The latest survey by Gartner, an international research and advisory organization, shows that companies currently using artificial intelligence (AI) or machine learning (ML) are conducting an average of 4 related projects, and 59% of the respondents said that they have deployed artificial intelligence technology.
Jim Hare, vice president of research at Gartner, said: "We have found that the speed of companies adopting artificial intelligence has grown significantly this year, and the number of artificial intelligence projects has also increased. This means that companies may need to undergo internal restructuring to ensure that artificial intelligence projects have appropriate manpower and funds. The best practice is to set up a Center of Excellence for artificial intelligence to allocate technology, obtain funding, set priorities, and share best practice experience in the most complete way possible."
At present, the average number of artificial intelligence projects in progress by companies is 4, but respondents expect that there will be 6 new ones in the next 12 months. By 2022, these companies expect to have an average of 35 artificial intelligence projects on hand. Or machine learning projects.
The survey shows that 40% of companies list customer experience (CX) as the primary motivation for using artificial intelligence technology. Although technologies such as chatbots or virtual personal assistants can be used to serve external customers, most companies (56%) currently use it. To support internal decision-making or provide advice 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-ranked project type is task automation, and 20% of respondents cited it as the top motivation. There are a wide range of automation examples, such as the issuance of financial invoices and contract verification, and the automatic screening of resumes in human resources or interviews with robots.
For the interviewees, the biggest challenges in adopting artificial intelligence include insufficient technology (56%), understanding of artificial intelligence use cases (42%), and doubts about the scope or quality of data (34%). Jim Hare reminded: “When facing advanced technology, how to find the most appropriate employee skills is one of the main doubts of the company. This technology gap can be achieved by cooperating with service providers and universities, or setting up training courses for existing employees, etc. However, the establishment of a solid data management foundation is not overnight. Since reliable data quality is the cornerstone of precise insight, trust building and prejudice reduction, all artificial intelligence projects must prioritize data readiness "This survey also shows that many companies regard efficiency as a measure of success when evaluating the value of a project. However, Whit Andrews, vice president of research at Gartner, said: “The way to show the value of a project with efficiency indicators is more common among companies that believe that technology adoption is conservative or mainstream; companies with more active technology adoption may be more concerned about customer participation. Whether the degree is improved."
Gartner conducted an online survey of 106 Gartner Research Circle Members in December 2018. With the assistance of this group of Gartner-led expert groups composed of IT and business professionals, artificial intelligence and machines were produced. AI and ML Development Strategies (AI and ML Development Strategies) research report; these subjects must have a certain degree of understanding of machine learning and artificial intelligence-related businesses and technologies that their own organization currently or plans to adopt.
