CompTIA research shows that 95% of South African businesses are prioritising digital fluency – the ability to confidently use digital tools, data, and emerging technologies – in IT hiring. Alongside this, World Bank highlights a demand for transferable capabilities such as communication and problem-solving.
The ability to construct meaning from data relevant to a business challenge has become as important as the ability to code the solution. Consider what this looks like in practice: a data scientist needs to understand a misleading pattern rather than simply surface it. A threat and vulnerability analyst must recognise bias in an AI-generated output before it informs a product or decision. Their insights then enable developers to build more appropriate systems.
For IT professionals, this points to an important distinction between technical proficiency and technological literacy. The ability to code, develop systems, or configure infrastructure establishes proficiency. Literacy determines how effectively professionals can interrogate the data informing their work, detect a hallucination, evaluate an output, and understand significance within a particular context.
As AI becomes embedded across the technology landscape, this distinction becomes increasingly consequential. IT graduates already know how to build the software needed to support an AI-enabled environment. What they may lack is the literacy to engage intelligently with the information, tools, and technologies surrounding this work, including the ability to question what the technology produces.
The World Economic Forum’s Future of Jobs Report 2025 reinforces the shift. Analytical thinking ranks as the most sought-after core skill among employers, while creative thinking and adaptability are also gaining importance. These are not alternatives to technical proficiency. They are the literacy that shapes proficiency into practical, implementable processes.
This broader conception of literacy also challenges the tendency to group capabilities such as communication and collaboration under the catch all label of ‘soft skills’. In technical environments, these are often essential functional capabilities. Being able to explain a complex finding, challenge an assumption, or interpret information from outside one’s immediate discipline can directly affect the quality of a technical outcome.
For employers, the challenge often lies in defining what these capabilities mean within a particular role and then finding credible ways to assess them. A generic requirement for ‘AI literacy’ tells a hiring team very little. The useful definition is the one linked to the tasks, decisions, and KPIs attached to a role.
This is where specialist IT recruiters can contribute beyond matching job specifications to CVs. An experienced recruiter understands how technical and transferable capabilities intersect across different roles and can help employers establish both proficiency and literacy requisites when defining roles. This then streamlines the process of finding and assessing suitable candidates.
And, as digital fluency becomes a more important part of technical work, the value of working with specialist recruiters is less about finding people who can code and more about finding the right combination of technical and transferable capabilities. Industry knowledge combined with market intelligence is critical for defining these requirements clearly and assessing candidates against the capabilities a role actually demands.
