Why Most AI Projects Fail (And What the Successful Ones Do Differently)
Across Australia, businesses are investing in artificial intelligence at a rate they couldn't have imagined three years ago. Boards have approved budgets. Teams have launched pilots. Vendors have pitched solutions. And yet, by most industry estimates, the majority of AI projects either never make it into production or fail to deliver the business value they promised. This is not because AI doesn't work. It is because most businesses are approaching it the wrong way. If your organisation is exploring AI, scaling a pilot, or recovering from a project that did not deliver, the same handful of issues are usually at play. Here is what they are, and what successful AI initiatives consistently do differently. 1. They start with a business problem, not the technology The first sign of an AI project in trouble is when the conversation begins with "we want to use AI" instead of "we have a business problem that AI might solve." Successful AI projects begin with a...