I’m torn about artificial intelligence right now. On one hand, I see how it excels at automating boring, routine tasks. It can even do some basic problem-solving pretty well. But here’s what worries me - what happens when AI messes up in complicated areas that need human judgment? Think about coding, legal work, or healthcare. These aren’t simple repetitive jobs. Also, I notice that many business leaders seem to be talking up AI way too much, probably to make their companies look more valuable to investors. This makes me wonder about two big questions. First, if machines take over most of the regular work people do now, what new kinds of jobs will actually be created for humans? Second, how long can this AI excitement last before reality hits and the whole thing comes crashing down?
Been through three major tech bubbles and this one’s different. Sure, there’ll be corrections, but the fundamentals are way stronger.
What I’m seeing firsthand - AI isn’t wiping out entire departments. It’s making everything a bit better. We cut code review time by 40% with AI assistants. Marketing cranks out first drafts faster. Support tickets get sorted automatically.
Yeah, companies promising AGI next year will crash hard. Same for anyone claiming AI fixes everything. But practical AI? That stuff sticks. Once you turn a 3-hour task into 20 minutes, there’s no going back.
Most businesses still run on manual processes you could automate today with existing tech. That’s massive runway before we hit any ceiling.
The job displacement panic is overblown. Every automation wave creates new roles. Someone’s gotta manage these systems, train models, handle edge cases. We hired two automation specialists this year just to keep up.
Bottom line - some companies will crash when reality hits their impossible promises. But intelligent automation? We’re just getting started.
i get the concern, really. like, all the hype from investors is loud, but the tech itself does help in many niche areas. i’ve found it useful for writing and digging into research. not magic, but solid for certain tasks. we’ll see which startups stick around.
The sustainability question depends on which AI layer you’re talking about. I’ve been in enterprise software for 10+ years, and real tech shifts always follow the same pattern - crazy overselling, then quiet integration into actual work. What worries me isn’t a crash happening, but when. Companies are burning VC money on moonshot projects while ignoring simple stuff that could pay off immediately. I’ve watched businesses blow millions chasing theoretical AI breakthroughs when they could just automate their invoice processing tomorrow. The correction will split real use cases from speculative garbage. Document processing, predictive maintenance, customer routing - not sexy, but they actually make money. Startups promising human-level reasoning? They’re screwed when funding dries up. On job displacement - history shows we adapt. The internet killed entire industries but created new ones we never saw coming. AI will probably do the same, though some sectors might have a rougher transition. Healthcare and legal will likely see augmentation, not replacement. AI handles routine analysis, humans manage the complex decisions.
I’ve watched tech hype cycles for years - dot-com bubble, mobile craze, blockchain madness. AI’s different though.
It’s actually useful. Not talking about replacing doctors tomorrow, but all that boring stuff eating 60% of most jobs. Data entry, reports, basic customer service, file processing.
The real opportunity? Automation workflows. Don’t replace entire jobs - make existing ones way more efficient. My team used to waste hours moving data between systems and generating reports. All automated now.
Sure, companies overpromising on AI will crash. But automation itself? Not going anywhere. It’s speeding up.
Here’s what people miss - you don’t need some fancy AI model for massive productivity gains. You need smart automation connecting your existing tools. Most business processes are just moving info from A to B with some logic between.
I’ve seen teams cut manual work by 70% automating routine workflows. No machine learning PhD needed. Just good automation tools handling repetitive stuff while humans do creative problem solving.
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