AI Growth Is Real, But So Are the Growing Pains | Week 4 to 10 Mar 26

The AI industry is in an awkward phase right now. Companies are making real money, hitting real milestones, and shipping real products that people actually use. At the same time, serious questions about how this technology gets deployed are causing talented people to leave companies and users to switch platforms. This isn't a sign the industry is broken—it's a sign it's maturing faster than anyone expected.

Military Applications Are Forcing Real Choices

Here's what happened: OpenAI announced a partnership with the Pentagon. Within days, thousands of users switched to Anthropic's Claude because they didn't want their tool supporting military applications. OpenAI walked back the partnership.

This matters because it shows that ethics aren't just talking points anymore—they affect business outcomes. Users have options now, and they're willing to switch if they disagree with how a company operates.

What you should do: If you're evaluating AI vendors, ask explicitly about their defense and military policies. Don't assume because a company is big that their values align with yours. Get it in writing. Your team will notice which vendors you choose, and it affects your ability to hire and keep good people.

The Money Side Is Growing Faster Than Anyone Expected

Nvidia just posted revenues over $100 billion and keeps crushing estimates. A startup called Cursor—basically an AI coding assistant—is doing $2 billion in annualized revenue. Universities are launching entire degree programs in AI. This isn't theoretical anymore; this is infrastructure.

This matters because it means AI isn't a maybe for your business anymore. It's becoming table stakes in software, manufacturing, hiring, and dozens of other functions. Competitors are already using it. The question isn't whether to adopt it, but how fast and how deliberately.

What you should do: Pick one specific function in your business—customer support, content creation, data analysis, whatever—and run a three-week trial with a commercial AI tool. You don't need a grand strategy yet. You need to understand what it can and can't do for you. Most business leaders are still guessing.

The Supply Chain Reality Is Getting Serious

Semiconductors and data center capacity are now the actual bottleneck. You can't expand AI operations without chips, copper for infrastructure, and enormous amounts of electricity. This isn't happening in a vacuum—the U.S. and China are competing hard for control of these resources, and it's reshaping global trade.

This matters because it means AI costs aren't going down as fast as the hype suggests. If demand keeps accelerating, electricity and chip prices will stay high. That affects what AI projects actually make financial sense for you and which ones don't.

What you should do: When you're evaluating an AI project, factor in real infrastructure costs—not just the software license. Talk to your IT team about your actual data center capacity. If you're considering moving heavy computational work to AI, understand what that costs to run, not just to license.

What To Do This Week

First, have a conversation with your leadership team about your company's stance on AI in sensitive applications. You don't need a perfect policy, but you should be clear about what you're comfortable with. This affects which vendors you work with and how your team perceives your values.

Second, run that three-week trial. Pick a narrow use case. Pick a tool. Give it to the team that actually does the work. Get feedback that's specific—what worked, what didn't, where's the friction. Most companies skip this step and wonder why AI projects stall.

Third, sit down with whoever manages your IT infrastructure and talk about data center capacity. As AI adoption spreads, it affects compute costs, electricity bills, and what's actually feasible to run in-house versus outsource. You need real numbers before committing to scaled deployment.

Fourth, check your job descriptions and hiring materials. If you're not mentioning AI skills or exposure, you're competing with one hand tied behind your back. Good people want to work with modern tools. Signal that you're serious about it.

Disclaimer

This AI-generated analysis synthesizes 250+ sources collected by Linkfeed from 4 Mar to 10 Mar 2026. While carefully curated, AI-generated content may contain occasional inaccuracies.

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