A surprising bipartisan consensus has emerged in US politics: opposition to **AI data centers**. While this convergence of concern is welcome for fostering constructive debate, we contend that focusing solely on data center infrastructure risks obscuring the more profound impacts of AI on society. Local opposition to data centers is often rooted in legitimate concerns. These include the misallocation of land resources amidst housing shortages, increased pressure on energy prices, and localized environmental impact. Unlike many industrial facilities, data centers create very few jobs, leading to a sense of inequitable exchange where tech companies profit while local communities bear the costs. Globally, their carbon footprint poses a significant environmental threat if current usage trends accelerate. For many, opposing data centers feels like the only tangible way to express their concerns about AI's potential to propagate misinformation, displace jobs, or even pose existential risks. ### A Strategic Diversion? However, this singular focus on data centers might be precisely what **AI companies** are banking on. They can often overcome localized protests, treating them as a manageable cost of doing business. More importantly, it diverts political and public attention from their ultimate objective: capturing the value of entire industries. Consider the staggering **three-quarters of a trillion dollars** being spent on data center infrastructure by US companies this year alone. While substantial, this figure pales in comparison to the market for enterprise software, which is roughly twice that size. The true ambition of AI companies extends far beyond compute infrastructure. AI has already made significant inroads into customer service and consumer sales. The next targets are even larger: enterprise software development, creative design, management, and even legal services. In the vision espoused by AI companies and their allies, AI is positioned to replace human professionals in fields like education and medicine. By focusing resistance on infrastructure development, these companies can avoid more challenging debates about the ethical deployment of their products and the protection of these critical sectors. ### Mixed Success and Shifting Sands While data center opposition campaigns have achieved widespread appeal, their effectiveness in the US has been mixed. They tend to be most successful against speculative, early-stage proposals. In contrast, advanced, well-capitalized projects often possess the resources to overcome local resistance. For example, an **OpenAI** and **Oracle**-backed facility in Saline Township, Michigan, is proceeding with construction despite initial local rejection. Legal action by developers forced a settlement, allowing the project to advance. Furthermore, the Trump administration, a vocal ally of corporate AI, has indicated a willingness to accelerate AI infrastructure development, potentially overriding state objections and utilizing federal lands. It's also worth considering that the current surge in data center development might be a temporary phenomenon rather than a long-term trend. Demand for centralized computing could decline as innovation progresses. Leading Chinese labs, such as **Z.ai**, are developing techniques to make frontier-class models smaller and more efficient to run. **AI power users** are increasingly adept at miniaturizing open-weight models for local execution on personal devices. Companies like **Apple** and **Google** are actively supporting infrastructure for running AI models directly on mobile phones. This suggests that the current data center boom could resemble the fiber optic cable bubble of the early 2000s, as demand shifts towards smaller models and on-device AI. ### Redirecting the Focus For those primarily concerned with affordability and environmental protection, a singular focus on data center construction may be misplaced. Current energy prices and inflation are more visibly impacted by geopolitical events. The US's disinvestment in long-term energy security, including ceding the renewable energy industry to China and rolling back climate commitments, has broader environmental implications. For instance, heating buildings accounts for 10% of global carbon emissions, dwarfing AI's energy use, and could be significantly reduced through renewable-powered heat pumps. Similarly, federal housing subsidies have remained stagnant for decades, despite soaring housing costs. Ultimately, the concentration of power and wealth within these tech companies represents the most significant existential risk to society. This necessitates a broader strategy to limit corporate power, particularly their ability to exploit the public and manipulate political systems. Opposing data centers should be viewed as merely a starting point. We must advocate for states to regulate AI, reject irresponsible applications of the technology, and actively shape corporate behavior. Furthermore, considering taxation on AI computation could allow the public to share in the profits while compelling AI companies to internalize more of their societal costs.