – what business challenges are we trying to solve?’” says Thandisizwe Kopolo, Managing Director, Intellehub. “The better question is, ‘Is our business ready for AI?’ Once you answer that properly, you can make much better decisions about what technology you actually need.”
But becoming an AI-enabled organisation involves considerably more than buying an AI platform or introducing generative AI tools into the workplace. The organisations most likely to realise meaningful and sustainable value from AI will be those that first put the right foundations in place.
“AI is getting a lot of attention, and rightly so, but there’s a danger of confusing adoption with readiness,” says Kopolo. “You can buy the most sophisticated AI technology available, but if your data is fragmented, your infrastructure can’t support it, your processes aren’t designed for it and your governance and security aren’t ready, you will fail,” he says bluntly.
AI readiness starts with the foundations
AI depends on the quality of the environment in which it operates. It will be constrained to the limits of the weakest piece of underlying technology infrastructure. Organisations need reliable, accessible and well-governed data; infrastructure capable of supporting increasingly demanding workloads; robust cybersecurity; clear governance and compliance frameworks; efficient business processes; and people with the skills to work effectively alongside AI. These are the crucial interconnected elements of an organisation’s ability to adopt AI responsibly and at scale.
Poor-quality or inaccessible data, for example, can undermine AI outputs regardless of how sophisticated the underlying model is. Inadequate infrastructure can constrain performance and scalability, while weak governance can create regulatory, security and reputational risks. Equally, deploying AI into inefficient or poorly understood processes can simply automate existing problems rather than solve them.
“AI doesn’t fix a broken foundation,” says Kopolo. “In many cases, it exposes one. That’s why organisations need to look at the whole operating environment before they start asking which AI tools they should buy.”
From technology deployment to organisational readiness
This is where Intellehub’s Design → Build → Operate approach provides a practical framework for organisations preparing for an AI-enabled future.
Rather than treating AI as another technology deployment, Intellehub works across the underlying environment required to make technology deliver business value. Its Design → Build → Operate model brings together the planning and architecture, physical and technological implementation, and ongoing management and optimisation needed to create a sustainable technology environment.
The approach enables organisations to assess their existing environment, identify gaps and establish the infrastructure and operational capabilities required to support new technologies such as AI.
“AI readiness isn’t a single project with a go-live date,” says Kopolo. “It’s an organisational capability. Our Design → Build → Operate approach takes a holistic view of what an organisation needs to adopt AI successfully, from business process reengineering and workforce training to infrastructure, cybersecurity, data and technology. It’s about creating the environment, capabilities and skills in which AI – and other emerging technologies – can actually work for the business, rather than simply adding another piece of technology to an already complicated environment.”
Making AI a business capability
For organisations considering AI adoption, the priority should therefore be to establish a clear baseline of readiness. This means understanding where data resides and how it is managed, whether infrastructure can scale, how cybersecurity and governance need to evolve, which processes are suitable for AI augmentation or automation, and whether employees have the skills required to use the technology effectively. The objective isn’t to delay AI adoption. It is to make that adoption more effective.
South Africa has no shortage of interest in AI. The challenge lies in ensuring that enthusiasm is matched by the infrastructure, processes, governance and skills needed to turn pilot AI projects into measurable business outcomes.
