AI Articles and Analysis about Business intelligence and analytics

Natural language processing (NLP) seems to see less use in pharma than AI approaches such as machine vision and predictive analytics, but nevertheless there are a few applications for NLP in pharma. The industry deals mostly with structured data, but in some business areas, unstructured data is the norm. In this article, we discuss how natural language processing can help pharmaceutical companies make sense of their unstructured data and use it to make decisions.

Business leaders in pharmaceuticals may be concerned with how machine vision will affect their operations in the clinical and scientific departments more than those of packaging and administration. However, prioritizing these types of operations may not provide the ROI as it’s hyped up to be. Instead, there are many possibilities for machine vision in pharmaceuticals related to packaging, shipping, and data entry.

AI applications for the insurance industry have certainly garnered a lot of press lately. We’ve previously covered such applications in the American and European insurance spaces. Countries in Asia such as China and Japan have large insurance industries and seem to have established national AI strategies.

We researched the military and defense space to discover how and where AI is utilized today by the world’s militaries and intelligence organizations as well as the capabilities artificial intelligence could bring to the sector shortly.

It may feel as though AI applications like machine vision and natural language processing hold the most potential value to pharmaceutical companies because of their capabilities to intake and transform unstructured medical data. This is especially true with machine vision, as medical imaging data can be used across multiple departments when analyzed by AI software.

Even during a time when the buzz around AI and digital data storage is prominent, there are still some companies with large amounts of backlogged data that are taking up space in their databases, but not providing enough value. Large stores of enterprise and customer data can be valuable to insurance companies for optimizing their business operations and gaining analytical insights on how their business decisions affect company growth.

It is clear the United States government has recently taken a strong stance in attempts to proliferate artificial intelligence technology innovations for the United States Department of Defense. There are those who believe that the US, Russia, and China have entered into a modern day Space Race-style competition to develop and harness artificial intelligence technologies.

In this article, we explore the applications of AI software within the automotive industry from production and manufacturing to insurance and transportation. We will discuss the equipment involved in collecting and analyzing data along with the potential value they offer to manufacturers, shared mobility companies, insurers, and drivers.