A recent survey reveals that CMOs around the world are optimistic and confident about GenAI’s future ability to enhance productivity and create competitive advantage. Seventy per cent are already using GenAI and 19 per cent are testing it. And the main areas they’re exploring are personalisation (67%), content creation (49%) and market segmentation (41%).

However, for many consumer brands, the divide between expectations and reality looms large. Marketers envisioning a seamless, magical customer experience must recognise that AI’s effectiveness depends on high-quality underlying data. Without that, the AI falls flat, leaving marketers grappling with a less-than-magical reality.

AI-powered marketing fail

Let’s take a closer look at what AI-powered marketing with poor data quality could look like. Say I’m a customer of a general sports apparel and outdoor store, and I’m planning for my upcoming annual winter ski trip. I’m excited to use the personal shopper AI to give me an experience that’s easy and customised to me.

I need to fill in some gaps in my ski wardrobe, so I ask the personal shopper AI to suggest some items to purchase. But the AI is creating its responses based on data about me that’s been scattered across the bran