FINAL WORD
3. Data Maturity – Ensuring high-quality, accessible, and structured data – AI is only as good as the data it learns from.
4. Strategic AI Planning – Defining specific, measurable AI use cases rather than broad‘ we need AI’ goals.
5. AI-Driven Transformation – AI actively driving business value, improving decision-making, and optimising efficiency.
Most businesses that make enquiries to us about AI are at level one or two. However, AI only starts to deliver real value at level four and five. If you’ re not moving through these stages, AI will only create complexity, not efficiency. Ultimately, this disconnect is the underlying reason why statistics show that a frighteningly large number of AI projects fail to deliver: It’ s not that the technology is bad. It’ s just that the technical maturity isn’ t there for it yet.
So, if you’ re thinking about bringing AI into your business, here are five things to check off before we talk about it:
1. Map out your business processes
You’ d be surprised how many businesses don’ t have a clear picture of how their operations run. They work in silos, with different teams doing things their own way. Before you layer in AI, take the time to map out key workflows – supply chain, customer service, finance, whatever’ s core to your business. Where are the inefficiencies? Where does work slow down? If you can’ t spot inefficiencies, AI is only going to make them faster and harder to unwind.
2. Talk to your customers and end users
It’ s easy to think you know what your customers want – but have you asked them lately? What frustrates them? What makes them come back? What would make their experience better? AI can help improve customer experience, but it needs to be pointed at the right problems. If you’ re guessing, then you’ re automating based on assumptions and fast-tracking to bad decisions at scale.
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