Machine learning is gradually becoming more mature, according to a survey by BrainCreators among 140 participants from different sectors and countries. 54 percent of the respondents have now implemented machine learning strategies in their organization.
According to the survey, 28 percent of this group is in the process of scaling up their machine learning initiatives. In addition, 35 percent said they were able to demonstrate a demonstrable Return On Investment (ROI).
A key reason for starting machine learning is because the company wants to make actions and decisions faster, says 50 percent. Another reason is to remain a competitor (23%). Improving the customer experience (9%) and reducing errors in business processes (6%) also play a role.
However, companies still see several challenges in machine learning. 34 percent see the integration of existing systems as a challenge, 20 percent mention the budget. Making data accessible (13 percent) is also seen as a major challenge.
Types of projects
All kinds of machine learning projects can be found within companies. The most common projects were the processing of information (26 percent) and Natural Language Modelling (19 percent). 17 percent say they have a project related to planning.
Other common projects revolve around Machine Vision (16 percent) and handling & control processes (11 percent).
The departments that benefit most from the projects are customer support and business intelligence departments (both 32 percent). According to 13 percent, marketing & sales also benefit from the projects.
Startups are further along
Moreover, startups are more likely to be advanced in machine learning than larger companies. According to BrainCreators, startups generally innovate faster, because they take risks more often. Employees are also more involved in strategic decisions and there is less internal bureaucracy.
“In order to further stimulate the growth and developments around Machine Learning, it is important that companies continue to experiment. However, it is important that there is a well thought-out strategy behind it, so that the new technology is implemented and used in the right way,” says Jasper Wognum, CEO of BrainCreators.
Wognum argues that it is important to create a corporate culture that has clear guidelines for human-machine collaboration. In this way, machine learning should be to the benefit of the employees.