A Gartner survey revealed that 55% of organisations that have previously deployed AI always consider AI for every new use case that they are evaluating. However, what is just as noteworthy is the 52% that report that risk factors are a critical consideration when evaluating new AI use cases.
“An AI-first strategy is a hallmark of AI maturity and a driver of increased return on investment,” said Erick Brethenoux, distinguished VP analyst at Gartner. “However, AI-first does not mean AI-only. While AI-mature organisations are more likely to consider AI for every possible use case, they are also more likely to weigh risk as a critical factor when determining whether to move forward.”
Gartner defines an “AI-mature” organisation as those who have deployed more than five AI use cases across several business units and processes, in production for more than three years.
Across all organisations, respondents had deployed an average of 41 AI use cases, with use cases remaining in production for 3.5 years (see Fig.1)
Fig. 1: Average duration of AI use cases in production
Both the number of use cases and the time in production rose with the size of the enterprise, with global enterprises reporting an average of 51 use cases in production for 4.3 years.
AI-mature organisations involve legal counsel in ideation
The most significant differentiator identified among AI-mature organisations was the involvement of legal counsel at the ideation stage of AI use cases. AI-mature organisations were 3.8 times more likely to involve legal experts at the ideation phase of an AI project’s life cycle.
“There is uncertainty around the ethics and legality of various AI tactics, as well as a fear of violating privacy regulations,” said Brethenoux. “Organisations that are more experienced with AI do not want to be told they’ve crossed a line once they are further along in the process of developing an AI use case.”
AI-mature organisations evaluate technical and business ROI metrics
When evaluating the return on AI investment, 52% of AI-mature organisations focus on a combination of technical and business metrics to assess ROI. In less mature organisations, technical metrics are most often used to measure the value of AI use cases.
More AI-mature organisations – 41% compared with 24% of all others – use customer success-related business metrics to estimate ROI. Furthermore, 47% of AI-mature organisations cite customer service as one of the top three business functions benefiting from AI, compared with 34% of others.
“Many business and IT leaders focus on AI’s impact on optimisation and productivity, but organisations do not prosper through cost cutting,” said Brethenoux. “Organisations that are using AI technology to attract and retain customers are able to more clearly articulate the impact on the business, driving a virtuous cycle of executive buy-in for new AI projects.”
AI-mature organisations are also more likely to define metrics earlier in the AI lifecycle. About 67% of AI-mature organisations define metrics at the ideation phase of every use case, compared with 44% of less mature organisations.
