In 2025, many South African firms moved past the initial fascination with artificial intelligence (AI) towards real deployment: nearly all major players now have AI strategies and many report measurable benefits from early initiatives.
Yet beneath the surface enthusiasm lies a far deeper and more difficult transition − one that goes beyond adoption to dependency.
The critical question for 2026 is not whether organisations embrace AI, but how they will manage reliance on AI systems for core decision-making, risk management, talent flows and strategic planning without weakening organisational judgement, resilience and autonomy.
From adoption to unseen operational reliance
South African firms are no longer simply experimenting with AI. A 2025 industry snapshot shows that more than 92% of local businesses view AI as integral to their corporate strategy, and a majority are already experimenting with tangible use cases across functions such as efficiency, customer service and back-office processing.
Decisions formerly made by experienced professionals are now sponsored by algorithmic recommendations.
But here lies a crucial shift: adoption is a choice; dependency is a constraint. In 2025, many organisations reached the point where AI tools weren’t just augmenting work − they were increasingly shaping it. Employees now regularly use AI in their day-to-day roles, yet a minority of workplaces have even basic governance frameworks in place.
This asymmetry − heavy use without robust policies − results in an emerging form of operational lock-in where organisations adjust their processes and expectations around AI outputs, willingly or otherwise.
Risks of unexamined operational lock-in
Dependency leads to subtle and often invisible pressures. Decisions formerly made by experienced professionals are now sponsored by algorithmic recommendations. Models that were supposed to speed up routine work are creeping into risk flags, performance assessments, supply-chain decisions and even strategic forecasting.
Once these systems outperform humans on speed or volume, it becomes tempting − and then habitual − to lean on them, even when the context demands human judgement.
The global picture offers stark warnings. Forecasts for 2026 suggest that more than half of AI initiatives worldwide risk failing not because of technology, but because of inadequate data practices, weak governance and misaligned incentives.
What happens when a system on which critical decisions depend fails, degrades or is miscalibrated? Dependency turns a tool into a risk vector − one that organisations are ill-prepared to manage.
This is not abstract theory. Research on AI trust and uptake reveals that although many employees use AI regularly, trust and understanding lag behind usage. Without trust and comprehension, over-reliance becomes commonplace − a dangerous mixture for organisations whose survival hinges on resilient judgement, not just fast outputs.
SA’s unique dependency dynamics
South Africa faces unique pressures that amplify dependency risks. Local organisations operate in environments marked by skills shortages, infrastructural constraints and competitive pressures that incentivise rapid technological shortcuts.
While initiatives like commitments to train one million South Africans in AI and related skills will bear fruit from 2026, they will not magically fill the strategic gap between having tools and understanding how to govern them responsibly at scale.
As local data centre capacity expands − with projections showing multibillion-rand growth over the coming years − the underlying infrastructure will encourage more AI workloads to be hosted domestically.
The risk here is not only technical dependency but ecosystem dependency: as organisations internalise AI production and consumption, external dependencies on global vendors, cloud services and opaque models will deepen − often without commensurate control or strategic autonomy.
An emerging consequence is that firms may find their competitive advantage defined by how well they integrate AI systems, rather than how they lead with human ingenuity.
When value creation and risk management are measured in AI outputs, organisations become dependent on algorithms for strategic narrative, not just tactical automation.
Confronting dependency, not just adoption
If 2025 was about taking AI seriously, 2026 must be about asking hard questions: Is the organisation shaping the technology, or is the technology shaping the organisation? Have decision rights shifted to models? Are leaders equipped to challenge AI recommendations when they conflict with domain knowledge, ethics or long-term strategy?
Navigating AI dependency means far more than adopting governance checklists. It requires embedding organisational reflexivity − the capacity to interrogate how AI influences culture, strategy and risk appetite − into the very fabric of executive decision-making.
It means designing processes that keep humans in strategic control, not just tactually involved. It means cultivating teams that understand when to trust model outputs and when to reject them.
Conclusion: A call to strategic maturity
In 2026, South African organisations will not be judged on whether they adopted AI; they will be judged on how they manage dependence on it.
Adoption was the easy part − the hard part is leadership, accountability and resilience in the face of systems that operate at scales and speeds beyond the capabilities of unaided human cognition.
Organisations must confront the hidden costs of dependency, including the erosion of human judgement, blind spots in governance and the accumulation of strategic risk. Boardrooms, executives and technologists alike must cultivate AI fluency that goes beyond operational usage − into strategic discrimination, ethical responsibility and institutional reflexivity.
We are entering a phase where AI will be more than a tool; it will be a custodian of organisational intent, whether we like it or not. The question for 2026 is this: Will South African organisations shape their AI dependency, or will it shape them?
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