Machine learning will change how we live and work more than any technology since the internet, says Chris Chelliah, group vice-president of Oracle Asia Pacific.
Mr Chelliah says the one risk with machine learning is in ignoring it.
Machine learning is already present in our everyday lives, in the software on our phones, in our cars and homes and in the business software, said Mr Chelliah.
Artifical intelligence technologies will be present in "almost every new software product" by 2020, said Gartner.
Media companies may soon be staffed by robots, and driverless cars will become common in the street.
"These will certainly be key areas of development in the next few years, but machine learning is changing the world around us in significant ways right now," he said.
"Machine learning's ability to quickly and effectively make decisions may sound less sensational than driverless cars, but it is what will make machine learning an era-defining technology."
Early adopters will gain a measurable edge in the marketplace, and few can afford to be left behind, said Mr Chelliah.
Machine learning is growing along with cloud computing because the integration of cloud applications, platforms and infrastructure are crucial to the effectiveness of machine learning.
"They open up machine learning to ever greater pools of data, breaking down silos and drawing in data from across organisations and their networks," he said.
The algorithms that drive machine learning need data from as many sources as possible. The more it feeds on that data the smarter it becomes and the greater its decision-making potential.
The growing acceptance of cloud technologies will fuel the development of machine learning in 2018, said Mr Chelliah.
Strategy is crucial in all of this, he said.
"Machine learning should deliver long-term strategic value, which will fundamentally transform functions or critical processes within businesses rather than delivering a short-term wow factor," said Mr Chelliah.
Reducing the amount of time to create accurate, reliable forecasts can have a significant impact on a company's bottom line by increasing its ability to plan, budget and resource effectively.
"The beauty of machine learning is its uses are almost limitless," said Mr Chelliah.
"It has a role to play in any situation where there is value in rapidly analysing and deriving understanding from data. For example, identifying trends or anomalies in vast data sets can be used in clinical research, compliance and security."
Machine learning is also driving a complete revolution in customer service, he said.
"In almost any customer-facing industry a vast number of enquiries fall into a limited number of categories and many are simple to predict and respond to using chatbots that are powered by machine learning," said Mr Chelliah.
This frees up customer service agents to handle the limited number of complaints that are more unique and require human intervention.
"Machine learning isn't going to replace people but it can certainly make people better at whatever they do. If there is a risk with machine learning, it is in ignoring it," he said.
