AI will continue to expand as organizations realize the power that AI can hold for solving problems better, faster, and at scale. Lives of people also will continue to be more useful as we turn the corner from applied analytics and natural language processing to multi-turn conversational AI and deep inference that turns our interactions with applications and devices into more robust and human-like with each and every software update. The enterprise applications for AI will be more robust and powered by extraordinary data growth and more powerful chips for workload acceleration, along with more robust software and frameworks that allow data scientists to move faster to deploy and test algorithms and apply data to solve big complex enterprise problems.
Ability to efficiently streamline the deployment of a process can be massive on the top and bottom line. Intelligent Automation has been a focal point of companies like Microsoft, with its Power Platform and Red Hat’s Ansible, both serving as examples of software solutions that have been built to enable the deployment of automation to streamline business processes from small simple tasks being built by citizen developers.
Technologies will transform the nature of work and the workplace itself. Machines will have the ability to carry out more of the tasks done by humans and perform some tasks that go beyond what humans can do. Some occupations will decline, others will grow, and many more will change.
AI and automation challenges are still causing hindrance. The limitations are partly technical, such as the need for massive training data and difficulties “generalizing” algorithms across use cases. Innovations have started to address these issues. Other challenges are in the use of AI techniques.