The rapid rise of artificial intelligence is forcing Wall Street to rethink how companies compete and make money. Analysts at Goldman Sachs recently released an in-depth note exploring whether AI will spark intense new competition or help dominant tech giants consolidate their power. While many believe AI will create a fairer playing field, history suggests that revolutionary technologies usually create highly concentrated profit monopolies.
To understand the future of the AI market, economists look back at past technological revolutions. Historic breakthroughs such as railroads, electricity, and the internet produced massive productivity gains across the global economy. However, these technologies also rewarded the builders and owners of the physical infrastructure with highly concentrated profits. If the AI revolution follows this same pattern, a small handful of massive tech companies will likely capture the majority of the wealth.
However, Goldman Sachs analysts raised a unique alternative possibility. They noted that the foundational models powering AI might eventually become mere commodities. If open-source competition and model sharing continue to spread rapidly, the profit margins for building these basic AI brains will compress. In this environment, the real winners will not be the companies building the models, but the firms that possess proprietary enterprise data and strong customer lock-in.
This debate happens at a time when corporate concentration has already reached historic highs. For over a century, administrative and tax records show that larger firms in finance, manufacturing, retail, and wholesale have steadily expanded. In the United States, this concentration has climbed continuously since the 1930s. Today, the top ten largest stocks represent roughly 35% of the total market, compared with just 18% a decade ago.
Economists use three competing theories to explain why companies keep getting bigger. The first theory suggests that globalization and international trade allow massive firms to capture a disproportionate share of global markets. The second theory blames weak antitrust enforcement and high regulatory barriers for protecting giant companies from smaller competitors.
Goldman Sachs finds the third theory—economies of scale and market share capture—the most compelling. Across advanced economies, corporate concentration rises much faster during periods of rapid technological change. When a major technological shock hits the market, the productivity gap between frontier firms and their smaller rivals widens significantly. We saw this happen clearly in the online retail sector, and AI will likely accelerate this trend.
Interestingly, the industries most exposed to AI today are already highly concentrated and enjoy some of the highest profit margins in the business world. At first, the integration of AI will likely trigger fierce competition among these massive firms as they fight for market share. But over time, the massive amount of intangible capital and specialized infrastructure required to run AI will inevitably raise network concentration, helping the dominant players extend their lead.
The financial stakes in this technology race are absolutely astronomical. The global artificial intelligence market stood at roughly $638 billion in 2024 and is on track to hit even higher numbers. Some optimistic analysts project that by the year 2034, the global AI market could exceed a staggering $4.8 trillion, representing a nearly 7.5-fold increase.
Ultimately, the long-term impact of AI on corporate profitability will depend on how successfully companies can adapt. While some firms will face extreme margin pressure and declining profits, the organizations that own proprietary data and build collaborative systems will secure durable, long-term wealth. Investors must look past the daily hype and focus on the companies that can turn massive AI spending into real, sustainable cash flows.
