We’re living through the single biggest tech disruption in history (and, if not the biggest, definitely the fastest). 

The AI revolution promises huge productivity gains by automating complex tasks, accelerating scientific breakthroughs in medicine, biotech, materials science, and democratizing access to expertise in critical industries like healthcare and education. People on the leading edge are already vibe-coding their grunt work away. 

It’s a great time to be alive. 

Or is it? The potential downsides are also clear: Prognosticating predictionistas have warned of massive job losses, brain rot, cyberattacks and worse. 

It’s a scary time to be alive. 

Since you’re reading this publication, it’s a safe assumption that you’re interested in and knowledgeable about technology, generally. And it’s become clear that technology, generally, is under dire threat from AI. 

How AI is harming technology

AI is killing, harming, delaying, or forcing higher prices on a wide range of technologies and tech products and services. The AI industry is: 

1. Creating catastrophic chip shortages. Major RAM makers Samsung, SK Hynix, and Micron have shifted their production to focus on High-Bandwidth Memory (HBM) needed for AI. This has led to shortages of standard DRAM and NAND chips used in smartphones, laptops, and medical devices.
2. Driving hardware prices up. Due to the memory shortage, building non-AI electronics is becoming expensive. By early 2026, prices for standard computer memory and storage drives (SSDs) had surged because the industry’s been prioritizing  high-margin AI chips over consumer parts. There’s even a trend of more people buying second-hand laptops because they can’t afford new ones. 

3. Delaying GPUs and the devices that use them. The demand for AI compute power, which usually relies on Graphics Processing Units (GPUs), has created a massive backlog for the processors and with it, the devices that use them for, you know, processing graphics. 
4. Creating COVID-like shortages. The diversion of chips to AI infrastructure is causing problems for non-AI hardware launches. Shortages of basic power and auto chips are affecting industries from automakers to home appliance makers. It’s like COVID all over again. 
5. Diverting investment in startups. Non-AI startups are struggling to raise money. Investors are funneling cash almost exclusively into AI ventures, forcing non-AI founders to pivot or adopt “AI-first” aspects (called “AI washing”), even when unnecessary. 
6. Draining brains from research labs. There’s always been a relationship between tech-related university research labs and tech. Now, this is being distorted by AI. Private AI companies are hiring away top academic researchers and engineers with massive salaries. This hollows out university departments and non-AI research labs, threatening the pipeline of future talent for critical fields like traditional software engineering. 
7. Discouraging grads from entering tech fields. As companies pivot to AI, they’re cutting entry-level jobs in other areas. US postings for entry-level roles dropped by 35% between 2023 and 2025. This disrupts the career ladder and discourages young people from pursuing non-AI tech careers.
8. Weaponizing cyberattacks. Malicious actors are using AI to attack non-AI systems. AI enables even moderately skilled hackers to launch sophisticated attacks. Tools that clone voices and generate fake identities are breaching traditional security protocols, overwhelming standard IT infrastructure defenses. 
9. Creating a new digital divide. Technical people, developers, and those embracing AI for vibe-coding and other tasks are pulling away from less technical or less inclined people. 
10. Turning the public against the tech industry. The public’s admiration for Silicon Valley is souring in part because of the excesses of the AI sector’s toxic “996” work culture, threats to jobs, AI slop, ridiculously high salaries, skyrocketing electricity bills, and environmental damage from new data centers. There’s also the unauthorized theft of personal data and copyrighted art to train models, and the flood of deepfakes, disinformation and AI slop people see on social networks like Facebook.
11. Destroying demand for apps. The regular software market is shifting toward “vibe-coding,” where people abandon paid app subscriptions in favor of creating their own custom, disposable applications using AI platforms like Replit, Lovable, and Cursor. Gartner predicts that consumers will cut their mobile app usage by 25% as they rely on generative AI assistants to handle tasks rather than scrolling through separate applications, even without vibe coding. Either way, the app development ecosystem is being hammered. 
12. Threatening the future of facts. AI chatbots are transforming search engines by providing direct answers instead of lists of links, a shift that starves publishers of the website traffic and revenue they need to survive. That reduces the incentives and finances for the production and publishing of new facts (for lack of a better term) while frequently presenting false information as fact. This harms technology, an industry that depends on education, new knowledge and training. 

All this sounds dire. And, in the short term, it’s not good. What we don’t know yet is the long-term impact of the AI revolution and whether it will prove to be a net benefit or a net harm to the non-AI technology people, business, projects, culture and communities we have loved for decades. 

In the meantime, it’s important to remain clear-eyed about the emerging costs to technology, even for those of us excited about AI. 

AI disclosure: I don’t use AI to do my writing. The words you see here are mine. I do use Gemini 3 Pro via Kagi Assistant (disclosure: my son works at Kagi) as well as both Kagi Search and Google Search to fact-check. I used a word processing application called Lex, which has AI tools, and after writing the column, I used Lex’s grammar checking tools to hunt for typos and errors and suggest word changes.