Many organizations have invested heavily in AI tools, yet measurable business outcomes often fall short of expectations. While AI adoption continues to grow, the challenge appears to be less about access to technology and more about integrating AI into day-to-day workflows and decision-making processes.
In your experience, what are the biggest barriers to turning AI experimentation into operational value? Is the issue primarily related to training, governance, change management, workflow integration, or something else?
As AI capabilities continue to evolve, it would be interesting to hear how firms are approaching long-term AI strategies and ensuring that adoption translates into meaningful business impact.