AI Articles and Analysis about Process automation

The healthcare domain seems ripe for disruption by way of artificial intelligence in the form of predictive analytics. Accenture estimates the AI in healthcare market will reach $6.6 billion by 2021.

The insurance industry is looking to adopt artificial intelligence applications for a variety of business functions due to its access to large volume of customer data. According to our AI Opportunity Landscape research in insurance, approximately 46% of AI vendors in insurance offer solutions for claims and 43% offer solutions for underwriting. While there are other areas of insurance that could benefit from AI, it's clear that these two core insurance tenets are where the traction is with AI in the industry.

This article is based on a talk by Emerj.com (formerly TechEmergence) CEO Daniel Faggella at a recently held independently organized TEDxURI event. Part of the talk was on the impact of artificial intelligence on job security.

Episode Summary: AI, specifically natural language processing, has made it easier to understand text as a medium in a deeper, more efficient way and at scale. With video, the situation is quite different. AI is already being used to help industries that work in the video medium. However, searching for content within videos is more challenging because video is not just voice and sound, it is also a collection of moving and still images on screen. How could AI work to overcome that challenge?

According to the Automated Imaging Association (AIA), machine vision is a combination of hardware like cameras, image sensors, and image processing software that can help automate applications like inspection and analysis by allowing machines (such as robots) to ‘see’ their surroundings.  

Stockbrokerage might be viewed by investors as a traditionally human-based service allowing them to buy and sell equities. When looking at the shift in how stock brokerage is different today compared to the early 2000s, the largest change seems to be in software-based automation. Put simply, a lot of what was being done by humans (such as executing trades, giving advice to investors, discretionary trading) can now be done through software.

Episode Summary: In this episode of the podcast, we interview AIG’s Chief Data Science Officer, Dr. Nishant Chandra, about natural language processing (NLP) for internal and team communication. Dr. Chandra talks about how NLP can help with sharing documents with specific team members whose roles warrant viewing those documents.

With an ongoing nurse shortage in the United States and other areas, startups and global companies have begun developing methods for handling time-consuming responsibilities traditionally held by nurses, ranging from daily operations to diagnosis.