As many as 95% of AI projects never make it past the testing phase. Despite growing investment and ever-higher expectations, many implementations end at the pilot stage, a board presentation, or a single proof of concept.
Why is this happening? Is the problem the technology itself, or rather the way organisations approach its implementation? How can we avoid the mistakes that prevent projects from delivering a measurable ROI and real operational value?
π Read the full article βWhy do 95% of AI implementations stop at the executive presentation stage?β prepared by Piotr Wegner β Solutions Director at Britenet β in which he explains what determines the transition from experiments to successful implementations in a production environment.
