BANGALORE, India — Fifteen years ago I came to Bangalore, India’s Silicon Valley, to do a documentary on outsourcing. One of our first stops was a company called 24/7 whose main business was answering customer service calls and selling products, like credit cards, for U.S. companies half a world away.

The beating heart of 24/7 back then was a vast floor of young phone operators, most with only high school degrees, save for a small pool of techies who provided “help desk” advice. These young Indians spoke in the best American English, perfected in a class that we filmed, where everyone had to practice enunciating “Peter Piper picked a peck of pickled peppers” — and make it sound like they were from Kansas not Kolkata.

The operations floor was so noisy from hundreds of simultaneous phone conversations that 24/7 installed a white-noise machine to muffle the din, but even then you could still occasionally hear piercing through the cacophony some techie saying to someone in America, the likes of: “What, Ma’am? Your computer is on fire?”

Well, 24/7’s founders — P.V. Kannan and Shanmugam Nagarajan — invited me back last week for an update. Their company is now called [24] and their shop floor is so quiet that the operators are encouraged to play their own music. The only noise is from the tapping on keyboards, because every query — from customers of U.S. retailers, banks and media companies — is coming in by text messaging from smartphones, tablets, desktops and laptops.

These text queries are usually answered first by a [24] chatbot, or “virtual agent,” powered by A.I. (artificial intelligence) and only get handed over to a person using H.I. (human intelligence) if the chatbot gets stuck and can’t answer. The transformation of [24] from perfecting its accents to perfecting its insights illustrates in miniature how A.I. is transforming the whole work landscape.

Virtually all of the [24] human operators today have college degrees, because they need to be able to text with good grammar in English, understand the interaction between the chatbot and the person calling for service and communicate with expertise and empathy when the chatbot runs out of answers.

At the training class I sat in on last week, Peter Piper was gone. He was replaced by a competition among trainees over who could grasp first exactly when the chatbot — which [24] calls by the woman’s name Aiva, for Artificially Intelligent Virtual Assistant — could no longer understand the “intent” of the customer and what that intent actually was.

“It’s a cool job,” Santhosh Kumar, a 45-year-old conversation designer, who came up through the 24/7 system, said to me. “You are designing what the chatbot should be saying to the customers.” It is all about “how to make a computer sound like a human.” Banks want their bots to be formal; retailers prefer more conversational bots.

Another new term I learned here was “containment.” That measures how deep into a conversation your chatbot can go without having to hand the customer over to a human agent. A company’s “containment rate” is like its A.I. batting average.

Today, [24]’s containment rate ranges from 20 percent to 50 percent of queries, depending on the company it is serving. Its goal is 80 percent. As the bots grasp more of each customer’s intent, the skilled humans are redeployed to more complex services and sales, and that, said Kannan, “turns into better sales and keeping customer satisfaction high.”

His chatbots, Kannan explained, are built with a “negative sentiment detector” to identify angry customers, so “we auto-generate sympathy when we can,” but for the most part “complexity and empathy” are left to the humans.

So what will a country like India, with so much unskilled labor, do about this challenge? It’s coming. But so is a possible savior. It’s also called technology and A.I.

While technology taketh it also giveth. India’s newest high-speed mobile network, Jio, in just the past couple years dramatically slashed the price of cellphone connectivity. This has taken smartphone diffusion much deeper into Indian society than ever before, connecting those making only a few dollars a day to the mobile network, and creating a vast new tool kit to lift them from poverty.

In Bangalore, I visited the EkStep Foundation. It was started by Nandan Nilekani, a co-founder of Infosys; his wife, Rohini; and the social entrepreneur Shankar Maruwada. EkStep (“One Step” in Hindi) argued that if India’s current youth bubble gets left behind by globalization and technology, India’s future will be tied to a giant ball and chain for the rest of the century.

EkStep has created a free, open-source digital infrastructure called Sunbird for making personal learning platforms. The Indian government leveraged it to create a national teachers’ platform, Diksha, which enables different states to put QR codes linked to all kinds of topics in their millions of old paper textbooks.

So don’t write the conclusion of this story yet. Thanks to A.I., Peter Piper just might be able to pick a lot more than a peck of pickled peppers — so many more that not only the top of India’s society will rise, but also the bottom.

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