AI Sector Overviews Articles and Reports
Artificial intelligence “sector overview” reports are designed to help business leaders explore the possibilities and important AI trends across industries. Search our sector overview reports below:
In the past decade the number of people killed by natural disasters each year has ranged from as low as 14,389 in 2015 to as high as 314,503 in 2010, according to the International Federation of Red Cross and Red Crescent Societies. Every year over 100,000,000 people are also affected by natural disasters. Government, companies, and aid organizations are all working to keep these tragic deaths as low as possible. One tool they have turned to for help in recent years is search and rescue robots.
Business leaders in pharma and life sciences have more specific business intelligence needs than peers in other industries. In addition to common business drivers like marketing, profit and loss, and customer churn, pharmaceutical companies need information regarding patients and clinical trial results.
McKinsey estimated that embarking on digital transformation to restructure value chains and drive R&D innovation across the pharmaceutical industry could be worth $50–150 billion of earnings before interest, taxes, depreciation, and amortization. In particular, machine learning is likely to continue finding a place in the pharmaceutical industry. Pharmaceutical companies have found applications for machine learning ranging from drug discovery to clinical trial retention.
The State of AI in the Asian Pharmaceutical Industry
AI seems to be making its way into the pharmaceutical space in Asia over the last two or three years, particularly in China and Japan. For the most part, the companies offering or using AI for drug discovery are just starting to acquire funding and talent. XtalPi seems to have the highest density of talent with a decent likelihood of being able to work with machine learning.
Facial recognition software is making its way into the mainstream, with consumer applications such as the ability to unlock one’s smartphone with their face. The banking sector has been at the forefront of enterprise adoption of AI since machine learning became the hot topic of the business world in the early years of the decade; as such, it makes sense that facial recognition technology would start to make its way into banking.
wikiMany of the pivotal technologies utilized by the public today have their roots in military projects. The internet’s first successful message transfer was due to a U.S. Department of Defense-awarded contract in 1969 for the development of the “ARPANET project.” Global Positioning System (GPS) technology utilized in smartphones today was put in place and created in the 1970s for accurate military positioning, coordination, and tracking.
There are few companies claiming to offer artificial intelligence solutions to orthopedics companies. We found that these solutions are intended to help orthopedics companies with at least one of the following business problems:
Sensors and mobile devices are in many ways working with AI software for business intelligence purposes in a few industries, including insurance and oil and gas. In the healthcare space, mobile devices and wearables allow patients to receive information on possible diagnoses for their symptoms and to monitor metrics such as their heart rate.
There are several companies claiming to offer AI solutions to banks and financial institutions. We found that these solutions are intended to help banking and finance companies with at least one of the following business problems: