It is estimated that the AI usage of enterprises will double by 2020

According to the latest survey by Gartner, an international research and consultancy organization, currently the enterprises using artificial intelligence (AI) or machine learning (ML) are carrying out an average of 4 related projects, while 59% of the interviewees said that AI technology has been deployed at present.

Jim Hare, vice president of research at Gartner, said: "We found that the rate of adoption of artificial intelligence by enterprises has increased dramatically this year, and the number of artificial intelligence projects has also increased. This means that enterprises may need to carry out internal reorganization to ensure that artificial intelligence projects have appropriate manpower and capital.   The best practice is to set up a Center of Excellence for artificial intelligence to distribute technology, obtain funds, set priorities and share best practices in the most perfect way possible. "

At present, the average number of AI projects currently in progress in enterprises is 4, but the interviewees expect to add 6 in the next 12 months, and by 2022, these enterprises expect to have an average of 35 AI or machine learning projects in progress.

According to the survey, 40% of enterprises listed customer experience (CX) as the primary motivation for using artificial intelligence technology. Although technologies such as chat robots or virtual personal assistants can be used to serve external customers, most enterprises (56%) currently use them to support internal decisions or provide suggestions to employees.   Jim Hare pointed out: "The use of artificial intelligence technology is not to replace human employees, but to enhance and empower employees to make faster and better decisions."

The second type of project was task automation, with 20% of respondents ranking it as their primary motivation.   Examples of automation are extensive, such as financial invoicing and contract verification, and automatic screening of resumes or robot interviews in human resources.

For the interviewees, the biggest challenges in adopting AI include lack of technology (56%), understanding of AI use cases (42%), and doubts about the scope or quality of data (34%).   Jim Hare reminded: "In the face of advanced technology, how to find the most appropriate staff skills is one of the major doubts of enterprises.   This technology gap can be filled by cooperating with service providers and universities, or by setting up training courses for existing employees. However, it is not easy to establish a solid foundation for data management.   Since reliable data quality is the cornerstone of accurate insight, trust building and prejudice reduction, all AI projects must prioritize data readiness. "   The survey also shows that many enterprises regard efficiency as a measure of success when evaluating the value of projects.   However, Whit Andrews, Gartner's vice president of research, said: "It is more common for companies that believe that technology is conservative or mainstream to use efficiency indicators to show project value.   Companies that adopt more active technologies may be more concerned about whether customer participation improves. "

Gartner conducted an online survey of 106 Gartner Research Circle Members in December 2018, and with the assistance of this group of experts led by Gartner and composed of IT and business professionals, Gartner produced a research report on AI and ML Development Strategies.   These subjects must have a certain understanding of the existing or planned machine learning, artificial intelligence-related business and technical aspects of their own organization.