Three years after artificial intelligence (AI) entered the mainstream, companies are still trying to ready their systems to use the technology, says the head of NTT Data (formerly Dimension Data), one of South Africa’s largest information technology (IT) firms. Companies worldwide have felt the pressure to capitalise on the trend by employing AI-backed services or software platforms to either improve their own operations or create products. According to Amantha Naidoo, NTT Data’s managing executive for South Africa, IT spend continues to be driven by companies preparing for AI and cybersecurity.
Many corporates struggle with deeply embedded legacy architectures and undocumented source code, making it difficult to get data AI-ready. The rapid pace of emerging tech is also widening the gap between available talent and industry needs. “We are in this dichotomy: as we modernise infrastructure, the ‘new and shiny’ keeps coming to our doorstep — generative AI and [now] agentic AI in 2025.
The net result is that sometimes the focus isn’t on getting the foundational capabilities right,” Naidoo told Business Day in an interview. The executive, in her role since May, is referring to the fact that much of the foundational work that would have made many organisations ready for the advent of AI was meant to have been done over the past decade, driven by cloud computing. The net result is that sometimes the focus isn’t on getting the foundational capabilities right.
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While, computing was mainly done by an organisation’s machines on premises in the past, Amazon, Google and Microsoft’s promise of “the cloud” was access to greater processing and storage without the capital expenditure. Doing so also meant digitising records, data, process flows and other information so businesses could take advantage of the data analytics capabilities enabled by cloud computing. However, despite the hype and apparent investment at the time, many of these “cloud migrations” and related projects remain incomplete, thus creating a knock-on effect since AI builds on that foundation.
In essence, leadership often becomes distracted by the new and shiny, failing to stay the course on long-term modernisation journeys. As such, Naidoo said there is a strong trend toward modernising legacy enterprise resource planning (ERP) backbones to ensure they are “future-fit” for AI integration.
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