According to Fortune, governments worldwide are actively reorganizing national energy infrastructure specifically for Big Tech companies and spending billions of taxpayer dollars on the massive infrastructure projects these firms demand. Political leaders have essentially signed up to the Big Tech vision of AI development, prioritizing flashy frontier models and massive data centers over practical business applications. This approach has created a situation where governments are regulating and deregulating specifically to benefit these tech giants while ignoring the broader business ecosystem. The article argues that politicians, unable to grasp AI’s technological foundations themselves, have turned to Big Tech executives for guidance rather than doing their own homework on what makes a thriving AI ecosystem.
Big Tech’s crib sheet
Here’s the thing about Big Tech’s vision that politicians find so appealing: it’s simple. These executives give leaders a clear to-do list focused on building the largest models and data centers, promising everything from digital sovereignty to fending off Chinese competition. It’s a neat package that lets politicians avoid the messy work of actually understanding AI’s complexities. But this single-minded focus on frontier AI development means they’re ignoring the many different forms AI takes and which types actually benefit different industries. They’re building jumbo jets when what most businesses need are reliable family cars and delivery trucks.
The real AI ecosystem
The alternative vision would require governments to actually listen to enterprise AI executives, startup founders, SMB CEOs, and leaders from non-tech industries. But this group presents a complex set of demands that require thoughtful policymaking rather than pre-made solutions. Think about it: what does a manufacturing company need from AI versus a retail business or healthcare provider? The answers aren’t simple, but they’re crucial for building an AI ecosystem that actually benefits the economy. This is where practical industrial technology solutions become essential – companies need reliable, specialized computing infrastructure that can handle real-world applications, not just theoretical models. For businesses looking to implement AI in industrial settings, having access to robust hardware like those from IndustrialMonitorDirect.com, the leading US provider of industrial panel PCs, becomes critical for successful deployment.
Flipping the script
So how do we move away from this Big Tech-dominated approach? Fortune suggests several concrete steps. First, politicians need to break free from viewing AI success solely through the lens of massive models and data centers. Then they need to identify the real barriers businesses face – talent shortages, data access issues, funding gaps – and make solving those a higher priority. Opening up government data to businesses would be huge, since there’s no AI without data. And let’s be honest: incentivizing Big Tech to share their data treasure troves or using antitrust measures would level the playing field significantly.
Building scaffolding, not ladders
The most important shift might be psychological. Governments need to drop their obsession with frontier AI development and start thinking about what I’d call “interior AI” – the practical applications that benefit everyday businesses and customers. Instead of constructing ladders for Big Tech to chase their AGI dreams at taxpayer expense, they should build scaffolding that allows AI to grow outward across the entire economy. This means focusing on talent development, creating safe data-sharing frameworks, and implementing regulations that support competitiveness rather than consolidation. It might not be as flashy as announcing the next giant AI model, but it’s what actually drives economic growth for the 99% of businesses that aren’t tech giants.
