The scalability of artificial intelligence (AI) can yield a substantial competitive advantage; however, mere investment in advanced technologies and algorithms is insufficient. It is imperative to reconfigure decision-making processes and operational frameworks to effectively extract value from AI, alongside investing in human capabilities to ensure sustainability. Within Excelsa, we commonly refer to this approach as AI at scale or AI @ scale.

The pioneers in AI @ scale, those who have successfully expanded AI capabilities throughout their organizations and derived significant value from their investments, typically allocate 10% of their AI investment towards algorithms, 20% towards technologies, and 70% towards integrating AI into business processes and adopting agile methodologies. In other words, these organizations prioritize investing twice as much in human resources and process optimization as they do in technological advancements.

Companies that neglect adequate investment in human resources and process optimization quickly encounter setbacks in their AI endeavors. This is because launching a series of promising AI @ scale pilot projects can be deceptively easy. However, without the appropriate approach and a dedicated focus on change management strategies, achieving widespread implementation of AI across the entire business becomes nearly impossible.