AI capabilities are rapidly maturing. And so, too, is enterprise adoption. More executives than ever before are actively conceiving where and how to leverage AI. But executives are also more discriminating about their organizational priorities for AI and how these leading edge technologies are rolled out. While CEOs were experimenting broadly with AI across their organizations in 2016, they are now highly focused on five priority areas.
In 2016, executives deemed customer satisfaction and retention as value drivers for their AI investments – now that focus on customer and other growth metrics is even deeper. And while technology availability was the leading concern for most executives in 2016, now it’s all about how they can best cultivate AI skills and use data most effectively.
So what do these changes mean? Moving from experimentation to implementation is not straightforward, and many companies are struggling with the transition. However, some businesses are achieving AI at scale successfully – and they are disproportionately financial outperformers. Confronting data issues and bridging the AI skills gap are critical to scaling AI and realizing value in the enterprise.