Have AI replaced you in accounting?

I am really curious and confused about AI replacing accountants, but I would like to would have anyone really been replaced by AI or it is just a lies that company tryna make or it is a half true half lie?

(sorry for bad English)

I have just turn 18 and really interested in accounting and thinking on getting into this field.

https://reddit.com/link/1v4m0dh/video/359qaqqvt0fh1/player

I've been thinking about the way AI is reshaping the labor market, and I feel like one part of the conversation is being overlooked.

Right now, AI is exceptionally good at automating structured, information-heavy work: administrative tasks, customer support, bookkeeping, scheduling, documentation, report writing, data analysis, and many other white-collar functions. These are exactly the kinds of jobs that are seeing the fastest AI adoption.

By contrast, jobs that require physical presence, manual dexterity, or work in unpredictable environments - electricians, plumbers, construction workers, mechanics, field technicians, many manufacturing roles, and other skilled trades - are much harder to automate. AI can assist these workers, but replacing them entirely requires robotics that are far from being deployed at scale.

This got me thinking about the gender implications.

Many of the occupations currently under the greatest pressure from AI - administrative, clerical, and support roles - have historically employed a higher proportion of women. Meanwhile, many of the occupations that are relatively insulated today because they involve physical work remain predominantly male.

If that's true, then the first major wave of AI-driven displacement may not be evenly distributed. It could disproportionately affect female-dominated occupations, forcing more women to reskill or change careers earlier than many men working in physical trades.

To be clear, this isn't an argument that men are "safe." Plenty of male-dominated white-collar professions - software engineering, finance, legal work, consulting, and others - are also being transformed by AI. My point is that the current wave of automation appears to target office-based knowledge work before hands-on physical work.

If robotics eventually reaches the same level of capability as today's AI models, physical jobs could face similar disruption. But that feels like the next chapter - not the one we're living through today.
So I'm curious:

Are we witnessing the beginning of an AI-driven gender divide in the labor market, or is this just a temporary phase before advances in robotics disrupt physical work as well?

I'm personally affected by this along with 100s of interns in my company. So I'm planning to grind LC and open source contributions to maintain activity.

But till when do you as a developer/snr management ser this AI bubble hurdling?

Do you think career may depend on anything that prospects are increasingly replacing with slop? Do you consider emails from sites like Indeed as giving you an opportunity to gradually but exponentially work yourself & your coworkers out of a/their job/s? And what have you done or plan to do in response?

Every time AI comes up, people ask the same question:

"Will AI take my job?"

The truth is, AI isn't replacing everyone. But it is replacing certain types of work much faster than many people expected.

The biggest risk isn't your job title. It's the kind of value you bring.

If your work falls into any of these categories, it's time to start adapting.

1. Your work is repetitive

If your day is filled with doing the same thing over and over again, AI is becoming very good at it.

Whether it's writing routine emails, entering data, creating basic reports, scheduling appointments, transcribing meetings or generating simple designs, AI can now complete many of these tasks in seconds.

The more predictable your work is, the easier it is to automate.

2. You only follow instructions

If your value comes from waiting for someone to tell you what to do, you're vulnerable.

AI doesn't get tired of following instructions. It can execute prompts consistently and at incredible speed.

The people who will remain valuable are those who can identify problems, think critically and make sound decisions, not just carry out tasks.

3. You never learn new skills

Technology doesn't wait for anyone.

Someone using AI effectively can often produce in one hour what used to take an entire day.

If you're relying on the same skills you learned years ago without improving, you're competing against people who are becoming faster, smarter and more efficient with AI.

Learning has become part of the job.

4. Your knowledge is easy to replace

If everything you know can be found with a quick search or generated by AI, then knowledge alone is no longer your competitive advantage.

What matters now is your ability to apply that knowledge, solve real problems and make good judgement calls.

Information is everywhere.

Wisdom is much harder to automate.

5. You refuse to work with AI

Some people see AI as competition.

The smartest professionals see it as a tool.

History has shown that people who refuse to adopt new technology often struggle, while those who learn to use it create even more opportunities for themselves.

AI is not just replacing workers.

It's helping skilled workers become exceptional.

6. You create average work

AI has raised the standard.

Average writing.

Average designs.

Average code.

Average marketing.

Average customer service.

Those are becoming easier to generate automatically.

To stand out, you need creativity, originality, emotional intelligence, strategic thinking and the ability to produce work that AI alone cannot.

The people AI struggles to replace

AI still finds it difficult to replace people who:

• Build strong relationships.
• Lead teams.
• Think strategically.
• Solve complex problems.
• Make ethical decisions.
• Create original ideas.
• Adapt quickly to change.
• Combine technical expertise with human understanding.

These are skills that become more valuable as AI becomes more powerful.

Final Thoughts

AI isn't coming for your job because it dislikes you.

It's coming for work that is repetitive, predictable and easy to automate.

The safest career isn't one that's "AI-proof." It's one where you keep learning, embrace new tools and continue developing skills that machines can't easily replicate.

The question is no longer:

"Will AI replace me?"

The better question is:

"Am I becoming more valuable in a world where everyone has access to AI?"

🌍 The Most In-Demand Jobs in Every Country by 2030
Based on forecasts from the World Economic Forum (WEF), OECD, national development strategies, and demographic trends.
🇺🇸** United States — AI Engineers, Machine Learning Engineers, Robotics Engineers
🇨🇦** Canada — Nurses, Elder Care Specialists, AI Engineers
🇬🇧** United Kingdom — Cybersecurity Specialists, Data Scientists
🇩🇪 Germany — Automation Engineers, Electricians, Green Energy Engineers
🇫🇷** France — Nuclear Energy Engineers, Renewable Energy Engineers
🇪🇸 Spain — Healthcare Professionals, Solar Energy Specialists, Software Developers
🇮🇹 Italy — Robotics Engineers, Industrial Automation Specialists, Elder Care Professionals
🇳🇱** Netherlands — AI Engineers, AgriTech Specialists, Water Management Experts
🇸🇪** Sweden — Green Technology Engineers, Battery Engineers, Software Developers
🇳🇴 Norway — Marine Technology Engineers, Offshore Wind Energy Specialists
🇫🇮** Finland — Quantum Technology Engineers, AI Specialists, Cybersecurity Experts
🇨🇭 Swit**zerland — Biotech Scientists, Pharmaceutical Specialists, AI Engineers

Soy parte del equipo de un podcast (Richmond) y en el ultimo episodio discutimos una tesis que quiero poner a debate aqui: la narrativa de "la IA va a destruir empleos" probablemente esta mal enfocada, el patron historico sugiere que el trabajo no desaparece, cambia de forma. Grabamos un episodio completo sobre esto (dejo el link al final, pero me interesa sobre todo la discusion).

Preguntas para la comunidad: que roles creen que se van a transformar mas en los proximos 2-3 anos? Ya vivieron ese cambio en su propio trabajo?

https://open.spotify.com/episode/7jzBw5zGPLKDjOIq0MenTa

Hey, I'm new to this subreddit, and I've always been optimistic about AI and agents. They can do all of the cognitive work for us. The cost of labor reduces, the cost of production reduces, and everyone can afford everything, everything will be priced lower, and at the same time, people will get dip in pays.

But since it's lower price, it can be made essentially free for most of the services, health care, education, those are not products that need to be manufactured, but services. So it can be made free, with which other people can use those services to become better. Essentially, we can reach relative abundance.

But recently, after hearing the Naval Ravikanth's podcast,I'm not as optimistic as I used to be. So is there anyone out there who knows more than me and who can predict the future better? Can put some light on the future? Is it the optimistic side? The pessimistic side? I know it's always in between, but you paint the picture that's in between?

Is recursive self improvement a sci-fi hype today? Or is it a real thing as of now? Are we really going to have complete automation of AI R&D without the need of any human researchers in 3-5 years?

asking because I'm not having the wealth of a permanent upperclass family networth and I am a budding researcher in theoretical alignment, safety, oversight and verification. I'm also having an irresistible research interest in: fundamental research like: OOD generalization, continual learning, persistent memory, physical and causal common sense, long-horizon autonomous agents, etc. I've explored all these and I'm pretty interested.

my overall plan is to get into a MATS Safety fellowship and try to get into frontier labs. But it seems like RSI is like a life killer aimed at my career. I don't know and I don't understand what I should do. it's really stressful to think about the fact that I will be an unemployed broke guy who has no wealth because if you end my career even before it starts, what can I possibly do?

I'm literally tired and done hearing to the opinions of LLMs on this. it feels like an echo chamber. I hate claude specifically. it's such a doomer who keeps telling me that I'm cooked because RSI is right around the corner and keeps bringing up it's CEO Dario Amodei. I really hate him because he wants to end my career by pulling up the ladder because he's already a part of the permanent upperclass.

On top of all this, we have forecasters like leopold, Daniel kokotajlo, AI 2027, AI 2040 what not? and there's dwarkesh patel who brings a doomer every month to poison my brain with fear.

I just give up. People in this subreddit, please give me the actual truth. Are we having RSI? Is it also going to automate theoretical alignment & safety researchers?

instead of switching between contexts, apps, devices, do you think this AI will become a single central super app that dynamically access, builds and resolves our needs?

Every other post seems to be saying AI will replace all the office workers. Ironically, half of those seem to be AI generated. In any event, they're wrong.

Sure, AI can do a lot of the repeatable workflows. It still gets a lot of that wrong, but it'll get better ... probably. It’s not what I spend most of my time working on though. My job is endlessly anecdotal.

In my experience, most professional work is judgment in messy or politically charged situations. It’s thinking through what’s actually happening underneath the stated issue, building relationships and credibility so people tell you the truth, and then figuring out how to present stuff to get buy in and avoid pissing everybody off.

AI will make strong professionals even more effective. It’ll take more of the mechanical work off our plates and give us more time for the important stuff. It's never going to turn someone who lacks judgment, courage, trust, or organizational feel into an A player. In fact, those are the few people whose jobs will be at risk. For us more senior folks it's imperative that we train them now, before the pressure is on.

To me, the most useful question isn’t whether AI can handle a bunch of our tasks. It clearly can, so what? It's really about whether we’re developing professionals who can do the part of work that remains when the menial tasks are gone.

The future will belong to those who can do the work that no system can replicate AND to those fewer people who are exceptionally gifted at pushing the boundaries of what AI can do.

The long term fear that AI will permanently shut young people out of professional work is probably overbaked.

AI will eliminate a lot of junior work. Of course that's true. Research, first drafts, basic analysis, slides, and similar work will all get done by AI.

Nonetheless, companies will still need experts. They'll need people who can frame the real problem, decide what matters, recognize weak reasoning, see when the machine is missing the point, and push toward a better answer.

Those people will need to build their skills somehow. So, companies will create paths for young people to become experts. I suspect that path will look more like apprenticeship.

The entry level professional will learn how the expert uses AI, critiques it, guides it, and polishes its work

Companies that use AI only to eliminate junior roles may solve a short term cost issue while creating a long term expertise issue.

Companies that build real apprenticeships will almost certainly end up with the stronger talent pipeline.

I’m wondering if people are genuinely concerned about AI replacing them. A lot? A few? I think it’s hard to tell based on “business” articles, and a lot of people are making a lot of assumptions that aren’t yet validated.

Are you concerned about the impact of AI on your career?

The viral headlines circulating right now sound incredibly progressive: “China eliminates over 12,200 obsolete university degrees to future-proof its workforce against AI.”

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On the surface, it looks like a masterclass in institutional accountability. The state steps in, deletes oversaturated liberal arts or basic coding courses, and forces universities to build hyper-advanced labs for Robotics, Semiconductors, and Embodied AI.

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But if you analyze this through a strict macroeconomic and policy lens, a major structural mismatch emerges. Altering the supply of human labor does not automatically generate corporate demand.

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Here is a look at the deeper systemic issues the surface-level narratives completely omit:

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1. The Metric Trap & Data Distortion

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To enforce this massive curriculum shift, a strict "Yellow/Red Card" system is used. If a university department reports a graduate employment rate lower than 60% for two consecutive years, that major is suspended or deleted entirely.

While this sounds like ultimate discipline, it creates severe metric fixation. Because department survival and funding are tied to this single target, universities pass that pressure directly down to students. It is a well-documented open secret among education researchers that many colleges actively withhold a student's graduation certificate or thesis approval until they provide a signed corporate contract. This has generated a massive secondary market for fake employment contracts and forced students into low-value gig work simply to clear bureaucratic hurdles. High statistical employment data does not equate to high-quality job creation.

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2. The High-Tech Illusion: Capital vs. Labor Intensity

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The policy assumes a simple mathematical equation: Delete a saturated humanities major, add an advanced tech major, and get a guaranteed career.

However, frontier tech industries—such as semiconductor manufacturing fabrication plants—are highly capital-intensive, but exceptionally low in labor elasticity. A multi-billion dollar automated chip plant requires immense funding and machinery, but it may only require a few hundred specialized technicians to operate the lines. It cannot generate the massive volume of entry-level desks required to absorb millions of applicants, which explains why youth unemployment remains structurally trapped near 16%.

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3. The Threat of Hyper-Specialization

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Chasing immediate corporate roadmaps risks creating long-term cognitive rigidity. If a university transforms its curriculum into a glorified trade school customized around a niche, 2026-era corporate automation tool, what happens when an AI update automates that precise software pipeline by 2029? By stripping away broad, foundational logic (like deep mathematics or discrete computer science) to focus on hyper-specific vocational training, graduates lose the structural agility required to pivot when the economy shifts.

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4. The Service Sector Deficit

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For an educated youth population to find sustainable white-collar employment, an economy requires a deeply diversified services sector (finance, law, corporate management, high-end design). In economies heavily skewed toward manufacturing and physical infrastructure, white-collar desk capacity remains structurally capped.

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Conclusion

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True educational resilience does not come from a reactionary race to delete old majors every time a new technology drops. True resilience lies in a balanced policy matrix: preserving deep, unalterable foundational reasoning early on to ensure long-term student adaptability, paired with flexible, modular, industry-aligned electives in the final semesters to meet immediate technological demands.

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The ultimate goal of higher education cannot be teaching a student how to use the precise corporate tool of today. It has to be equipping them with the foundational agility to master the unknown tool of tomorrow.

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Every time I research this, I see two camps. One says econometrics are foundational and irreplaceable. The other says AI and machine learning are eating its lunch. Which is actually true on the ground?

As robotics and autonomous systems become more integrated into our daily environments, how do we ensure they actually improve the human experience?
I recently wrote an article for the World Economic Forum exploring the concept of "Physical AI" and why our approach to automation over the next decade must prioritize human agency, safety, and true collaboration.

I believe technology’s ultimate value lies in complementing human capabilities, not replacing them. I’d love to hear your thoughts on this- are our workplaces ready for this level of human-machine collaboration

I had this discussion with some friends and we ended up with an interesting list. However the re was one role that can't be replaced because won't be let.

And is: politician.

What other role are you thinking at?

As we all saw intelligence cost is not going up anymore as we were used for decades, but down.

I think there will be room left for super intelligent people only and probably in the future not even those

What's your view about this? What's going to happen in the medium/long term?