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

 

But it's not too soon to speculate. There is no question companies will progressively 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 cannot be ruled out, a couple big obstructions stand in the way of AI having an effect on productivity similar to the PC era.

 

One problem is that AI is ruled by the companies that are already among the most productive in the world. As MIT economist David Autor and colleagues have written, wealth is significantly 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 biggest tech companies in the world, the superstar firms, are exactly the ones that already dominate artificial intelligence all over the world, the companies at the forefront of deep learning and other sorts of cutting-edge AI. In a sense, AI is being used to boost productivity that is already greatly 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's less and less technology improvement that is extensively available in a direct way to every firm. Fundamental research has contracted across the technology industry, and much of what innovation happens is progressively more concentrated in the R&D labs of those same superstar firms.

 

With superstar firms ruling 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. Regardless if productivity does not 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 some time to materialize. Back in 1987, Nobel Prize-winning economist Robert Solow was the first scholar to suggest 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 gradually the numbers did show progress. An AI boom is possible; undoubtedly, 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.

 

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