AI company executives see themselves as enhancing workers' livelihoods, not ending them. They argue that desk jobs will become more rewarding as machines take over work that "frankly is not that interesting and is also better done by a machine," explained Stuart Frankel, CEO of Chicago-based Narrative Science.

"A lot of time is being spent staring at spreadsheets and staring at walls of numbers and then taking that, gleaning a little insight, writing up a report and sending it to somebody," Frankel said. His company's advanced natural language processing platform, Quill, can do that.

Narrative Science made headlines in 2012, when it revealed that Quill was writing up earnings reports for Forbes and sports for the Big Ten Network. Beyond simply inserting data into preset phrases, the program tells stories by picking out relevant information from large data sets and putting information in context, Frankel said.

"It can write just about any story that is driven by structured data," Frankel said. The company now focuses on report writing for businesses, including financial and professional services, health care, medical billing and sales. Quill writes suspicious-activity reports for compliance departments and files them with government agencies, creates investment portfolio summaries and issues analyses on topics from real estate to loan risk. And like all technology, it does not need vacation time, a lunch hour or a health care plan.

Frankel argues that Quill's ability to crank out compliance reports, for example, frees up officers to take on more complex fraud investigations. But it is not obvious why computers could not soon take up those, too.

"In principle I understand what it means to do more fulfilling work, and higher-level stuff, but what does that even mean now?" Dhar asked. "Because more fulfilling work earlier would be, let's say, discovering things or finding things or figuring out connections between things. ... But computers can do that as well."

Business software company Salesforce has a tool called Einstein that reads sales representatives' emails and suggests ways for the humans to be more productive. After parsing the messages, Einstein enters information into a database. It generates sales forecasts based on representatives' history and otherwise obliterates administrative tasks that take up their time, according to Jim Sinai, vice president of marketing for Salesforce Einstein. The software also uses more advanced analysis than the "little micro-experiments" that marketers use to determine ad-campaign strategies, allowing employees to focus on more interesting tasks.

"I think that today, if you walk into a marketing org, there's someone in there doing the segmentation and the testing, and I think that they would probably much rather be working on understanding who our target audiences really are and what they want and how to create better [ads] for them," Sinai said. "We're shifting the value of what people do, not necessarily whether they need a job."

But the question is not so much whether they need a job as whether the job needs them. Economists expect automation to further exacerbate income inequality, as the owners of technology, along with the coders developing it, profit while others grow increasingly redundant. The tech industry has minted scores of billionaires, but its impact on job growth has been limited when compared to the blue-chip juggernauts of yesteryear. General Electric, for example, has a market value of $250 billion, a far cry from Google's $650 billion. But GE has 295,000 employees, while Google has just 74,000.

Still, people are complicated. And despite the advances, computers are not necessarily adept at reading them. "There are lots of jobs that involve an ability to deal with human beings," Dhar says. "Machines can't do that very well right now."