Data science and machine learning will become more mainstream, especially in the following industries: energy, finance (banking, insurance), agriculture (precision farming), transportation, urban planning, healthcare (customized treatments), even government.
The rise of sensor data – that is, IoT – will create data inflation. Data quality, data relevancy, and security will continue to be of critical importance.
With the rise of IoT, more processes will be automated (piloting, medical diagnosis and treatment) using machine-to-machine or device-to-device communications powered by algorithms relying on artificial intelligence (AI).
The frontier between AI, IoT, data science, machine learning, robotics, deep learning and operations research will become more fuzzy.
Statistical engineering will be present in more and more applications, be it machine learning, AI or data science.