Why are new technologies not making us more productive?

For years, corporate America has believed that cloud computing and artificial intelligence will boost productivity-rich productivity. This belief has inspired the flow of venture financing and spending companies. And the winnings, supporters insist, will not be limited to a small group of technology giants, but will spread throughout the economy.

This has not happened yet.

Productivity, defined as the cost of goods and services produced per hour of work, fell sharply in the first quarter of this year, the government said this month. Quarterly figures are often volatile, but the report seemed to shatter earlier hopes that the recovery in productivity had finally begun, which was helped by accelerated investment in digital technology during the pandemic.

Productivity growth since the pandemic has now been about 1% a year, at a meager rate since 2010 – and well below the last period of significant improvement, from 1996 to 2004, when productivity grew by more than 3% a year.

The economy is growing not only through increased capital and labor. Another important component is the nation’s skill in creating and commercializing innovation, making investment and workers more productive.

It would seem that a small percentage of productivity growth can significantly affect a country’s wealth and standard of living over time. Even an additional annual productivity growth of 1% over several years, by 2024, will result in an additional $ 3,500 per capita income for Americans, McKinsey & Co. estimated. in last year’s report. The average annual increase of 3.8% from 1948 to 1972 was the engine of the nation’s post-war prosperity.

Productivity is not a cure for economic ills. “Even if optimism about this wave of digital technology proves to be justified, it doesn’t mean there will be a real drop in preferences,” said Laura Tyson, a professor at the Haas School of Business at the University of California, Berkeley. chairman of the Board of Economic Advisers in the Clinton administration.

But a less productive economy is a smaller economy with fewer resources to address social issues such as inequality.

The current performance puzzle is the subject of heated debate among economists. Robert Gordon, an economist at Northwestern University, is a major skeptic. Today’s artificial intelligence, he said, is mostly an image recognition technology that scans huge clusters of words, images and numbers. His exploits, according to Gordon, are “impressive but not transformative,” as was the case with electricity and the internal combustion engine.

Eric Brinolfsson, director of Stanford University’s Digital Economics Laboratory, is the leader of the Optimist Camp. He admits he was somewhat disappointed that performance improvements are yet to be seen, but is convinced it is only a matter of time.

“Real change is happening. There is a tidal wave of transformation, ”Brinolfsson said. “We see more and more facts on the ground.”

It will probably be years before there will be a final response to the performance debate. Brinolfson and Gordon made a “long bet” last year, and the winner was determined in late 2029. But industry-level and company-level research using data ranging from Census Bureau business surveys to online vacancy lists shows a pattern of diffusion and barrier technology.

Leaders are mostly large companies that have been investing in digital technology for years, and young, high-growth companies that are often supported by venture capital. Cloud computing is quite common, but not the most advanced technology like AI applications.

Some experts argue that limited distribution is not so surprising at this stage, given that three-quarters of businesses in the U.S. are small, with less than 10 employees.

At Anthem, a health insurance company whose plans cover more than 45 million people, now about 75% of customer issues are resolved through digital channels, including a web portal, a mobile app and speech recognition software. Three years earlier, the digital share was about 30%. The technology of answering questions, which helps people perform basic tasks such as checking the status of a claim, paying bills or finding a doctor, is partially animated by AI.

Digital automation has eliminated 10 million phone calls that could make Anthem call centers, according to Rajiv Ronanki, president of digital platforms.

Anthem, which is changing its corporate name next month to Elevance Health, is not cutting customer service staff. But the role of these workers and the way their work is measured has changed. The traditional measure of call center performance is “call processing time,” and the less time per call, the better. Now Anthem wants its customer service staff to solve customer problems with one call, if possible, rather than transferring them to another department.

Many of its call center staff have received additional training to become what Anthem calls “care navigators”. Now measuring their effectiveness includes solved problems and consumer satisfaction surveys. With this broader set of measures, Ronanki said, the company’s contact agents are 30-40% more productive. According to him, adding skills and reworking work is just as important as improving technology.

“Building technical capacity is just the beginning,” Ronanki said.

It takes time for new technologies to expand and people to understand how best to use them. For example, the electric motor, which was introduced in the 1880s, did not provide a significant increase in performance until the 1920s, when a mass-produced assembly line reorganized work around technology.

The personal computer revolution began in the 1980s. But it wasn’t until the second half of the 1990s that economic productivity really increased as these machines became cheaper, more powerful and connected to the Internet.

The revival of the 1990s was fueled by a leap in investment in technology by companies and venture capitalists, especially the Internet and web startups. Similarly, software spending in the United States has more than doubled to $ 385 billion over the past decade as companies invest in digitizing their operations, research firm IDC said.

According to PitchBook, which tracks funding, venture capital investment in artificial intelligence startups around the world increased by more than 80% last year to $ 115 billion.

Cresta is a startup with artificial intelligence that tries to address the current issue of performance. In 2020, Cresta introduced its original product: software for referrals and real-time training for call center agents. Its technology digests vast amounts of text and voice conversations to identify patterns of behavior and answers to questions that solve customer problems or generate sales.

The goal is not to replace workers, but to increase their productivity, said Zayd Ann, co-founder and CEO of the company. Cresta’s offer, he said, was made possible by recent advances in the power and speed of AI software, which he called “changing the game”.

Cresta has 200 employees, has raised more than $ 150 million in venture capital and has dozens of corporate clients including Verizon, Cox Communications and Porsche.

CarMax, the country’s largest retailer of used cars, began testing Cresta software in December. The artificial intelligence experiment took place after years of investment to translate the company’s computer operations to more flexible cloud systems, said Jim Coots, executive vice president of strategy, marketing and products.

Customer inquiries at the CarMax Contact Center are usually lengthy. Used cars of different years, models, features and driving histories, as well as financing plans for what is a major purchase, vary. The range of issues is virtually unlimited, Lyski said, so purely automated communication is not an option.

But a computing assistant who could help sort out automotive complexity by offering suggestions and real-time information was appealing. For the first time, Cresta trained with CarMax contact center data, and the experiment began with its live chat agents having text conversations with customers.

The experience is encouraging, Coot said. Response time, conversion to sales and shortened session time increased by approximately 10%. And the system keeps learning and getting better. The company has launched a pilot project with voice call agents, increasing the total number of agents using AI technology to 200.

One concern, Lyski said, was how employees would react to having artificial intelligence behind them. Would it be good enough to be seen as a desirable helper rather than an annoying distraction? The reaction was positive, he said.

Cresta started with contact centers as a large early market because it is a time consuming area where AI can be applied relatively quickly and productively. But Enam sees that its “real-time intelligent intelligence” can potentially be useful in a wide range of knowledge, acting as a smart helper in everything from hiring to product development.

“This technology has a more general purpose than we see now,” he said.

Brinolfson of Stanford is betting that this is true, and Gordon of the Northwest is questionable.

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