AI enthusiasts still slow to adopt new technology

Among those making the jump to AI, the three most popular uses are to increase efficiencies or worker productivity, to inform future business decisions and to streamline processes. 
Jeff Rowe

Artificial intelligence and machine learning are rapidly becoming critical parts of the IT framework of many organizations, including in healthcare, but that doesn’t mean IT managers are necessarily flocking to adopt new AI.

According to a recent survey by the RELX Group, a global provider of information and analytics, “while the value of the technologies is clear to executives, only 56 percent of organizations use machine learning or AI. In addition, only 18 percent of those surveyed plan to increase investment in these technologies.”

The company surveyed 1,000 U.S.-based senior executives across government, healthcare, insurance, legal, science/medical and banking in September, and the research found that 88 percent agree that AI and machine learning will help their organizations be more competitive. Still, they are taking their time adopting them.

“Organizations [that] can successfully use emerging technologies such as AI and machine learning to provide their customers with better products and advanced analytics can emerge as the leaders of the future,” said Kumsal Bayazit, chairman of RELX Group’s Technology Forum.

“While awareness of these technologies and their benefits is higher than ever before, endorsement from key decision makers has not been enough to spark matching levels of adoption.”

The measured pace of adoption notwithstanding, the study showed that AI and machine learning are making their mark, with 69 percent of those surveyed saying the technologies have had a positive impact on their industry.

Among other things, machine learning and AI are helping solve challenges by automating decision processes (cited by 40 percent); improving customer retention (36 percent); and detecting fraud, waste and abuse (33 percent).

One possible explanation for the lack of AI and machine learning adoption, analysts say, is a disconnect at the decision-making level. Senior leadership must be able to understand the practical use of, and objectives for, advanced technology in order to articulate the message to their employees and drive top-down buy-in and implementation.