AI & ML Catching on Despite Early Adoption Struggles
Companies plan to add AI and machine learning at a record pace in the next year, doubling their investments, according to a recent report by Gartner, the tech research and consulting group.
Gartner’s report, Survey Analysis: AI and ML Development Strategies, Motivators and Adoption Challenges queried 106 IT business professionals, of whom 59% said they are already using AI. Those organizations have an average of four AI projects in place. They plan to add six more AI and machine learning efforts by 2020 and another 15 by 2022.
The survey summed up these findings, according to a story in TechRepublic.com:
- 56% of organizations are using the technologies to support decision-making and to give recommendations to employees
- The second most important type of project is automation of tasks, such as invoicing and human resources screening, listed by 20% of respondents as most important.
- The main inhibitor of technology adoption is a lack of understanding by IT and business professionals (56%).
“The rising number of AI projects means that organizations may need to reorganize internally to make sure that AI projects are properly staffed and funded,” said Jim Hare, a research vice president at Gartner, in a press release. “It is a best practice to establish an AI Center of Excellence to distribute skills, obtain funding, set priorities and share best practices in the best possible way.”
Organizations aren’t seeking to replace human workers, but rather are using AI to make better decisions faster, according to Hare. A lack of employee skills is actually hampering companies’ ability to adopt AI, a major concern for the future.
According to a TechRepublic story on a Pactera Technologies report, 85% of AI projects fail due to senior management not recognizing the value or resisting investment in emerging technology. The report, Artificial Intelligence Localization, Winners, Losers, Heroes, Spectators, and You, surveyed IT professionals. Of those, 77% said they face barriers to entry from senior management.
The report echoes that of a Dimensional Research report based on a survey of 227 tech professionals who said eight out of 10 organizations using AI and machine learning have projects that are problematic or inactive. Of the organizations reporting a failing project, 96% say it’s because of data quality, data labeling and a lack of model confidence.
TechRepublic offers a free AI guide for business executives to learn how to adapt, called “Artificial Intelligence: A Business Leaders’ Guide.”