Publication Name: analyticsindiamag
Date: December 2020

Top Data Science AI Trends To Watch Out For In 2021

Top Data Science AI Trends To Watch Out For In 2021

The year 2020 was full of unexpected challenges. Having said that, it also served as a unique opportunity to leverage technology on multiple fronts. From adopting it in various industries such as retail, eCommerce and others, to adopting it to ensure the safety of employees in work from home scenarios, and improving consumer experiences, the industry went through various digital touchpoints. Adoption of data, analytics, AI, cybersecurity and other new technologies saw an exponential growth to bring about changes to fit into the changing business scenario.

Looking at the previous year, 2021 looks like an opportunity for tech trends to grow to newer arenas. Intelligent machines, hybrid cloud, increased adoption of NLP, and overall an increased focus on data science and AI is going to be the highlights in the coming year. Some of the other trends that may see a rise in the coming year are pragmatic AI, containerisation of analytics and AI, algorithmic differentiation, augmented data management, differential privacy, quantum analytics, among others. Considering these trends, it can be said that data is increasingly becoming a critical part of organisations after the pandemic.

The annual data science and AI trends report by Analytics India Magazine aims to highlight the top trends that will define the industry each year. This report, which has been developed in association with AnalytixLabs, covers the trends that will shape the year 2021. AnalytixLabs is a leading Applied AI & Data Science training institute in India. These trends are a culmination of popular industry opinions.

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Automation And Intelligent Machines Will Drive Critical Roles

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“Business Process Automation has got a tremendous impetus and top-most priority in any CXO’s list, given the unique circumstances we went through in 2020. Intelligent automation is about augmenting this with intelligent decision making and filling the crucial gaps for some hard to replace HIL (Human in the loop) based systems. Intelligent automation adoption will see cross-connecting advancements of different technologies like virtual conversation agents, NLP based entity engines, computer vision with edge AI, and large scale bot orchestrations.”   Read more

— Biswajit Biswas – Chief Data Scientist, Tata Elxsi