9 Indicators Of The State Of Artificial Intelligence (AI), May 2019

US federal government contract obligations and AI-related investments grew almost 75% to nearly $700 million between fiscal 2016 and 2018 [Federal News Network]. Of those that have adopted an AI-driven marketing solution, 74% reported using AI in an "assistive" fashion, which surfaces insights for marketers to consider during manual decision making. Only 26% of marketers reported using autonomous AI, which can act on its own insights and work collaboratively with marketers (without adding manual work) [Albert and Forrester]. Notable growth came in areas like food and consumer goods (48%), plastics and rubber (37%), life sciences (31%), and electronics (22%) [Robotic Industry Association]. Nearly eight out of 10 enterprise organizations currently engaged in AI and ML report that projects have stalled, and 96% of these companies have run into problems with data quality, data labeling required to train AI, and building model confidence; only half of enterprises have released AI/ML projects into production; 78% of their AI/ML projects stall at some stage before deployment; 81% admit the process of training AI with data is more difficult than they expected; 76% combat this challenge by attempting to label and annotate training data on their own; 63% go so far as to try to build their own labeling and annotation automation technology; 71% report that they ultimately outsource training data and other ML project activities [Alegion and Dimensional Research].