U.S. AI Strategy Needs IBM Moment to Drive Open Standards and Global Leadership

AI is at a pivotal stage in its development, one that resembles the early days of personal computing in the 1960s rather than the internet boom of the 1990s. Unlike the rapid expansion of the internet, which was driven by open standards and widespread access, the current AI landscape is marked by high costs, extreme concentration, and limited accessibility. This situation creates barriers for startups, academics, and smaller companies trying to enter the field, as they are often forced into long-term contracts with dominant cloud providers, making it difficult to move data or shift workloads freely [1].

The analogy to the 1960s computing era is instructive. At that time, computing power was the domain of governments and large institutions, with room-sized machines requiring massive resources to operate. The shift to personal computing, led by companies like IBM, Microsoft, and the adoption of open operating system standards, democratized access and catalyzed a technological revolution. Today, AI is in a similar transitional phase, and the need for an “IBM PC moment” is more urgent than ever [1].

To achieve this transformation, the article argues that the U.S. must adopt a more coordinated and strategic approach to AI development. A fragmented market and lack of national strategy risk allowing other nations, particularly China, to take the lead. China has already released several action plans aimed at promoting AI standards and offering public-private partnerships to support its national champions. Beijing has even announced a state-run exchange to market and catalog computing power, further centralizing and streamlining AI development within the country [1].

In contrast, the U.S. has been slower to act. The government has the opportunity—and perhaps the obligation—to foster a more open and competitive AI ecosystem. This can be done through the creation of strategic compute reserves, similar to the strategic oil reserve, which could provide emergency capacity during crises. Additionally, procurement policies should prioritize small and medium enterprises to promote a more diversified and resilient market [1].

The article emphasizes that market forces, guided by open standards, will ultimately drive AI innovation. When companies can easily compare compute options and move workloads between providers, competition leads to lower prices and better services. When developers can access standardized AI infrastructure without long lead times, innovation accelerates [1].

A key component of this strategy is the promotion of American-developed AI standards on a global scale. When allied nations and even adversaries adopt these standards, the U.S. strengthens the broader democratic technology ecosystem. For example, President Trump’s decision to allow China to purchase NVIDIA H20 processors supports long-term U.S. interests by encouraging Chinese developers to build on American technology. This kind of reliance on an American technology stack can amplify influence and promote democratic values far beyond the scope of traditional export controls [1].

The U.S. AI Action Plan, announced by President Trump, represents a step in the right direction. It outlines a vision for maintaining American leadership in AI and sets the stage for a more open, competitive, and accessible future. However, the article concludes that swift and decisive action is necessary. Without it, the U.S. risks ceding its current leadership in AI to other nations and missing out on the next major technological revolution [1].

The opinions expressed in the article reflect the views of the author and not necessarily those of Fortune.

Source: [1] AI isn’t having a ’90s internet moment, it’s more like ’60s personal computing, and it needs one special company to kickstart the revolution (https://fortune.com/2025/08/06/artificial-intelligence-like-internet-1990s-personal-computing-1960s/)