Recent surveys, studies, forecasts and other quantitative assessments of AI highlight the mix results of implementing AI in the enterprise; the increased adoption of Robotic Process Automation (RPA) and Work From Home (WFH) practices as a result of Covid-19; and China as the largest source of top-tier AI researchers, with more than half of them working in the US.
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AI in business
Over a quarter of all AI initiatives are already in production and more than one third are in advanced development stages; organizations are reporting an increase in their AI spending this year; top benefits: improved customer experience, greater employee efficiency, and accelerated innovation; top challenges: spending around one third of the AI lifecycle time on data integration and data preparation, lack of staff with necessary expertise, lack of production-ready data, and lack of integrated development environment; around 28% of the AI/ML initiatives have failed [IDC survey of 2,056 IT and line of business decision makers worldwide]
77% of banking executives believe that unlocking the value of AI will be the difference between winning and losing; 28% think AI’s top benefit is improving user experience through greater customer personalization [Temenos]
16% of European companies believe automation through AI and other emerging technologies can help them minimize the impact of Covid-19 [IDC survey, March 23, 2020]
AI and the future of work
The jobs most at risk from pandemic job losses in Europe overlap to some extent with those most vulnerable to displacement through automation: 51 million jobs (22% of total jobs) are at risk from automation and 24 million jobs are at risk of displacement though both Covid-19 and automation (59 million jobs are at risk from Covid-19) [McKinsey Global Institute]
Robotic Process Automation (RPA) software from Blue Prism can process loans in less than two minutes, roughly 30 times faster than a person [WSJ]
Takeda plans to train thousands of staff to build and use software bots for themselves; based on a successful pilot with 22 employees, it estimates that the effort could automate 4.6 million hours of office work per year—the equivalent of roughly 2,000 full-time workers (but Takeda doesn’t see the technology displacing anyone); RPA provider UiPath added 836 new customers in the first quarter, doubling its customer base year-over-year [Wired]
U.S. employers since January have posted a total of 42,682 job ads for positions with an AI skills component, an increase of 14% from the same period last year, according to CompTIA. IDC’s low-end estimate is projecting the number of global AI-related jobs this year at 927,000, up 11% from 2019. IDC’s more optimistic outlook is for 969,000, a 16% gain over last year [WSJ]
An analysis of AI jobs posted in top 12 countries by GDP, July 2015 through March 2019, found 68,959 jobs were in the IT department (an increase of 363%) and 156,294 jobs were in other business areas (an increase of 74%) [Gartner]
54% of Americans would like Work From Home to be their primary way of working and more than 75% said they would like to continue to work remotely at least occasionally; nearly 40% said they feel strongly that their employer should provide employee opt-in remote work options when returning to normal operations [IBM survey of more than 25,000 US adults, April 2020]
74% of CFOs intend to move at least 5% of their previously on-site workforce to permanently remote positions [Gartner survey of 317 CFOs and Finance leaders on March 30, 2020]
37% of jobs in the United States can be performed entirely at home, with significant variation across cities and industries [University of Chicago]
The Life of Data, the fuel for AI
More than 59 zettabytes (59 trillion gigabytes) of data will be created, captured, copied, and consumed in the world this year; the amount of data created over the next three years will be more than the data created over the past 30 years, and the world will create more than three times the data over the next five years than it did in the previous five; by 2024, entertainment data will be 40% of the Global DataSphere and productivity/embedded data will be 29%, stalled somewhat by Covid-19 dynamics; the consumer share of the Global DataSphere will hover around 50% and decline roughly 4% over the next five years, slowly ceding share to the enterprise DataSphere [IDC]
Akamai observed momentous internet traffic growth in March, which can be explained by new guidelines around social distancing and remote working during Covid-19. One of the observed changes is the increase in consumption of internet services over enterprise-connected devices, with a 40% increase during the month. The research also shows an increase of more than 400% in traffic to malware-associated websites.
On average, data wrapping—when a company’s products are “wrapped” in data analytics features and experiences that help and delight customers—represents 26% of the value a company creates from data monetization [MIT CISR]
AI arms race
The US has a large lead over all other countries in top-tier AI research (defined as researchers with papers accepted at NeurIPS 2019), with nearly 60% of top-tier researchers working for American universities and companies; more than two-thirds of the top-tier AI researchers working in the US received undergraduate degrees in other countries; China is the largest source of top-tier researchers, with 29% of these researchers having received undergraduate degrees in China; the majority of those Chinese researchers (56%) go on to study, work, and live in the US [Marco Polo]
AI markets
59% of U.S. healthcare providers will invest in robotic process automation (RPA) in the next three years, up from 5% today [Gartner]
The AI market worldwide will grow from $28.42 billion in 2019 to $40.74 billion in 2020 and $99.94 billion in 2023 [The Business Research Company]
AI quotable quotes
“Buying one-way airline tickets was a good predictor of fraud [in automated detection models]. And then with the covid-19 lockdowns, suddenly lots of innocent people were doing it”—Svetlana Sicular, Gartner
“Only the tech giants and the hedge funds can afford to employ these [AI] people”—an unidentified senior manager at an organization that is neither
“We often hear from medics saying they have a big dataset on one disease or another. But when you ask basic questions about what format the data is in, we never hear from them again”—Dr Pearse Keane, Moorfields Eye Hospital
“There’s a scientific reason we’re not going to get to full self-driving with our current technology. [The] less ambitious stuff—I think that’s much more realistic”—Mary “Missy” Cummings, Duke University
