More than half of the organizations (52%) consider risk factors a critical consideration when evaluating new AI applications, according to a recent survey by research and advisory firm Gartner. The research revealed that 55% of organizations that have previously implemented AI always consider AI for every new use case they evaluate.
According to Erick Brethenoux, Distinguished VP Analyst at Gartner, an AI-first strategy is a hallmark of AI maturity and a driver of increased return on investment. However, he emphasizes that “AI-first does not mean AI-only.” While AI-mature organizations are more likely to consider AI for every potential use case, they are also more inclined to weigh risks heavily before making decisions to proceed.
The survey was conducted from October to December 2022, with 622 respondents from organizations in the US, France, the UK, and Germany that have implemented AI. Gartner defines an “AI-mature” organization as one that has rolled out more than five AI use cases across different business units and processes, in production for more than three years.
The research also revealed that AI-mature organizations are more likely to seek legal advice in the ideation phase of AI use cases. They are 3.8 times more likely to involve legal experts at this stage of an AI project cycle. Brethenoux states,
“There is uncertainty about the ethics and legality of various AI tactics, as well as fear of violating privacy regulations.”
When evaluating the return on AI investments, 52% of AI-mature organizations focus on a combination of technical and business metrics to assess ROI. Additionally, 41% of AI-mature organizations, compared to 24% of all other organizations, use customer success-related business metrics to estimate ROI.
Brethenoux notes,
“Many business and IT leaders focus on the impact of AI on optimization and productivity, but organizations do not thrive solely by cutting costs. Organizations that use AI technology to attract and retain customers can articulate the impact on the business more clearly, leading to a positive cycle of executive approval for new AI projects.”
AI-mature organizations are also more likely to define metrics earlier in the AI lifecycle. Seventy percent of AI-mature organizations define metrics in the ideation phase of each use case, compared to 44% of less mature organizations.
