Changing the AI narrative from confusion to clarity

Artificial intelligence has become the corporate obsession of 2025. From the explosion of ChatGPT to the everyday integration of tools like Microsoft Copilot, companies echo with conversations about how AI is a competitive advantage or how it will improve productivity and customer experiences. According to Gartner,  79% of companies perceive AI as an essential part of their success story over the next two years and yet…only 20% are using it every day[1].

It proves an ongoing point – enthusiasm isn’t the same as adoption. Companies are stalling at the starting line because they’re caught between the fear of falling behind and the confusion of how to begin. And they do need to begin because AI is stretching into every part of the business, from chatbots to email to documents to solutions.

The global AI market is forecast to reach $407 billion by the end of 2027 at a compound annual growth rate, says MarketsandMarkets, of 36.2%[2]. It is adding value to multiple layers within the business that include workflows, robotics, IoT, back-office functionalities and customer experiences. Despite these numbers, uptake remains uneven, and in South Africa many companies are wary of pouring money into ambitious AI projects that may be out-innovated within the year, or that do not have a clear return. Companies are concerned that their data isn’t ready, their teams don’t have the right skills, and what governance models they need to keep them compliant.

There are three themes that are emerging in most conversations about AI. The first is the cost and the uncertainty of ROI. AI is perceived as expensive, requiring vast data lakes and infrastructure before results are possible. This misconception prevents leaders from experimenting with AI in smaller and more practical ways, particularly in areas of the business that could benefit from incremental AI innovation.

Of course, the concerns around data lakes and infrastructure come with worries about data quality. Without clean and reliable data, AI deployments run the risk of failing before they start and companies often underestimate just how much preparation is needed to build strong data foundations. Then, wedded to the data, is security and governance. Leaders are legitimately cautious about where their data has to go and want to feel confident about how it is used and where it is stored.

These three challenges combined are leading to AI paralysis – companies know they can’t ignore AI but they don’t know how to move forward without risking wasted spend or making regulatory missteps. Part of the issue is the speed at which AI is changing. Every month, new tools and models appear, and each one out innovates the other. Analyst firm IDC has characterised the AI ecosystem as ‘simultaneously maturing and fragmenting’ because while tools are advancing rapidly, they are also multiplying which makes it hard for companies to choose the solutions best suited to their needs. Will the solutions be the same in a year’s time? Will they even be relevant?

Microsoft Copilot has done an excellent job of breaking the ice, making AI feel more accessible and relevant by embedding it into tools people use every day. However, workplace productivity is only one part of the AI opportunity – it goes beyond drafting emails or summarising meetings. It can reimagine your business processes.

So, for companies to effectively sidestep these challenges and extract value from AI, they need a strategy. Success comes down to the model you choose and how you align the technology to your very real business problems. Clarity has become the most valuable AI commodity of all because you don’t want another pitch about why AI matters, you want a way to move away from enthusiasm towards execution. And that means starting small and tying your projects directly to strategy so your skills, data, security and governance are built in from the outset.

Braintree works with companies to assess their readiness and identify the first workloads that will deliver genuine, measurable value and give them a clear path forward. Not every company will be ready on day one, and that’s okay because when you can work with a partner that understands your unique environment and concerns, you can benefit from AI incrementally and intelligently. Braintree’s Azure AI Jumpstart programme is a structured readiness programme designed to help companies take the first practical steps towards AI so you can completely avoid paralysis or being left behind.

Chris Badenhorst, Head of Azure Core, Data and AI Services at Braintree.

BUSINESS REPORT