Coronavirus will finally give artificial intelligence its moment
(Bloomberg Opinion) -- For years, artificial intelligence seemed on the cusp of becoming the next big thing in technology — but the reality never matched the hype. Now, the changes caused by the Covid-19 pandemic may mean AI’s moment is finally upon us.
Over the past couple of months, many technology executives have shared a refrain: Companies need to rejigger their operations for a remote-working world. That’s why they have dramatically increased their spending on powerful cloud-computing technologies and migrated more of their work and communications online.
With fewer people in the office, these changes will certainly help companies run more nimbly and reliably. But the centralization of more corporate data in the cloud is also precisely what’s needed for companies to develop the AI capabilities — from better predictive algorithms to increased robotic automation — we’ve been hearing about for so long. If business leaders invest aggressively in the right areas, it could be a pivotal moment for the future of innovation.
To understand all the fuss around artificial intelligence, some quick background might be useful: AI is based on computer science research that looks at how to imitate the workings of human intelligence. It uses powerful algorithms that digest large amounts of data to identify patterns. These can be used to anticipate, say, what consumers will buy next or offer other important insights. Machine learning — essentially, algorithms that can improve at recognizing patterns on their own, without being explicitly programmed to do so — is one subset of AI that can enable applications like providing real-time protection against fraudulent financial transactions.
Historically, AI hasn’t fully lived up to its hype. We’re still a ways off from being able to have natural, life-like conversations with a computer, or getting truly safe self-driving cars. Even when it comes to improving less advanced algorithms, researchers have struggled with limited datasets and a lack of scaleable computing power.
Still, Silicon Valley’s AI-startup ecosystem has been vibrant. Crunchbase says there are 5,751 private-held AI companies in the U.S. and that the industry received $17.4 billion in new funding last year. International Data Corporation (IDC) recently forecast that global AI spending will rise to $96.3 billion in 2023 from $38.4 billion in 2019. A Gartner survey of chief information officers and IT leaders, conducted in February, found that enterprises are projecting to double their number of AI projects, with over 40% planning to deploy at least one by the end of 2020.
As the pandemic accelerates the need for AI, these estimates will most likely prove to be understated. Big Tech has already demonstrated how useful AI can be in fighting Covid-19. For instance, Amazon.com, Inc. partnered with researchers to identify vulnerable populations and act as an “early warning” system for future outbreaks. BlueDot, an Amazon Web Services startup customer, used machine learning to sift through massive amounts of online data and anticipate the spread of the virus in China.
Pandemic lockdowns have also affected consumer behavior in ways that will spur AI’s growth and development. Take a look at the soaring e-commerce industry: As consumers buy more online to avoid the new risks of shopping in stores, they are giving sellers more data on preferences and shopping habits. Bank of America’s internal card-spending data for e-commerce points to rising year-over-year revenue growth rates of 13% for January, 17% for February, 24% for March, 73% for April and 80% for May. The data these transactions generate is a goldmine for retailers and AI companies, allowing them to improve the algorithms that provide personalized recommendations and generate more sales.
The growth in online activity also makes a compelling case for the adoption of virtual customer-service agents. International Business Machines Corporation estimates that only about 20% of companies use such AI-powered technology today. But they predict that almost all enterprises will adopt it in the coming years. By allowing computers to handle the easier questions, human representatives can focus on the more difficult interactions, thereby improving customer service and satisfaction.
Another area of opportunity comes from the increase in remote working. As companies struggle with the challenge of bringing employees back to the office, they may be more receptive to AI-based process automation software, which can handle mundane tasks like data entry. Its ability to read invoices and update databases without human intervention can reduce the need for some types of office work while also improving its accuracy. UiPath, Automation Anywhere and Blue Prism are the three leading vendors in this space, according to Goldman Sachs, accounting for about 36% of the roughly $850 million market last year.
More imaginative AI projects are on the horizon. Graphics semiconductor-maker NVIDIA Corporation and luxury automaker BMW Group recently announced a deal where AI-powered logistics robots will be used to manufacture customized vehicles. In mid-May, Facebook said it was working on an AI lifestyle assistant that can recommend clothes or pick out furniture based on your personal taste and the configuration of your room.
As with the mass adoption of any new technology, there will be winners and losers. Among the winners, cloud-computing vendors will thrive as they capture more and more data. According to IDC, Amazon Web Services was number one in infrastructure cloud-computing services, with a 47% market share last year, followed by Microsoft at 13%.
But NVIDIA may be at an even better intersection of cloud and AI tech right now: Its graphic chip technology, once used primarily for video games, has morphed into the preeminent platform for AI applications. NVIDIA also makes the most powerful graphic processing units, so it dominates the AI-chip market used by cloud-computing companies. And it recently launched new data center chips that use its next-generation “Ampere” architecture, providing developers with a step-function increase in machine-learning capabilities.
On the other hand, the legacy vendors that provide computing equipment and software for in-office environments are most at risk of losing out in this technological shift. This category includes server sellers like Hewlett Packard Enterprise Company and router-maker Cisco Systems, Inc.
We must not ignore the more insidious consequences of an AI renaissance, either. There are a lot of ethical hurdles and complications ahead involving job loss, privacy and bias. Any increased automation may lead to job reductions, as software and robots replace tasks performed by humans. As more data becomes centrally stored on the cloud, the risk of larger data breaches will increase. Top-notch security has to become another key area of focus for technology and business executives. They also need to be vigilant in preventing algorithms from discriminating against minority groups, starting with monitoring their current technology and compiling more accurate datasets.
But the upside of greater computing power, better business insights and cost efficiencies from AI is too big to ignore. So long as companies proceed responsibly, years from now, the advances in AI catalyzed by the coronavirus crisis may be one of the silver linings we remember from 2020.