At first it was hard to see, but in time, economists did indeed find evidence that information technology contributed to boosting economic productivity. 

It’s too soon to expect to see data showing a similar boom from artificial intelligence, today’s big IT revolution. The technology is just becoming industrialized, and many companies have yet to even try to use things such as machine learning in any significant way. 

But it’s not too soon to speculate. There’s no question companies will increasingly use AI technologies of various sorts. AI is now well on its way to being part of how companies function. Every company has tons of data to analyze, and that analysis can benefit from even simple machine learning techniques. And companies have processes, from HR to accounting to sales, that can make use of automation that AI can bring. 

Will all that show up in the numbers around output per employee and such, the measures of productivity?

Though it can’t be ruled out, a couple big obstacles stand in the way of AI having an effect on productivity similar to the PC era.

One issue is that AI is dominated by the companies that are already among the most productive in the world. As MIT economist David Autor and colleagues have written, wealth is increasingly concentrated in the hands of what they term “superstar firms,” a situation of “winner take most,” where “a small number of firms gain a very large share of the market,” firms that are the “more productive” ones.

Those companies include Google and Facebook, and others that, Autor and colleagues show, are much more efficient in terms of their labor force. “Many of the canonical superstar firms such as Google and Facebook employ relatively few workers compared to their market capitalization” because “their market value is based on intellectual property and a cadre of highly-skilled workers.”

Google, Facebook, Apple, Amazon and Microsoft, the largest tech companies in the world, the superstar firms, are precisely the ones that already dominate artificial intelligence globally, the companies at the forefront of deep learning and other forms of cutting-edge AI. In a sense, AI is being used to reinforce productivity that is already vastly above normal.

At the same time, something unfortunate has befallen all the non-superstar firms in the world. Back in the 1980s and 1990s, PCs and related technology were a broad global trend benefitting any company that bought PCs, servers and networking. Productivity was theoretically available to all. 

With the death of Moore’s Law, the decades-long rule of progress in the semiconductor industry, there is less and less technology improvement that’s broadly available in a direct way to every firm. Fundamental research has contracted across the technology industry, and much of what innovation happens is increasingly concentrated in the R&D labs of those same superstar firms. 

As Carnegie Mellon researchers Hassan N. Khan, David A. Hounshell, and Erica R. H. Fuchs wrote in Nature magazine last year, “as advances in semiconductors slow, and downstream firms increasingly pursue application- or domain-specific innovations, technological progress will be increasingly unevenly distributed.” 

That uneven distribution is “in contrast to the industry-wide benefits of advances in the underlying transistor technology” in prior decades.

With superstar firms dominating AI, and broad tech progress no longer evenly distributed, how will AI contribute to a boom? Perhaps it will happen indirectly, a process of “trickle-down” productivity, as ordinary firms adopt the AI technologies provided by Google and Microsoft and Amazon in the cloud. 

Even if productivity doesn’t immediately improve at every firm, improvements could still materialize inside of industries, and as a national or global phenomenon.

It’s important to remember that productivity can take time to materialize. Back in 1987, Nobel Prize-winning economist Robert Solow was the first scholar to point out the apparent absence of IT-led productivity growth. “You can see the computer age everywhere but in the productivity statistics,” he famously wrote. It took another decade or so, but eventually the numbers did show progress.

An AI boom is possible; certainly, it shouldn’t be ruled out. But market concentration and a slowdown in tech innovation broadly speaking will make it more challenging to achieve than was the case for technology revolutions of the past.

Source : https://www.forbes.com/sites/tiernanray/2019/09/26/will-there-be-an-ai-productivity-boom/?ss=ai#7a5047c82916