The statistics are sobering: according to various industry reports, somewhere between 70-85% of AI initiatives fail to deliver their intended business value. But why?
After leading AI transformations at organisations ranging from global publishers to cruise lines, we've identified the critical patterns that separate successful initiatives from costly experiments.
The most common mistake is starting with the technology rather than the business problem. Teams get excited about the latest machine learning techniques or large language models, but forget to ask the fundamental question: what business outcome are we trying to achieve?
Successful AI initiatives start with a clear 'Why.' By grounding initiatives in tangible business needs, customer needs and ROI, you remove the guesswork. This means defining success metrics upfront, identifying the specific decisions the AI will inform, and understanding how those decisions translate to business value.
The second critical factor is organisational alignment. AI projects rarely fail for purely technical reasons—they fail because the organisation isn't ready to act on the insights. This requires change management, upskilling, and ensuring the right incentives are in place.
Our approach at CrewCreate combines technical excellence with commercial rigour. We work with leadership to define clear objectives, with data teams to ensure technical feasibility, and with end users to guarantee adoption.