The year has been an unconventional whirlwind for all of us. But it has been an incremental phase for AI. This year, the conversations around AI in ethics, responsibility, engineering and research have peaked. So let’s see what 2021 has in store for AI.

ML and Hyperautomation:

Hyperautomation is an IT mega trend which simply states anything within an organization that can be automated, should be. For instance, legacy processes. AI and ML happen to be among the major drivers of this change within organisations, accelerated further by the ongoing pandemic

AI Engineering:

One of the biggest challenges in deploying AI and ML models is scalability, maintainability and governance – and this can be addressed with a robust AI-first engineering infrastructure. This incorporates elements of DevOps, DataOps and ModelOps, making AI a part of the mainstream of the DevOps process instead of an add-on track.

Cybersecurity:

This is one domain that has to constantly upgrade itself in the wake of challenges to asset safety online such as malware, DDOS attacks, ransomware and more. AI-powered cybersecurity tools can collect data from a company’s transactional systems, communications networks, digital activity and websites, external public sources, and utilize AI algorithms to recognize patterns and identify threatening activities.

The intersection of AI, ML and IoT:

A strong foundation in IoT allows for robust AI systems to thrive. The two avenues are closely connected and in the coming year, we could see more integration of the two with Artificial Intelligence of Things (AIoT) redefining industrial automation

Ethics in AI:

The conversations around ethical and responsible use of AI has dominated the business sphere this year, and will continue to be a crucial point of focus for AI companies next year too. We can expect some concrete steps being put in place like an ethics committee, appointing an AI ethics officer among others to ensure higher levels of compliance 

Source: CRN