85% of AI projects stop before creating value
Seventy to 85 percent of all AI initiatives fail to generate measurable business returns. They drive. They deliver results in test environment. And then they stop.
The reason is rarely technology. It's typically one of three places: Employees don't know how to use AI effectively in everyday life. Management has not taken strategic ownership. Or the organization lacks the processes and routines that integrate AI into day-to-day operations.
That's not a sign that AI isn't working. This is a sign that adoption requires as much attention as implementation.
What characterizes the companies with 3.7x returns
The companies that measure the highest AI returns and productivity increases have one thing in common: They invest in people, not just technology.
It involves dedicated AI ambassadors in-house, ongoing training across the organisation and a governance structure that gives everyone the confidence to experiment. And a pragmatic approach to adoption: Start with the use cases that provide quick, visible gains, and build confidence and momentum from there.
Documentation automation. Customer Support. Internal Knowledge Search. These are not the most glamorous use cases. But they are the ones who work first and who create the confidence that makes the next steps possible.
Your Responsibilities as a Leader
AI is not an IT project. It's a management project. It requires you to honestly map where your organization is today. That you define a concrete goal picture. And that you ensure that your plan prioritizes people and competencies to at least the same degree as systems, in a 70-20-10 ratio.
You don't have to start over. But you need to start with honesty about where you really are.
Contact Kristina directly and we'll map out where your organization is today.
