The adoption of cognitive technologies is on the rise, aiming to address business challenges, with many leaders expecting AI to significantly transform their organizations within the next three years. However, ambitious AI initiatives often face hurdles or fail. For instance, in 2013, the MD Anderson Cancer Center initiated an ambitious project to use IBM's Watson for diagnosing and suggesting treatment plans for certain cancers. By 2017, despite having spent over $62 million, the project was paused without having been applied to patient care. Meanwhile, less ambitious applications of cognitive technology at the center, such as providing hotel recommendations for patients' families, assisting with bill payments, and solving IT issues, have shown more success, improving patient satisfaction, financial outcomes, and reducing mundane tasks for staff.

This experience underscores a broader trend: simpler, "low-hanging fruit" projects often yield better results than more complex "moon shot" initiatives. This observation is backed by our survey of 250 executives familiar with their organizations' cognitive technology use, and an analysis of 152 projects across various companies. Despite the allure of ambitious AI projects, driven by the significant hype around AI, companies have historically seen greater success with technologies that incrementally improve business processes.

This discussion leads us into an examination of AI's role in business, emphasizing the importance of viewing AI through the prism of enhancing business capabilities. AI can broadly support three key areas: process automation, data analysis for insights, and enhancing customer and employee engagement. Our study categorized 152 cognitive technology projects into these three areas: automation, insight generation, and engagement, showing a clear distribution of how companies are applying AI to drive value.

In conclusion, as companies plan their AI strategies, focusing on building cognitive capabilities that align with their business objectives, and preferring incremental improvements over grandiose transformations, may lead to more sustainable success.