AI Articles and Analysis about Process automation

The finance sector has proven itself an early adopter of AI in comparison to other industries. As such, the applications of artificial intelligence and machine learning in finance are myriad. Traders, wealth managers, insurers, and bankers are likely well aware of this in some form.

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.

To some, facial recognition may feel like an AI technology with one chief use case and numerous niche ones that are not helpful outside of the client company that requested it. While security and anti-fraud solutions tend to dominate the conversation, there are many actionable possibilities for facial recognition software.

The insurance industry is dominated by large global firms that deal with thousands of customers filing insurance claims every day. Claims processing is a huge part of the insurance business process and improving turnaround time for each claim is critical to reducing operational costs at insurance firms.

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.

When it comes to the possibilities for AI in the insurance space, it may seem like machine vision is an inevitable choice for any insurer looking to have as much information on the insured property, car, or people as possible. However, this may still yet to be the case for many insurers. The insurance space has a relative lack of case studies for this type of AI software. This may indicate a lack of demand from the insurance industry or a lack of traction on the part of the technology's use in insurance.

When it comes to the healthcare industry, one might be able to think of numerous use cases for AI approaches like machine vision or predictive analytics. However, the applications of natural language processing (NLP) in healthcare are just as varied.