Today it’s become an article of faith that everything moves faster. Business pundits tell us that we’re living in a VUCA world (Volatile, Uncertain, Complex and Ambiguous). These are taken as basic truths that are beyond questioning or reproach. Yet are things actually moving any faster than in earlier eras? The evidence is surprisingly scarce.

Certainly productivity isn’t growing any faster. The Bureau of Labor Statistics reports that productivity growth today stands at about the post-war average, significantly slower than the period before 1970. At the same time, an analysis by the Federal Reserve Bank found that business dynamism is decreasing while average markups are increasing. 

The problem, as I noted in my book Mapping Innovation, is that innovation isn’t an event, but a process of discovery, engineering and transformation—and it’s the last part that takes the longest. History shows that it takes decades to go from a breakthrough to a measurable impact, because figuring out how to put a new idea to good use is much harder than people realize. 

The 40-year wait for electricity’s economic payoff

In 1882, just three years after the legendary development of his light bulb, Thomas Edison opened his Pearl Street Station, the first commercial electrical distribution plant in the United States. By 1884 it was already serving over 500 customers.

Up till that point, electric light was mostly a curiosity. While a few of the mighty elite could afford to install generators in their homes—J.P. Morgan was one of the very first—that was beyond the means of most people. Electrical transmission changed all that, and in the ensuing years much of the country was wired up.

Yet as the economist Paul David explains in The Dynamo and the Computer, electricity didn’t have a measurable impact on the economy until the early 1920s, 40 years after Edison’s first plant was built.  The problem wasn’t with electricity itself—Edison quickly expanded his distribution network, as did his rival George Westinghouse—but with a lack of complementary technologies.

At first, the major application for electricity was electric light, which had a limited effect. To truly impact productivity, factories needed to be redesigned and work itself had to be reimagined. Later, household appliances like refrigerators and washing machines were invented, expanding electricity’s reach. Productivity would soar for another 50 years.

The internal combustion engine followed a similar path. The automobile actually had limited economic impact in the age of the corner store. It was the development of the supermarket, and later the shopping mall and the category killer store, that made the new mode of transportation truly transformational.

Productivity paradoxes, then and now

It’s been clear for some time now that we’ve been in the midst of a second productivity paradox. The first, which lasted from the early 1970s to the mid-1990s, saw diminished productivity gains amid increased investment in computer technology and prompted economist Robert Solow to note, “You can see the computer age everywhere but in the productivity statistics.”

The first productivity paradox dumbfounded economists because it violated a basic principle of how a free market economy is supposed to work. If profit-seeking businesses continue to make substantial investments, you’d expect them to see a return. Yet with IT investment in the 70s and 80s, firms continued to increase their investment with negligible measurable benefit.

A paper by researchers at the University of Sheffield sheds some light on what happened. First, productivity measures were largely developed for an industrial economy, not an information economy. Second, the value of those investments, while substantial, represented only a small portion of total capital investment. Third, businesses weren’t necessarily investing to improve productivity, but to survive in a more demanding marketplace.

In 1996, with the rise of the Internet, productivity growth began to boom again but then disappeared just as abruptly in 2004. Despite the hype surrounding things such as Web 2.0, the mobile Internet and, most recently, artificial intelligence, productivity growth has remained sluggish for the last two decades. 

Nobody really knows exactly why this is true, but the most likely explanation is that the present and future are very much like the past. While the advances in digital technology are truly astounding, the world is not digital. Most of the economy is still rooted in the homes we live in, the vehicles we ride in, the clothes we wear, the food we eat and, increasingly, the services that keep us healthy. All the gadgets and apps simply don’t have that much impact. 

The long wait for quantum computing, AI and synthetic biology

As impressive as the breakthroughs in the past have been, the future promises to be even more transformative. Generative AI has been adopted faster than either the personal computer or the internet. Quantum computing promises to be exponentially more powerful than its digital predecessor for many applications. Synthetic biology technologies like CRISPR and mRNA will give us cures for diseases  that have plagued humanity since the beginning of time. 

Yet here again, the reality doesn’t meet the hype. Despite all the enthusiasm about AI, there is very little indication that it is improving productivity and there is even some evidence that “AI workslop” is damaging it. Quantum computing is still years away from proving it can be useful, and while CRISPR has genuinely produced miracle cures, they are still far too expensive to be practical. 

Part of the problem is that, as Paul David explained in his paper, when new technologies first emerge, we’re not very good at using them. Technologies don’t implement themselves, so there’s always a learning curve as people who understand the technologies learn to work effectively with people who understand the problems they can solve. 

Another issue is that technologies need ecosystems. Consider the case of the automobile. It took time for infrastructure, such as roads and gas stations, to be built. Improved logistics reshaped supply chains and factories moved from cities in the north—close to customers—to small towns in the south, where labor and land were cheaper. That improved the economics of manufacturing further.

Ideas that change the world always arrive out of context for the simple reason that the world hasn’t changed yet. Identifying where a new technology fits in and scaling it to impact takes time. 

Innovation isn’t about technology or ideas. It’s about solving problems

People tend to think of innovation as a single event, like when Alexander Fleming, returning from a summer vacation, noticed that a strange mold had killed his bacterial cultures and, studying the matter further, discovered penicillin. What is rarely mentioned is that what Fleming discovered had no practical value and couldn’t have cured anyone.

It was just a mold secretion—unstable, unusable, with no way to produce it at scale. So it was largely ignored, buried in a medical journal for over a decade. Then a different team, led by Howard Florey and Ernst Chain, picked it up. Collaborating with American labs, they turned it into a viable treatment, and in 1945—more than 15 years after Fleming’s “Eureka moment”—penicillin became commercially available.

Simply announcing a breakthrough or devising a solution doesn’t immediately translate into impact. Technology doesn’t implement itself. It takes time for people who understand new solutions to learn how to collaborate effectively with people who deeply understand the problems they can solve. That’s not a technology problem. It’s a human problem. And no amount of computer chips or software code will make it go significantly faster.

That’s why we need to take the claims of the Silicon Valley types with a grain of salt. Yes, artificial intelligence will likely be transformative, as will quantum computing, CRISPR, mRNA and probably other things as well. But there will be no shortage of wrong turns and blind alleys along the way. 

Breakthroughs can happen in an instant, but genuine transformation still happens at human speed.