Rikap’s analysis rests on the centrality of “intangible assets” to contemporary corporate power. Tangible assets are physical commodities: when they are bought and sold on the market, ownership transfers from the producer to the buyer. Intangible assets work differently. They are commodified forms of knowledge, with companies using patents and other legal instruments to extract intellectual rents for usage.

Not only does ownership never change hands, but the owner of the intangible asset continues to accrue more data (and therefore more value) while it is being used (rented) by others. This provides a new stream of knowledge that can subsequently be turned into more intangible assets.

There is a tendency for the “knowledge predators,” as Rikap describes them, to concentrate their control of intangible assets over time, due to key structural advantages. These companies can innovate better than potential competitors, because innovation requires financial and intellectual resources that are predominantly in their hands.

In the context of AI development, they also have a radically enhanced capacity to process data and extract information from that data. Finally, they also have the power of the platform, where “network effects” generate an intrinsic tendency toward monopolization. Given all this, it’s little wonder that the concentration and centralization of knowledge, and therefore capital, is advancing so rapidly.

Rikap has copious evidence to justify her bold claims about “intellectual monopolies” in the data age. The individual research and development (R&D) expenditures of Amazon, Google, Microsoft, and Meta are all greater than those of every country with the exception of the United States and China. The number of small firms usurping big firms has fallen by half in the first quarter of this century.

Rikap’s most important claim may be one that cannot be fully captured in statistics. She insists that Amazon, Google, and Microsoft are able to effectively control companies which they do not own, by means of the “cloud.”

Why is the cloud so important? Because it consists of the infrastructure that the rest of the digital economy relies upon to function. Amazon, Google, and Microsoft own around 65 percent of the global public cloud market. This means that most of the other economic players are paying an intellectual rent to these three companies for data storage and processing power, so-called infrastructure-as-a-service.

Moreover, software, platforms, and datasets are all sold as cloud services. Most companies and even states that have sought to bypass the cloud hegemons by establishing their own private cloud networks have given up before long. This is due to the costs involved and the risks of falling behind technologically.

Crucially, the relationship between a company and a cloud provider is not like the typical one between a principal entity and a subcontractor, where the subcontractor is in the subordinate position and has limited insight into the operations of the principal entity as a whole. In the case of the cloud provider, the dynamic is inverted: the provider has the data to see how the whole value chain works, while the company by which they are contracted has only “fragmented and marginal” knowledge. As Rikap puts it: “The cloud hegemons alone control — and profit from — the full spectrum of knowledge generated within the system.”

Big companies are aware of their subordinate position to the cloud hegemons, but they have limited scope to break free. There are major costs involved for companies that ditch one cloud provider for another, as their services are designed to be “sticky.” The spread of AI is only increasing their control, because every company that integrates AI into their operations needs data processing power (“compute”) for their core operations, which they get from the cloud.

Even major tech companies like Nvidia and Meta are in some ways ensnared by the cloud giants. A digital technology director at Santander, one of Europe’s biggest banks, made the following comment to Rikap about Amazon, Google, and Microsoft: “You feel the pressure because you play by their rules, their timing and their processes.”

What is the relationship between states and Big Tech? In contrast with the postwar era, when the internet and semiconductors first emerged, the largest tech firms in the United States are not reliant on the state for contracts, nor for R&D funding. In fact, the US government itself is reliant to a large degree on Big Tech, especially the cloud hegemons, because it has few alternative supply sources upon which to draw. There has been a shift in the balance of power between the state and capital in the United States.

For now, the US “tech-industrial complex” is working together relatively seamlessly with the state: Big Tech is offered wide access to the US government, while that government in turn resists pressure to regulate Big Tech at home and abroad. Champions of this partnership often present it as being in the best interests of everyone to improve economic performance across the US economy. However, the evidence for broad productivity gains are few and far between.

It is more plausible to assume that the key ambition is to empower US imperialism by drawing as much of the world as possible into a relationship of technological dependency. This allows Silicon Valley firms to appropriate value from the rest of the world “as they capture technologies that are based on globally co-created data and knowledge.” Rikap believes that the digital sovereignty of the vast majority of nations has already been “significantly eroded.”

The threat posed by American tech hegemony could not be clearer. How have governments responded to this threat? Rikap finds that the European Commission’s strategy, which has focused on regulating “gatekeepers” and supporting the development of the European tech industry, has placed “too many hopes on market forces and competition.”

In India, attempts to use public-private partnerships to build AI “gigafactories” are still dependent on partnerships with US tech firms. Brazil has sought to build a public intermediate layer to provide computing services to the public sector, but it would also still ultimately be reliant on US cloud giants.

China stands out as the only country to have built a sovereign tech stack, including its own cloud ecosystem. This makes it a potential alternative partner for other countries seeking to reduce their dependency on Silicon Valley.

However, Rikap is skeptical about the idea of China as an alternative model, arguing that the Chinese approach has been based on “largely imitating US technologies.” This imitation policy means that China is always playing catch-up with US tech companies. It is also replicating many of the same problems those companies have generated, including the formation of similar intellectual monopolies.

While this may well be true, Rikap gives little consideration to the fact that the balance of power between the state and capital in China differs from the situation in the United States. Xi Jinping’s “Big Tech crackdown” in 2020–21, which forced tech companies to reorient toward the broader economic goals of the state, exemplifies this point.

In addition, as Nick Srnicek points out in his recent book on AI, while China may still lag behind the United States at the frontier of AI development, that does not mean we can observe the same picture when it comes to AI adoption. In fact, Beijing has been focusing on how to diffuse AI across the economy. This focus on adoption may lead to significant differences in innovation patterns emerging between China and the United States over the long term.

Nonetheless, Rikap may be right in warning the rest of the world to avoid replacing American tech dependencies with Chinese ones. That still leaves difficult questions over how to build digital sovereignty when AI requires scale to be effective, a scale that many countries may not be capable of reaching alone.

Rikap makes the case for a publicly owned alternative, which should be governed as an “international commons,” reflecting the fact that knowledge is cocreated beyond borders. That sounds great, but it raises obvious questions about political agency: in a world where democracies are almost entirely national in character, where is the demos that could produce such a significant rupture with American tech hegemony at international level?

We have to face a harsh reality: to the extent that the international political sphere meaningfully exists, it is either paralyzed (the UN, BRICS) or dominated by the very tech oligarchs who we want to get rid of (see Davos, for example).

More realistically, Rikap suggests that a starting point for developing a popular digital sovereignty would be to prevent companies that use “black box” technologies from accessing public contracts, and to start the process of building public alternatives by focusing on the health care sector in particular. Baby steps, for sure, but it’s important to demonstrate that ruptures with US cloud hegemony, however small, are possible.

The Rulers is the latest in a series of books offering proof that modern technology is strengthening the global power of the United States. If Adam Tooze’s Crashed opened our eyes to the importance of the Federal Reserve’s control over dollar swap lines for the rest of the world, Rikap’s book draws our attention to the importance of the cloud for contemporary American geoeconomic power.

This emphasis on American supremacy jars with the prevailing narrative about the United States, a narrative that has grown more prevalent since the Iran war began. According to this view, the United States is in terminal decline, as proven by the fact that it is increasingly unable to exercise its will over other countries, to the point that a mid-level power like Iran can close one of the world’s most important shipping routes. How can the United States both be increasingly powerful internationally and at the same time in rapid decline?

It may be the case that we need more nuance to square this circle. It’s possible to believe that the United States does possess new geopolitical weapons in the highly digitized realms of tech and finance, while at the same time it is losing ground in the more materially grounded realms of manufacturing and critical raw materials, where China has global primacy. Of course, these are just different ends of the one global value chain: tech and finance are ultimately dependent on the material world.

This brings us back to the starting premise of Rikap’s argument, which is that intangible assets sit above tangible assets in terms of importance for corporate power. That may be true when comparing the power of one corporation over another, but does it still hold when we consider the power of one country in relation to its rivals?

The United States can only continue to be a dominant power if it has a reliable supply of critical raw materials and dependable manufacturing capacity. We saw evidence of US vulnerability to Chinese-dominated critical raw materials when Donald Trump had to back away from a tariff war with China for fear of being cut off from resources that the United States in general, and Silicon Valley in particular, needs.

While modern technology has increased the global reach of US tech companies, it has also fundamentally changed modern warfare in a way that puts American assets, including those of Big Tech, in greater jeopardy. Iran’s ability to attack US radars and client states in the Gulf with cheap drones, with the list of targets including data centers, shows that reliance on digital technology can quickly change from an asset to a source of vulnerability. Iran never followed through on its threat to cut undersea data cables, but if its forces had done so, they could have caused a financial and technological meltdown in the Gulf.

A final factor to consider is Washington’s loss of soft power. Indeed, this aspect of power projection is inversely related to the weaponization of US financial and technological hegemony: the more the United States flexes its muscles, the more the rest of the world can feel its chains and take notice of their existence. There would be no debate about the need to pursue alternatives to American cloud hegemons and to the dollar were it not for the fact that Trump’s second presidency has so clearly displayed the risks of dependency on the United States.

The narrative of decline is perhaps an overly simplistic one. A more balanced picture of American power in the twenty-first century might suggest that US imperialism has tightened its grip in some regions, particularly those where it does not face serious hard power threats (like Europe and Latin America), but it has also grown weaker in others, particularly those where the United States still requires physical force to dominate (like East and West Asia). Rather than focusing on decline as such, we should revise our understanding of the contours of American power in the data age.

The rise of Big Tech has led to a fracturing of the US economy, divided between high-earning tech jobs and low-paid service work on the one hand, and between tech firms and traditional companies on the other. Recently, economists have started calling this the K-shaped economy, with AI pushing stocks into the stratosphere while most workers struggle and corporate bankruptcies continue to rise.

Rikap finds that automation is what underpins this fracturing. Currently, automation usually doesn’t mean that workers lose their jobs altogether, but it does mean that they are de-skilled as AI systems take over the core of the creative process, forcing workers to occupy themselves with “low-quality, simplified tasks.” AI has had a particularly pronounced impact on degrading creative labor jobs, like script writing, graphic design, and software development.

The long-term ramifications are likely to be that workers find themselves pushed out of creative labor roles and into the informal service sector, which has itself been radically changed by digital technology. The growth of the gig economy, where platforms hire workers on a piecework basis, reflects a fundamental shift in how the labor market is structured.

Algorithmic management systems have made it easy for companies to minimize labor costs by “nudging” workers to complete tasks for platforms at times of peak demand, avoiding paying workers for time between tasks. The gig economy thus acts as a new type of reserve army of labor, one based on underemployment rather than unemployment per se.

This explains why the labor market can appear “tight” when looking at the employment statistics without any corresponding increase in the bargaining power of workers, because redundancy in the labor market is disguised by precarious service work. In fact, Rikap argues, the fracturing of the economy should make us wary about forms of analysis that are founded upon the use of statistical averages in general: “Indicators developed for an era when firms were more homogenous become misleading when applied to intellectual monopoly capitalism.”

Rethinking the indicators we need in the digital age is just one part of a broader rethink that is necessary if the Left is to make sense of our modern, data-dominated world. It’s capitalism, but not as we knew it.