AI capabilities are rapidly maturing. More and more industrial products executives are actively determining 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. These CxOs are highly focused on select priority business functions and value drivers for their AI investments. These areas emphasize revenue growth and the customer.
And while technology availability was the leading concern for executives in 2016, now it’s how to cultivate AI skills, address regulations, and drive buy-in
Execution
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 outperforming financially. Adopting AI as part of a broader digital reinvention play, pinpointing AI investments, and developing capabilities are critical to realizing value in the enterprise.
More companies are considering the adoption of AI and are focusing on business functions where it can add value. Our research indicates companies will continue to invest in AI, but with more realistic expectations for ROI. Topline, customer satisfaction, and customer retention value drivers are typical objectives of AI implementations
Outperformers are organizations that report having outperformed their peers in revenue growth and profitability. They are in more mature phases of their AI journey. Outperformers expect to continue to out-invest their peers in AI. In 2016, 77 percent of industrial products enterprises were at least considering AI adoption. Today, the proportion has increased to 88 percent.
The outperformers think strategically about digital technologies, including AI. They leverage analytics and AI across the business. Outperformers capitalize on data. They adhere to data governance. Outperformers are automating their processes with analytic solutions beyond traditional business process management or basic robotic process automation. They are using unstructured data and/or algorithms and involving multiple types of AI technologies and data discovery.