AI implementation is not a simple shortcut to reducing staff—or simple in any way, according to a Wharton professor: ‘The main point … is the significant amount of effort required to make it happen’ Bitget
In Finance & Insurance, the implementation of AI for tasks like fraud detection or claims processing requires substantial investment in data infrastructure and skilled personnel. Similarly, in Education, using AI for personalized learning or automated grading needs careful planning and ongoing refinement to avoid unintended consequences for students and teachers. Both sectors need to understand that realizing the benefits of AI requires more than just software purchase; it requires fundamental changes in workflows, training, and organizational structure.
Organizations should focus on strategic AI implementations tied to specific business objectives with ample project management and change management resources. Simplistic 'AI first' approaches will result in significant opportunity costs as projects stall or fail, wasting resources and potentially reducing customer satisfaction.