Artificial intelligence speeds up code generation for tech teams.
South Africa’s tech teams have reached near-universal artificial intelligence (AI) adoption, with 97% of tech team leaders reporting that their teams are already using AI tools in their workflows.
While adoption is high, the actual impact of AI remains uneven — shaped by leadership alignment, process maturity, and how teams measure success.
This is according to OfferZen’s Engineering Leadership Report 2025, which surveyed 331 tech leaders across various company sizes and sectors.
According to the report, an overwhelming majority of participating tech leaders say their IT teams are using AI in some capacity. This suggests that almost every software team in the country is experimenting with or integrating AI — from coding assistants to internal tools.
But immediate benefits aren’t automatic, the study cautions. While many leaders credit AI with faster code delivery, they warn that it can also shift bottlenecks “downstream”, requiring stronger systems, clearer processes and careful coordination to prevent quality loss or technical debt.
When used thoughtfully, AI can amplify engineers’ productivity and allow them to focus on higher-impact work — not repetitive minutiae, the study points out.
“For South African companies, the message is clear: integrating AI isn’t optional. But doing it well requires more than buying seats on a tool — it demands thoughtful leadership, culture, and people who know how to combine human judgment with AI speed,” notes the report.
“In contrast, teams with weak communication, unclear process or poor context are more likely to find AI exacerbates existing problems rather than solves them.”
The report reveals a clear perception gap inside organisations. While tech teams are already using AI tools in their work processes, 55% of tech leaders say AI’s current capabilities are overhyped, the strongest scepticism comes from executives.
Some 60% of executives believe AI is overhyped. This drops to 51% of team leads and 48% of mid-level managers.
“Executives are more cautious because they carry the burden of risk, governance and audit exposure. Many have been burned by hype cycles before and are wary of investing heavily in tools that may fail to deliver promised returns,” notes the report.
In contrast, most mid-level managers are seeing direct day-to-day value from deploying AI: faster debugging, cleaner documentation and shorter shipping times. Their challenge is communicating these wins upwards to the exec teams to close the expectation gap, states the study.
When measured purely on speed, AI is already delivering meaningful gains. Of leaders, 58% say AI has increased the speed at which their teams ship software, while only 17% report no improvement.
But when measuring quality, the picture shifts:
- 42% say AI has not increased code quality
- Only 33% report quality improvements.
The report adds that while AI speeds up code generation, the same can not be said for the processes surrounding it — such as testing, code review, documentation and auditing — which still take the same amounts of time as before.
OfferZen engineering manager Jason Tame, says this is where leadership becomes critical. Tech leaders must redesign delivery systems so AI improves the entire value chain, not just coding velocity, he notes.
“AI acts as an amplifier – it magnifies organisational strengths and exposes dysfunctions. By working in small batches, implementing robust CI/CD practices, enforcing strict static analysis and maintaining disciplined automated testing, teams will be able to ship quickly with AI assistance without compromising quality.”
