For a long time, much of ICT distribution has been a game of reaction – waiting for vendor forecasts, fulfilling reseller orders and doing our best to keep the system moving. But as we all know, reacting isn’t the same as anticipating. And in today’s volatile, data-rich world, anticipation is everything.
We’ve been thinking hard about how artificial intelligence and data-led insight can help us move from reacting to predicting. Because if we want to create real value in the channel, we need to be smarter, not just faster.
This isn’t about chasing hype. It’s about practical change. As I shared in earlier pieces, distribution still relies heavily on gut feel – years of experience, yes, but often without enough data to validate those instincts. AI doesn’t replace instinct; it augments it. It helps us spot patterns we can’t see, unpack noisy, unstructured data and remove unnecessary assumptions from decision making.
Consider stock planning. If a product is underperforming, traditional thinking might suggest demand has dropped. But AI might show something deeper – perhaps a shift in buyer behaviour, a packaging change that confused customers or channel conflict we hadn’t considered. One of the most powerful things AI can do is help us ask better questions sooner.
The opportunity isn’t just in analysing structured data like sales histories or stock levels. It’s in combining that with unstructured data – reseller conversations, feedback forms, even call centre transcripts. That’s where the real demand signals often live, and it’s where AI excels. According to International Data Corp, organisations that invest in decision intelligence – AI-driven analytics focused on improving judgment – are seeing up to 30% improvement in decision-making speed and outcomes.
That matters in a market like South Africa, where every unit, every delay and every insight counts. We don’t have the luxury of overstocking or relying on long lead times. Accuracy matters. Efficiency matters. And being able to sense change early gives us a critical edge.
Predictive supply chains
Globally, the shift towards predictive supply chains is gaining real traction. A recent article in Harvard Business Review noted that machine learning is already transforming supply chain management by enabling dynamic, scenario-based forecasting that moves beyond static historical models. This reflects a mindset shift from responding to disruption to preparing for it.
Across the industry, the few companies that have embraced AI in their supply chains are seeing more than just incremental improvements. They’re streamlining logistics, tightening up inventory management and lifting service levels in ways that were difficult to achieve with traditional methods alone. These gains are not just about efficiency – they’re about resilience and responsiveness. And while much of the early adoption has come from larger global players, the same principles apply locally. With the right mindset and tools, there’s no reason South African distributors can’t unlock similar advantages.
Read: Zuckerberg bets big on artificial general intelligence
But as with any technology shift, it’s not just about the tools – it’s about mindset. We have to get more comfortable with testing, learning and sometimes getting it wrong. The fear often isn’t about the tech itself. It’s about unfamiliarity, ethical concerns and not knowing where to begin. But the truth is, starting small, staying curious and committing to learning can go a long way.
AI also allows us to reassign human effort. Repetitive forecasting, data clean-up admin – these can be automated. What’s left is the work that only humans can do: building trust, strengthening partnerships and navigating nuance. That’s where we want to spend more of our time.
This isn’t a future conversation. This is a now conversation. And if we’re honest, it’s one our industry has delayed for too long. Predictive distribution, enabled by AI, is not just possible but inevitable. The question is whether we lead that shift or get pulled along by it.
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