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Image: Andrey Suslov/Getty Images; murniati/Adobe Stock
Every year since 2010, I’ve posted an article about what trend I expect to dominate the next twelve months. Throughout the 2010s, these forecasts usually focused on emerging technologies or new currents in management thinking. But around 2020, that began to shift. The annual trends are increasingly centered on how we cope with change rather than the change itself.
Last year my trend was “The Coming Realignment.” History tends to propagate at a certain rhythm and then converge and cascade around certain points. Years like 1776, 1789, 1848, 1920, 1948, 1968, 1989—and, it seems, 2020—mark these inflection points. The years that follow are usually spent absorbing the shock and navigating the consequences.
Today, everything is up for question. Will AI boom or bust? Will it take our jobs or bring new prosperity? What kind of economic system will we adopt for the future? We are in the midst of a great realignment. What we know from previous inflections is that what comes after will be profoundly different from before. What we most need to watch is our institutions.
Today, the AI investment boom is without a doubt the single biggest factor propping up the US economy. Just this year, tech giants are expected to invest roughly $364 billion in the technology. And the spending won’t stop there. McKinsey projects that building AI data centers could add up to $5.2 trillion in investment by 2030.
This boom is different from what we’ve seen in the past because the main investors aren’t speculators or startups, but some of the world’s most profitable companies, including Alphabet, Meta, and Microsoft. Unlike in past cycles, if the industry hits a downturn, there will still be tens of billions of dollars in annual profits to cushion the blow.
Still, as investor Paul Kedrosky points out, there are reasons to worry. Investment in data center infrastructure has already surpassed the peak of the dot-com boom and is beginning to approach levels last seen during the railroad frenzy of the 19th century. Also, 60% of the cost of those data centers goes to AI chips, which have a useful life of only about three years.
That means this is not a boom that can wait decades to pay off. If today’s investments don’t generate returns in the near future, much of the infrastructure could fully depreciate before delivering meaningful profit. In practical terms, unless tech firms can earn more than $200 billion in profit—on these investments alone, not from their core businesses—they will be underwater. And as investment accelerates, that bar only rises.
Kedrosky also notes signs of growing systemic risk. Increasingly, tech giants are choosing to finance their infrastructure build-outs with Enron-like special-purpose vehicles. These structures cost more but keep the debt off their balance sheets. That risk, in turn, is increasingly being passed to more traditional investors, including REITs.
A 2023 report by the World Economic Forum, analyzing 673 million jobs, predicted structural job growth of 69 million jobs and a decline of 83 million, an overall decrease of 14 million jobs. An IMF analysis found that 40% of global employment is exposed. In an interview with Axios, Anthropic CEO Dario Amodei said AI could wipe out half of all entry-level white-collar jobs in the next one to five years.
Yet more grounded economic analyses suggest a much more modest impact. A study by the St. Louis Fed suggests a 1.1% increase in aggregate worker productivity, with much of that increase concentrated in the tech sector. A paper by Nobel laureate Daron Acemoglu, which looks at total factor productivity (TFP), a measure which takes use of capital into account, sees a 0.66% increase over 10 years, translating to a 0.064% increase in annual TFP growth.
A recent McKinsey report takes an optimistic view. While noting that many routine office and production jobs are likely to disappear, those that leverage technical, social and emotional skills are likely to flourish, just as Autor has predicted. However, there is reason to suspect that optimists may be merely extrapolating from historical trends that may no longer apply.
There’s no guarantee that the future will look like the past. An analysis in Harvard Business Review suggested that AI could disrupt the non-routine creative work that, to this point, has been hard to automate. Meanwhile, research in Science has found that, although AI may enhance individual creative work, it diminishes the diversity of novel output, potentially stifling the very innovation it aims to support.
Before 1789 the world was ruled by the divine right of kings and the feudal system. Yet that year would prove to be an inflection point. The American Constitution, the French Revolution, and the first Industrial Revolution, already underway since the introduction of the steam engine in 1776, together created a fundamental realignment of power.
These forces would build and clash for decades until things came to a head in the revolutionary year of 1848. Today, we seem to be in a similarly liminal space, as we decide what kind of future we want to live in. The next century and a half would be dominated by the tensions between socialism and capitalism.
When the Berlin Wall came down in 1989, the West was triumphant. Communism was exposed as a corrupt system bereft of any real legitimacy. Yet for anyone paying attention, communism had long been discredited. As far back as the 1930s, Stalin’s disastrous collectivization and industrialization campaigns had led to mass starvation. By the 1970s, Soviet total factor productivity growth had gone negative, meaning more investment actually brought less output.
Yet today, it is capitalism that finds itself under siege from all sides. Leftist progressives like Bernie Sanders and Zohran Mamdani advocate for reining in the private sector and creating a bigger safety net. The mercantilist American president rails against free trade and nationalizes the means of production. Christian nationalists openly call for theocratic rule.
At the same time, a new cadre of theorists has emerged whose ideas don’t fit the traditional right-left paradigm. New Right thinkers such as Curtis Yarvin and Patrick Deneen call for wholesale reordering of society. On the more technocratic side, a new school of thought is emerging that is associated with Ezra Klein and Derek Thompson’s book Abundance.
In Why Nations Fail, economists Daron Acemoglu and James Robinson explain why the fate of nations rests less on innate factors such as geography, culture, or climate and more on the quality and types of institutions they build. In particular, they make the distinction between inclusive institutions and extractive institutions.
Inclusive institutions protect property rights broadly across society, establish fair competition, and reward innovation. Extractive institutions, on the other hand, concentrate wealth in the hands of a small elite who exploit the broader population. These elite players control resources and use state power to enrich themselves at society’s expense.
We are clearly in a liminal period in which we are struggling to adapt to shifts in technology, economics, and identity. Will AI oppress or empower regular people? Will we trade openly or retreat behind national barriers? Will we focus primarily on our local communities or see ourselves as citizens of a larger planet?
As ever, there will be no shortage of pundits predicting the paths the future will take. Many of their narratives will be persuasive—but also mutually contradictory. The real tell will be what kinds of institutions we build and which ones we allow to decay or be destroyed outright. Are we creating institutions that strengthen rights and the rule of law, or those that serve the powerful?
The outcome is still unclear, but the lines of battle have been drawn. If you want to know what to expect in the near to mid-term, pay less attention to predictions about technology, politics, or ideology and focus instead on institutions. Those are what create the norms and rituals that will shape the behaviours of the future.
ABOUT THE AUTHOR
Greg Satell is Co-Founder of ChangeOS, a transformation & change advisory, a lecturer at Wharton, an international keynote speaker, host of the Changemaker Mindset podcast, bestselling author of Cascades: How to Create a Movement that Drives Transformational Change and Mapping Innovation, as well as over 50 articles in Harvard Business Review. You can learn more about Greg on his website, GregSatell.com, follow him on Twitter @DigitalTonto, watch his YouTube Channel and connect on LinkedIn.