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:
This article is based on a presentation at the 2017 AI Applications Summit conference in Boston, entitled “Artificial Intelligence in the Hospital Setting” (slide deck embedded below) delivered by Emerj CEO Daniel Faggella - updated with recent insights and interviews from Emerj's podcast and AI Opportunity Landscape data.
We interviewed Karine Perset, from the OECD Directorate for Science, Technology and Innovation in France about the informational pillars that make up strong AI governance for governments worldwide. She offered us numerous insights into how the OECD developed the AI Principles and works with governing bodies to design policies that will keep AI safe and trustworthy into the future.
In July 2017, The State Council of China released the “New Generation Artificial Intelligence Development Plan," outlining China's strategy to build a US$150 billion Chinese AI industry in a few short years, and to become the leading nation in AI by the year 2030. Other nations followed suit quickly with national AI strategies of their own - with the US trailing behind by nearly two years before developing a semblance of an AI initiative. The proposed 2021 budget for the national security budget in the US is $740 billion - with a billions of dollars being earmarked for AI specifically (learn more: US Public Sector AI Opportunity Report).
We see evidence dating back to 2017 that Johnson & Johnson has been regularly publishing about their investments and initiatives related to artificial intelligence. At present, Johnson & Johnson does not seem to boast any mature, deployed applications with the firm itself, but its AI-related investment initiatives indicate their aspirations.
Leading retailers - like Walmart, Stop & Shop, and Home Depot - are enhancing their payment and fraud detection systems, using artificial intelligence that learns transaction norms and infers risk from the context of each transaction.
The COVID-19 pandemic has caused incredible disruption in healthcare systems across the world, as well as an immediate demand for innovative solutions to the growing number of coronavirus patients. Many AI vendors are already trying to find ways they can serve this demand through augmenting their machine learning-powered products - from diagnostics interfaces to radiology solutions and everything in between.
Mitsubishi UFJ Financial (MUFG) is a Japanese holdings bank and financial services company ranked 5th on S&P Global’s list of the top 100 banks, and the largest Japanese bank on the list.
Barclays is a UK bank ranked 20th on S&P Global’s list of the top 100 banks. Like other top banks, Barclays has forayed into AI for a variety of use-cases. The bank seems to work with AI vendors more than it builds AI applications in-house, which aligns with the general trend of AI adoption in financial services: 68% of the AI products we researched as part of our AI Opportunity Landscape research in financial services were bought from vendors.