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 a study from Researchscape International, 74 percent of 300 marketers surveyed said personalization in this field has strongly helped their clients or companies in advancing customer relationships. It also found that 54 percent said their clients or companies experienced a 10 percent increase in sales, while 13 percent of marketers surveyed reported a more than 30 percent lift.
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.
Virtual assistants operating in response to voice or text interactions have steadily gained traction and formed a profitable sector, according to Research and Markets. The market research firm projects that total revenue will hit $15.8 billion in 2021 up from $1.6 billion in 2015. The firm also estimates that total global consumers will reach 1.8 billion by 2021.
A collaborative report by Moore Stephens and WARC estimated the size of the martech industry around $34.3 billion dollars in 2018. It follows that AI would find its way into the marketing world. Marketing experts agree that AI will have a significant impact on the marketing world in the coming years. As of now, numerous companies claim to assist marketers in aspects of their roles from garnering insights from dashboards to automating spend on ad networks.
The fashion industry has grown at 5.5 percent annually in the past decade, according to the McKinsey Global Fashion Index, and in 2016 was estimated to be worth $2.4 trillion.
In recent years, artificial intelligence has enabled pricing solutions to track buying trends and determine more competitive product prices. While static pricing keeps prices absolute, dynamic pricing adjusts prices to offer customers different prices based on external factors and their individual buying habits.
Today, customers interact with banks and financial institutions across several different channels which has lead to an explosion in customer data being collected by these organizations. This data can be effectively leveraged using AI to gain insights on current and future customer behavior.
In a 2017 symposium in Harvard’s Institute for Applied Computational Science, R. Martin Chavez, Deputy Chief Financial Officer of Goldman Sachs explains that the company’s US cash equities trading division used to employ over 600 human traders back in 2000. Today that number is down to just two human traders, with the rest of the jobs being taken over by automated trading platforms that are managed by around 200 computer engineers.