AI business adoption, attitudes and expectations

50% of workers are currently using some form of AI at work compared to only 32% last year; workers in China (77%) and India (78%) have adopted AI over 2X more than those in France (32%) and Japan (29%); 65% of workers are optimistic, excited and grateful about having robot co-workers and nearly a quarter report having a loving and gratifying relationship with AI at work; 64% of workers would trust a robot more than their manager and half have turned to a robot instead of their manager for advice; workers in India (89%) and China (88%) are more trusting of robots over their managers, but less so in the U.S. (57%), UK (54%) and France (56%); 82% think robots can do things better than their managers, including providing unbiased information (26%), maintaining work schedules (34%), problem solving (29%) and managing a budget (26%); managers are better than robots in understanding workers’ feelings (45%), coaching them (33%) and creating a work culture (29%) [Oracle survey of 8,370 employees, managers and HR leaders in 10 countries]

The growth of AI applications in deployment was actually less this year than last year, with the total percentage of CIOs saying their company has deployed AI now at 19%, up from 14% last year—far lower than the 23% of companies that thought they would newly roll out AI in 2019 [Gartner]

74% of Financial Services Institutions (FI) executives said AI was extremely or very important to the success of their companies today, while 53% predicted it would be extremely important three years from now; about 75% expected that over the next three years their organizations will gain major or significant benefits from AI in increased efficiency/lower costs; while 61% of FI executives said they knew about an AI project at their companies, only 29% of these executives reported on a project that had been fully implemented; only 29% of AI projects are within full implementation phase, with 46% still pilots, 35% in proof of concept and 24% in initial planning; challenges include securing senior management commitment (45%) and securing adequate budget (44%); technologies used in AI projects include virtual agents (72%) and natural language analysis (56%); 50% found it extremely or very challenging to secure talent and 49% found it extremely or very challenging to attract and retain professionals with appropriate skills [Cognizant survey of FI executives in US and Europe]

AI business impact

Google’s Natural Language Processing (NLP) model BERT was added to its set of search algorithms and will help it better understand one in 10 searches in the U.S. in English (“With the latest advancements from our research team in the science of language understanding—made possible by machine learning—we’re making a significant improvement to how we understand queries, representing the biggest leap forward in the past five years, and one of the biggest leaps forward in the history of Search”) [Google Keyword]

Twitter reported in a letter to shareholders that 50% of all abusive tweets on the platform are being removed by its automated moderation tools before users have a chance to report them, up from 43% the previous quarter [Fortune]

AI consumer attitudes

Almost two in three Britons disagree with police using artificial intelligence such as facial recognition technology to identify suspects [Reuters and YouGov survey of 2,000 Britons]

About 40% of adult Americans drivers are leaning more to buying self-driving cars in the future as they look to snack, chat on their phone or catch up on email while the car drives itself [Reuters and Adobe Analytics survey of 1,040 American adults]

200 business school students at Boston University and at New York University were offered the opportunity to take a free assessment that would provide them with a diagnosis of their stress level and a recommended course of action to help manage it; 40% signed up when they were told that a doctor was to perform the diagnosis, but only 26% signed up when a computer was to perform the diagnosis (in both experimental conditions, participants were told that the service was free and the provider made the correct diagnosis and recommendation in 82% to 85% of previous cases); 243 Americans from an online panel were asked to indicate their preference between two providers for a skin cancer screening, with both providers 90% accurate in their diagnoses; the degree to which participants perceived themselves as unique predicted their greater preference for a human than an (equally accurate) AI provider; it had no effect on their preference between two human providers [Harvard Business Review]

The future of work, now

Across more than 18,500 tasks, for each occupation, on average, workers were asked to perform 3.7 fewer tasks in 2017 than seven years earlier. When looking at the impact of AI and machine learning on tasks across seven years, the data show that among tasks that are more suitable for machine learning (e.g., scheduling, credential validation), workers, by occupation, were asked to perform 4.3 fewer tasks. Conversely, among tasks that are less suitable for machine learning (e.g., design, industry knowledge), workers, by occupation, were asked to perform 2.9 fewer tasks. This reflects a 46% larger decline in demand for tasks that are more likely to be suitable for machine learning, compared to those that are less likely. Tasks have shifted out of mid-wage jobs into low-and high-wage jobs. For every five tasks shifted out of mid-wage jobs, four tasks move to low-wage jobs and one moved to a high-wage job [MIT-IBM Watson AI Lab]

AI IP

AI-related applications to the US Patent Office grew to about 3,800 in 2018 from roughly 3,200 in 2017 and about 1,900 in 2014 [WSJ]

The Life of Data, the fuel for AI

Mobile calls remain an important means of communication for many people, with our crowdsourced data showing that only six per cent of people did not make a call during the three-month fieldwork period. For the 94% of panellists who did, almost a third made more than 50 calls per month. However, calls were fairly short on average; over eighty per cent of calls were shorter than five minutes, with the majority of these under ninety seconds, indicating that people are making frequent but relatively short calls. Average monthly data consumption varied significantly between panellists. 44% of people used less than 500MB of mobile data per month, while only 10% of people used 5GB or more [Ofcom]

Mobile device usage as a percentage of financial services transactions has increased from 28% in 2014 to 61% so far in 2019; since 2017, the percentage of suspected fraudulent transactions from mobile devices increased 138%—far outpacing the growth in overall mobile transactions which only grew in the same time by 30% [iovation]

AI market forecasts

Annual revenue for enterprise applications of AI will increase from $7.6 billion worldwide in 2018 to $107.3 billion in 2025 [Tractica]

AI software used for contract analysis is expected to generate nearly $958 million in annual revenue by 2025, up from $85 million in 2019 [Tractica]

AI predictions

By 2023, 25% of employee interactions with applications will happen via voice, up from almost 3% in 2019 [Gartner]

By 2022, 75% of new-end user solutions leveraging AI and ML techniques will be built with commercial, instead of open source, platforms [Gartner]

By 2023, over 75% of large organizations will hire AI behavior forensic, privacy, and customer trust specialists to reduce brand and reputation risk [Gartner]

By 2022, more than half of major new business systems will incorporate "continuous intelligence" that uses real-time context data to improve decisions [Gartner]

Through 2022, deployment of artificial intelligence to augment, streamline, and accelerate IT Operations will be a principal IT Transformation initiative for 60% of enterprise IT organizations [IDC]

AI quotable quotes

“…collaboration between humans and machines does not necessarily lead to better outcomes, and human supervision does not sufficiently address problems when algorithms err or demonstrate concerning biases”—Michelle Vaccaro and Jim Waldo, Communications of the ACM, November 2019

“When AI is used extensively on the offensive, you need to have a symmetric response on [cybersecurity] defense”—Hitesh Sheth, President and CEO, Vectra AI

“While machine learning may be able to spot patterns in x-rays or mammograms and aid in a diagnosis, only a physician can work with a patient to determine the best course of treatment for that individual”—Atul Grover, executive vice president of the Association of American Medical Colleges

“Patients believe that their medical needs are unique and cannot be adequately addressed by algorithms… When we explicitly described an AI provider as capable of tailoring its recommendation for whether to undergo coronary bypass surgery to each patient’s unique characteristics and medical history, study participants reported that they would be as likely to follow the treatment recommendations of the AI provider”—Chiara Longoni and Carey K. Morewedge, Boston University

82% of CEOs say they have a digital initiative or transformation program, but only 23% think their organizations are very effective at harvesting the results of digital, and even fewer CIOs would say they are very strong at this [Gartner surveys of CEOs and CIOs]

Source : https://www.forbes.com/sites/gilpress/2019/11/01/ai-stats-news-64-of-workers-trust-a-robot-more-than-their-manager/?ss=ai#661a3b0d2b21