In today’s digital economy, data is often referred to as the new currency of business. But what use is this currency if it’s locked away, never invested or spent – or used to drive better decision-making within the business? Many organisations are collecting vast amounts of data without extracting its full value – often owing to a lack of strategy, trust or understanding. As artificial intelligence (AI) matures, it offers a powerful lever to convert this dormant asset into actionable insights – but only if organisations are ready to use it legally and responsibly.
This was the key theme of a recent webinar discussion featuring Karlien Rust, CTU Training Solutions’ National Marketing Manager; Johan Steyn, human-centred AI advocate; and Amelia Phefo-Masibulele, who works in the public sector for the City of Tshwane.
From passive collection to active insight
Too many organisations treat data collection as a compliance checkbox, says Rust. "Are we using data, or are we just collecting it to be compliant? Often it sits dormant, without activation or insight."
Loyalty cards, for example, capture huge amounts of consumer data – but many retailers fail to act on that information beyond surface-level promotions. In contrast, others are using customer app data to adjust interfaces dynamically, based on buying behaviour. This gap between data collection and data activation is where real business value is either unlocked or lost.
Steyn notes that the problem often starts at the top. “Businesses don’t realise what a goldmine they’re sitting on. They outsource data management to the techies without aligning it to board-level strategy. Collecting data shouldn’t be a box-ticking exercise – it has to serve a purpose.”
AI: The catalyst for smarter decision-making
AI can uncover patterns that humans can’t see and answer questions businesses didn’t even think to ask. “Without AI, it would take much longer to uncover trends – and by the time you do it manually, the trend has already changed,” Rust points out. AI doesn’t just accelerate analysis; it elevates it.
Still, there's a persistent mismatch. “We measure what’s important to the business,” says Steyn, “but not necessarily what’s important to the customer. And then we’re surprised when customers aren’t loyal or staff aren’t engaged.”
Public sector organisations are beginning to see the value of data, says Phefo-Masibulele. “We’ve historically collected data because we were told to, not because we had a strategy for it. There’s also a silo mentality – each department holds onto their data, which makes integrated decision-making very difficult.”
Trust, strategy and culture: The foundations of success
Even among organisations striving to be data-driven, a lack of trust persists. “Businesses may aim for data-driven decisions, but then don’t trust the data to make those decisions,” Phefo-Masibulele says.
Building trust requires both a culture shift and better data governance. “To build effective AI, you need to understand the value of your data – how to access it, use it and prepare it to address real organisational challenges,” she added.
AI can also break through outdated survey methods and vanity metrics, enabling businesses to offer hyper-personalised experiences. It can give a business a competitive edge and build loyalty, but it’s not without trade-offs. “Hyper-personalisation can box people in,” warns Phefo-Masibulele. “It doesn’t work across every customer segment and in some instances may raise ethical concerns.”
AI is not a magic wand
A common misconception, says Steyn, is that AI is either too dangerous to use or that it will magically solve all business problems. “You need a business strategy that may include AI — not an AI strategy in search of a solution to a problem.”
Rust agrees. “Companies often start with the ‘how’ – how to implement AI – rather than the ‘what’. What are you trying to achieve? What data do you already have that can support that? Start there.”
The fear of “unclean” data also holds businesses back. The solution? Start small, pilot safely and involve people in the process. “AI complements human decision-making – it doesn’t replace it,” says Phefo-Masibulele. “Understand its potential and its limitations.”
Gartner research suggests that 70% of AI projects fail to deliver ROI, often because organisations rush in without defining the problem clearly or understanding the context in which AI will operate.
The reality of AI: Investment, effort and payoff
“If you do it right, AI will eventually reduce costs and make life easier,” says Steyn. “But in the short term, it requires investment – time, effort, oversight and training. The beast you tackle when you decide to implement AI is often bigger than you imagine.”
For mid-sized businesses nervous about their data maturity, the advice is to start with your goals. “What do you want to achieve? What will improve your business or increase revenue? If there’s no clear financial or strategic aim, you probably don’t need AI yet,” Steyn advises.
Often, businesses have more data than they realise – they just need to consolidate it and align it with their ‘why’. Data silos, lack of strategy and fear of the unknown are all barriers – but with the right mindset, they’re all solvable.
Final thoughts
AI has rewritten the playbook on how businesses interact with customers and make decisions. But unlocking its true potential requires more than tools – it requires trust, strategy and a willingness to re-imagine old ways of working.
As Rust sums up: “What is the main criterion you need to help you make a decision? Start there. AI can help, but only if you know what you’re aiming for.”
You can watch the full webinar here: AI and Data Webinar – YouTube
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