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:
InkWood Research estimated the size of the artificial intelligence market in the healthcare industry at around $1.21 billion in 2016. We surveyed more than 50 executives from healthcare companies previously and laid out the state of AI applications in the healthcare space. It seems AI-based healthcare innovations have made their way into Asia, led by developments in China, India, Japan, and South Korea. Numerous companies claim to assist healthcare professionals in Asia with aspects of their roles, including assisting in diagnostics, remote caregiving, and improving a patient's ability to manage their health using data from wearable devices.
NASDAQ estimates more than $5 trillion is traded every day in what it describes as “the most actively traded market in the word:” foreign exchange, or forex. Business leaders might expect AI to make its way into the forex world the way it has into finance and banking broadly. Most companies claim to assist foreign exchange traders by predicting when to trade or hold onto currencies. As it turns out, however, Most of the AI vendors in the forex space are in fact only claiming to use AI. There is strong evidence to suggest that their claims are illegitimate.
Modern AI and machine learning software require large sets of data in order to train its algorithms to make judgments, make predictions, and take actions. Data is a critical part of bringing artificial intelligence to life in different industry sectors. The applications we’ve highlighted below involve organizing historical and real-time data from existing businesses in the retail sector from which data scientists can build machine learning models.
It should come as no surprise that AI has found its way into radiology in a similar fashion to most other medical fields. Many AI vendors selling into the radiology field are just beginning to gain regulatory approval. We researched the use of AI in radiology to better understand where AI comes into play in the industry and to answer the following questions:
Some financial institutions have begun investing in departments that focus on artificial intelligence and machine learning applications that could determine their customer's sentiments towards market developments. These applications fall under the category of sentiment analysis. We have previously covered some of the top the machine learning applications in finance. In this report, we focus on AI-based sentiment analysis applications for the finance sector.
McKinsey reported that most oil and gas operators have not maximized the production potential of their assets. A typical offshore platform, according to the 2017 report, runs at about 77% of its maximum production potential. Industry-wide, the shortfall comes to about 10 million barrels per day, or $200 billion in annual revenue.
Our AI in Banking Vendor Landscape and Capability Map report details the state of various AI approaches and capabilities within specific banking functions, measuring them on their level of funding, evidence of ROI and adoption at large banks, and more. In this article, we discuss how and where banks are using natural language processing (NLP), one such AI approach—the technical description of the machine learning model behind an AI product.
Natural language processing, (NLP) is one AI-based technology that's finding its way into a variety of verticals. We covered the business applications of NLP in our previous report, and in this report, we intend to cover the technology's applications in finance more extensively. NLP might allow a company to garner insights that can be used to assess a creditor's risk or gauge brand-related sentiment across the web. We researched the space to better understand where NLP comes into play in the finance industry and to answer the following questions: