AI and Machine Learning Trends in 2021
Based on Gartner’s Top Strategic Technology Trends for 2021, 37% of all firms surveyed are leveraging AI in their business. It’s also predicted that by 2022, 80% of modern technologies will be based on artificial intelligence and machine learning.
Moving into 2021, businesses and investors alike will need to be strategic in how they leverage the recent breakthroughs in AI and ML in the past years. To help in strategizing, we have compiled some of the top AI and machine learnings trends to expect in 2021.
The rise in e-commerce and general online transactions have led to the need for automated customer service functions.
These tools use reinforcement learning to be able to respond to customer concerns efficiently and accurately. Reinforcement learning is needed for a chatbot to correctly answer customer queries on bookings, deliveries and consultations.
Machine learning development companies utilize reinforcement learning to increase a chatbot’s sequential conditions such as identifying sales leads and knowing when to transfer communication to a service agent.
With more businesses shifting online in 2021, chatbots and similar automated customer service features will increase exponentially.
An AI feature that also supports chatbot function is conversational AI technology. This is the foundation of automated messaging and speech-based applications. It allows machines to understand the intended meaning of a user in different languages while also giving accurate responses in a human-like manner.
Beyond chatbots, this technology is useful in smart assistants like Apple’s Siri, Samsung’s Bixby, Amazon Alexa and Google Home. Smart assistants have proven to make daily life easier both at home and on-the-go.
With more people working remotely heading into 2021, home automation is useful for professionals that need to multitask on a regular basis.
AI and machine learning will be integral in healthcare applications in 2021. Even this year, the pandemic has been largely mitigated by AI and big data to identify patients and potential hot spots. Smartphone applications have been used to monitor the temperature of individuals and track a community’s movements to understand the spread of the disease.
With more people using applications to monitor and predict health problems, AI will continue to play an integral part in technological advances in healthcare in the coming years.
AI, machine learning and the IoT are becoming increasingly intertwined in industrial settings. Sensors in IoT devices are able to generate IoT networks that are able to accumulate large volumes of data. This is useful for AI and ML to develop smarter and more secure devices that can operate efficiently and predict certain outcomes.
These types of technology are especially useful in manufacturing plants where machines that regularly require maintenance are able to predict when a tune-up is needed next. In a world that is increasingly requiring efficiency in the production and distribution of items, the intersection of AI, ML and IoT is essential.
Written by Rebecca Jade
Edited by Alexander Fleiss