It’s that time of year again and McKinsey has updated their global survey on AI adoption and practice. This survey is valuable because it focuses on the relative competitive position of companies using AI. There are two types of company now – those that adopt AI and those that don’t. Those that don’t will fail. For those that adopt, there are leaders and laggards.
According to McKinsey, a small share of companies are achieving outsize business results from AI, which is widening the gap between the leaders and the laggards. High performers are seeing greater revenue increases and cost decreases than those that don’t adopt AI. The advantages are seen mostly in marketing, sales and manufacturing.
However, there are varying capabilities across AI adopters. What makes a company an AI leader is whether management can scale AI beyond a few attractive use cases and successfully embed AI more deeply in the company mindset. This is primarily an issue of strategic alignment and business ownership of AI outcomes. Cross-functional collaboration and investment in the talent required to translate business needs into technical needs is a core differentiator of AI leaders.
McKinsey raises the alarm that too few companies take the risks of AI seriously.
Despite extensive dialogue across industries about the potential risks of AI and highly publicized incidents of privacy violations, unintended bias, and other negative outcomes, the survey findings suggest that a minority of companies recognize many of the risks of AI use. Even fewer are taking action to protect against the risks.
While some people recognize the risks, they fail to do anything to manage them. Explainability, for example, is widely recognized as a new risk that is specific to AI but this doesn’t necessarily translate into having a process to manage a real situation where lack of explainability becomes a real business issue. The recent Apple Card fiasco is a case-in-point.
The survey supports our view that AI is a defining capability for organizations. AI has completely transformed the competitive landscape and is creating a distinct division between those who adopt and scale and those who fail to make the transformation.
Clearly technical talent is vital, but this work also points to the real nature of an AI transformation – it takes the entire company to be AI-aware, on-board and skilled in the creation, deployment and management of Machine Employees.