If you’ve been scrolling through the news lately, you’ve probably noticed that AI isn’t winning any popularity contests. A March 2026 NBC News poll found that 46% of registered voters have a negative view of artificial intelligence. A majority — 57% — said the risks outweigh the benefits. And honestly? That makes sense. The headlines are loud, the changes feel fast, and nobody likes the feeling that the ground is shifting under their feet.
But it’s worth slowing down and looking at what’s actually happening — not just what the loudest voices are saying. Because the data tells a story that’s a lot more balanced than the one most people are hearing.
The Data Center Question
Let’s start with the big one. Data centers have become a lightning rod. They use a lot of energy. They take up land. They need water for cooling. These are real concerns, and communities have every right to ask hard questions about them. In 2025, over $156 billion in data center projects were blocked or delayed because of local opposition. That’s not nothing.
But here’s what doesn’t make the headlines as often: data center construction has become one of the largest drivers of economic activity in the country. A Goldman Sachs analysis estimated roughly $7.6 trillion in cumulative capital spending on AI infrastructure between 2026 and 2031. That money doesn’t vanish into thin air. It flows into construction jobs, electrical work, concrete, steel, logistics, and the small businesses that support all of it.
Take Oracle’s data center campuses. Their facilities in New Mexico and Wisconsin each created around 4,000 construction jobs. Their Abilene, Texas site has employed more than 8,000 construction workers since breaking ground. And once the buildings are up, the work doesn’t stop — Oracle expects to hire nearly 8,000 permanent operations staff across just four of their campuses. These aren’t Silicon Valley coding jobs. They’re facilities engineers, security teams, inventory managers, and logistics coordinators. Many of these roles don’t require a four-year degree.
And there’s a piece of this story that matters a lot: several of these companies have built workforce training programs specifically for military veterans transitioning to civilian careers. That’s the kind of thing that doesn’t generate clicks but does change lives.
On the energy side, the picture is evolving fast. Major tech companies are investing billions in renewable energy — solar, wind, and even next-generation nuclear — to power these facilities. One major hyperscaler is spending $20 billion on an energy park that combines data center operations with on-site renewable generation and storage. The goal isn’t just to power AI. It’s to feed surplus clean energy back into the grid. That’s a very different story than “tech companies are burning through all our electricity.”
The Jobs Conversation
This is probably the most common fear around AI: “It’s going to take my job.” It’s understandable. Change is uncomfortable, and the speed of AI development makes it feel even more uncertain.
But the numbers tell a more complicated story. The World Economic Forum’s Future of Jobs Report projected that by 2030, AI and related technologies will create roughly 170 million new jobs globally while displacing about 92 million — a net gain of 78 million positions. In the U.S. alone, AI-related job postings climbed more than 25% year-over-year in early 2025. And more than half of those postings came from outside the tech industry — in healthcare, finance, manufacturing, and marketing.
There’s also a wage story here. Workers with AI skills are earning a 56% premium over peers in the same roles without those skills, according to PwC research. That’s up from 25% just a year earlier. The demand for people who can work alongside AI is growing fast, and it’s showing up in paychecks.
None of this means the transition is painless. There are real gaps in training access, and the benefits aren’t distributed equally. Younger workers and those without college degrees face steeper hills to climb. But the idea that AI simply deletes jobs and offers nothing in return doesn’t match the evidence.
Where AI Is Already Doing Real Good
Beyond economics and employment, there are areas where AI is doing work that’s hard to argue against.
Drug discovery is one of the clearest examples. Developing a new medication has traditionally taken 10 to 20 years and cost billions of dollars, with most candidates failing in clinical trials. AI is compressing those timelines. Pharmaceutical companies are now using AI to sift through millions of potential compounds computationally — testing their properties before a single molecule is synthesized in a lab. One AI-designed drug for a serious lung disease has already made it into Phase II human trials. The potential here isn’t abstract. Faster drug development means treatments reaching patients sooner.
AI is also being used to improve weather forecasting, optimize supply chains so food doesn’t spoil before it reaches shelves, detect wildfires earlier, and help doctors identify diseases in medical imaging with a level of consistency that even experienced radiologists find valuable.
These aren’t hypothetical use cases. They’re happening right now.
The Sentiment Gap
Here’s the most interesting part of the polling data: there’s a massive gap between how people feel about AI and how they use it. While nearly half of voters say they view AI negatively, the number of people using tools like ChatGPT rose from 48% in late 2025 to 56% by March of 2026. Over half of employed Americans say they’re using AI at work at least a few times a month.
People are voting with their feet even while telling pollsters they’re worried. That gap suggests something important — the discomfort isn’t really about the tools themselves. It’s about uncertainty. About who benefits and who gets left behind. About whether anyone is steering the ship.
Those are fair concerns. They deserve honest answers, not dismissal.
The Bottom Line
AI is not perfect. There are legitimate questions about privacy, about environmental impact, about concentration of power, and about making sure the economic benefits reach real communities and not just corporate balance sheets. Our approach should be thoughtful and measured.
But every major technology in history — electricity, the automobile, the internet — went through a period where public opinion ran negative. People were scared of what they didn’t fully understand yet. And in every case, the technology didn’t go away. It got better. The rules around it got smarter. And over time, the benefits became impossible to ignore.
AI is in that awkward middle chapter right now. The one where the costs are visible and the benefits are still coming into focus. Patience doesn’t mean blind optimism. It means giving the full picture a chance to develop before writing the whole thing off.
And so far, in our opinion, that full picture looks a lot more promising than the headlines suggest. Here’s to cautious and informed steps onward.
Securities offered through Registered Representatives of Cambridge Investment Research, Inc., a Broker/Dealer, Member FINRA/SIPC. Advisory services offered through Cambridge, a Registered Investment Advisor. Sound Foundation Wealth Advisors and Cambridge Investment Research, Inc. are not affiliated.
