One statistic keeps doing the rounds: nearly 80% of organisations have deployed generative AI, yet fewer than one in five can point to a measurable improvement in operating margin. Frankly, while it is a remarkable gap, that’s exactly what I’d expect.

What’s even more interesting is how consistent the major research firms have become. Across reports from McKinsey, IBM, KPMG, Accenture and others, the diagnosis is largely the same. Technology is everywhere. Business impact isn’t.

Most organisations haven’t transformed anything. They’ve accumulated pilots.

They’re automating tasks around the edges while leaving core operating models largely untouched. They measure adoption - licences issued, prompts submitted, hours saved - instead of measuring whether the economics of the business have actually changed.

The same pattern showed up this week in a completely different context. Australia’s financial complaints authority reported a surge in AI-generated submissions - template complaints and recycled arguments that create more work for everyone involved.

That isn’t transformation. It’s automation applied to an already inefficient process.

The more I look across industries, the more I think this is the real divide emerging in AI.

Some organisations are using it to make existing work faster. Others are using it to redesign how work gets done.

Only one of those changes the economics.

The question I’d be asking every executive team isn’t, “How many people are using AI?” It’s, “Which three core business processes now operate fundamentally differently because of AI?”

Most organisations still don’t have a convincing answer.

#ArtificialIntelligence #Strategy #DigitalTransformation