TOP 10 Highest-Paying Jobs for the next 10 years (and 5 jobs that have NO future)
19m 39s
This episode explores how AI is reshaping the job market, not through mass replacement but through augmentation. While many routine, repetitive roles—like customer service, data entry, and word processing—are declining due to automation, new careers in healthcare, IT management, and data science are flourishing. The growth is driven by human needs for judgment, oversight, and strategic decision-making, which AI cannot replicate. Jobs with high AI exposure are not disappearing; instead, they are evolving. For example, healthcare roles like nurse practitioners and physician assistants grow due to shortages and regulatory barriers to automation. Similarly, software engineering and IT management remain strong because they require accountability and complex planning. The core insight is that work is shifting from execution to definition and evaluation—tasks where human judgment, ethics, and long-term thinking matter most. A simple framework—define, execute, evaluate—helps professionals assess which tasks can be automated and which should be taken on personally. The message is clear: jobs don’t vanish; they transform. By using AI to handle routine work, individuals can reclaim time and focus on higher-value responsibilities, leading to greater productivity and career growth. The future belongs not to AI replacing humans, but to humans mastering how to work alongside AI.
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More than 750,000 office and administrative support jobs
are projected to disappear from the U.S. economy by 2035.
And at the same time, some professions are projected to grow by more than 40%.
So if you're choosing what to study,
think about changing careers or wondering whether your skills will still be valuable in five years,
this video will help you understand where demand is growing,
what these jobs pay, and what it takes to get into them.
Today, we're looking at 10 growing careers ranked by median salary from lowest to highest.
And at the end, I'll also show you the five fastest declining occupations in the country,
plus a simple way to identify which parts of your own work you should start rethinking.
Because here's the surprising part.
Some of the jobs I have done in the past are not the same as the ones I have done in the past.
are still growing.
:
of the 206 occupations with the highest AI exposure, 141 are still projected to grow
over the next 10 years. So it's not like AI is wiping them out. That's 68%. So high AI exposure
does not mean a profession is going to disappear. It's mostly meant changing. Because when we think
about AI augmenting jobs, it augments certain tasks inside the job. They're not the same thing
as replacement risk. And for the AI context, a Bureau of Labor Statistics combined five research
sources, including RealCloud and Microsoft Copilot usage mapped to workplace tasks. So we'll go from
number 10 to number one, and then we'll wrap up with the disappearing professions. We start this
with a profession that earns just over $100,000. Management analysts. In plain English, those are
consultants. The people companies hire to figure out how to do work better. This is the job that
should be shrinking, right? Because you can ask AI anything. Very high exposure to AI augmentation
is something that AI can generate. Research, analysis, slides, and recommendations. Exactly
what AI is best at. Well, here's what's happening instead. Plus 109,000 jobs. And here's why. Every
company on earth is trying to restructure itself around AI, and most have no idea how. The
restructuring is the product. When Satya Nadella, CEO of Microsoft, pushed back on the white collar
apocalypse framing in June, his line was, how about we think about reorganizing the jobs? Somebody gets
paid to do that reorganizing. And the openings? 94,000 every single year. One of the most hireable
jobs on the list. Number nine. This is the one nobody puts on these lists, and it's the smartest
bet in the data set. These are people who train nurses, pharmacists, physical therapists,
physician assistants, and entire healthcare workforce this decade depends on. Plus 17.9%.
The logic behind this is healthcare is adding roughly a third of all new
American jobs. Those millions have to be taught by somebody. And in healthcare, you legally cannot
scale teaching with a chatbot. Clinical training requires supervised human hours. Whenever you see
a field exploding, ask who trains the workforce? That job is usually undervalued and underbooked.
The barrier is real, though. You need a doctoral or a professional degree. This is a decade-long
play, not a six-month switch. Now, let's leave the laptop economy entirely for this job. Constructors
run job sites. They figure out budgets, schedules, subcontractors, inspectors. Plus 55,000 jobs,
nearly 50,000 openings a year. And here's the connection to everything else in this video.
AI has a physical footprint. Data centers, power plants, chip fabs. Every AI announcement you read
this year eventually becomes a construction project with a manager and a hard head.
Jensen Huang on Fox Business in late August said,
Computer plants, all of the AI factories being created, hundreds of thousands of jobs are being
created as we speak. This is also where the money is moving. CNBC reported AT&T is spending roughly
$38 billion over five years on hiring and training blue-collar and skilled trade workers. If you've
been told your whole life that the safe path is a screen job, this decade might argue the opposite.
Let's move on to number seven. Data scientists, plus 34.6 percent, the third fastest-growing
occupation in America. It is estimated to go from 275,000 to 371,000 by 2035. How is this the
fastest-growing, high-paying job when AI can write code and run analysis? Because of what AI actually
did to it. It automated the middle. The cleaning, the boiler play, the first-pass model. It did not
automate the two ends. Deciding which question is worth asking and deciding whether the answer is
trustworthy enough to bet the company on it.
Andrew Ng put the economics of this better than anyone when he was on this podcast in August.
Well, that 60 percent that a human does has become even more valuable because it's called
an economic complement to the 30, 40 percent that's now cheaper. And so what will happen is
people that use AI, maybe people that use AI will replace people that don't use AI, but AI is not
in a position for the vast majority of jobs to replace people. Of all the different professions,
the one that's most affected by AI now is software engineering because AI is actually
fantastic at writing code. And what we see is that the number of job openings in software
engineering is up, contrary to what the doom fear-mongers would say, right? AI is not actually
able to replace software engineers. And all the good software engineers I know are busier than
ever. Now, the flip side of it is, if someone still writes code like it's 2022 before chat GPT,
they're in trouble.
They need new skills. Don't do stuff that 30, 40 percent AI can automate. You've got to start
doing that. Let AI do that. But then gain new skills to do the other 60, 70 percent AI cannot do.
That's the whole mechanism. Make part of a job cheap and the remaining human part
gets even more valuable, not less.
Number six, medical and health services managers.
They run clinics, hospital departments, nursing facilities, group practices,
plus 24.2 percent, 155,000 new jobs, 62,000 openings a year. And it needs a bachelor's degree,
not a medical one. It's where two unstoppable forces meet. Healthcare demand is exploding
because of aging. And healthcare is also the most regulated, most fragmented,
most administratively broken industry in the developed world. And it's being digitized
right now, badly and expensively. I've had a couple of doctors on this podcast and they confirmed.
Whoever understands both the clinical side and the operational side is the bottleneck.
Bottlenecks get paid well. This is the non-clinical route into healthcare. You don't
need medical school. You need to be able to run a complicated operation full of stressed people.
Number five, information security analysts, plus 21 percent. The standard explanation is
more hackers, more cybersecurity jobs. True, but it misses what changed. AI made attacking cheap,
convincing, phishing, and perfect English at scale for free. Voice cloning, automated vulnerability
scanning. And companies are shoving AI into everything, creating brand new categories of
risk. Nobody has a playbook for it. One note, 14,000 openings a year is modest. This is a smaller
occupation than people assume, about 193,000 people. And it's genuinely competitive, but it's
also the most accessible, high-paying job on this list without a degree-heavy path. Number four,
practitioners. Pays $132,000 a year with 29,000 openings a year. Requires master's degree,
AI exposure high, plus 41 percent. The single fastest growing occupation in the United States
of America. Not a tech job or an AI job. A nurse with a master's degree. So we're experiencing
a physician shortage. So more primary care goes to nurse practitioners. And again,
it's so interesting. Like we hear this conversation, oh, AI is going to replace doctors. We need
more nurses, for God's sake. State laws that keep expanding what they can do independently. And an
aging population needing more teen care management than the system has capacity for. Now notice,
BLS, Bureau of Labor Statistics, credited high exposure to AI, and it's still the fastest growing
job in the country. That's the clearest proof that exposure and risk are different things. AI can
draft notes, flag interactions, summarize a chart. It cannot examine the patient, hold legal responsibility
or sit with a frightened person for 20 minutes.
Diagnosis is one task inside the job, not the job.
Number three, we're still staying in healthcare.
Physician assistants with low AI exposure
growing by 20% year over year
with 35,000 new jobs added, $136,000 a year.
And now look at that last number
because this is the reason it's on the list at number three.
Out of 831 occupations,
physician assistants sit in the low bucket,
the bottom quarter.
The government's read built partly
on what people actually ask Claude and Copilot to do
is that these tasks are among the least touchable
by current AI in the economy.
$136,000 growing 21%, lowest exposure quartile.
Almost no other combination like that exists in the data.
Number two, oh, how many times have we heard
that software developers are gonna be replaced by AI?
And in reality, this job still pays $135,000
a year, grows by 10% with 95,000 openings a year
with yes, very high AI exposure.
So this job that the internet has been writing obituaries for
is projected to add 174,000 jobs.
This is the largest projected gain
of any occupation in America paying over $100,000.
So if you want to become a software engineer,
this is your sign.
Total headcount goes from about 1.7 million
to roughly 1.9 million,
by 2035.
Now, honestly, the picture underneath that number is mixed.
TechCrunch found in SignalFire's data
that while big tech hiring overall is down about 25% from 2019,
engineering hiring is only down 11%.
And engineers went from 46% of new hires to 55%.
Engineering is the most resilient function in tech,
not the most fragile.
On the other hand,
Indeed's hiring lab found US software postings
up to 10% of new hires.
Up 15% since Cloud Code launched,
while overall postings fell 7%.
But 71% of that gain came from senior roles.
So the job is growing.
The entry point is narrowing.
Number one, computer and information systems managers.
$175,000 a year,
plus 15.8%,
108,000 new jobs.
This is the person who decides what a company bills,
buys, and retires,
and what happens next.
What happens when it breaks?
IT directors, engineering managers,
CTOs of mid-sized companies,
and it's rated very high exposure.
A huge chunk of work is documents,
planning, review, and communications.
Still growing almost 16% at the top of pay scale.
Why?
Because the scarce thing about 2026
isn't the ability to produce technical output.
AI made that cheap.
The scarce thing is judgment under uncertainty
and accountability for the outcome.
Deciding what to do next,
deciding what to build,
getting blamed if something doesn't work,
deciding what not to build,
being the person whose name is on it when everything fails.
Look at the top of this list.
Managers, senior clinicians, senior engineers.
Pay is concentrating in the roles that decide
rather than roles that execute.
The obvious question is,
how do you move toward the deciding side?
You hand off the part that repeats.
And the honest state of that right now,
in the US, 28% of people use AI at all.
In Singapore,
it's 61%.
In the UAE,
it's 64%.
When researchers ranked what people actually do with it,
running an agent didn't even make the top 10.
Not because it's hard,
but because almost nobody has sat down and done it once.
So I wrote out my own setup.
Four steps, about 20 minutes.
It is no code and it works in ChatGPT2.
It's in my newsletter, Future Proof, free.
Link is in the description.
Now let's talk about the other direction.
The five occupations
shrinking fastest and what they have in common.
And by the way,
all five are rated very high AI exposure.
Number five,
customer service representatives down 5%.
Also a small number in terms of percentage,
but it's also 141,000 absolute numbers because 2.6 million Americans do this job.
And this is where the AI story is most visible in real data.
Goldman Sachs research covered by CNBC found US call center employment running 39% below trend.
Klarna is the case study.
Everyone quotes their CEO said their AI agent did the equivalent of about 850 people's jobs.
But here's the part that is worth quoting.
They wanted to offer a human support as kind of the VIP experience with higher quality and one number worth noting.
Again, even while shrinking, this occupation still has 289,000 openings a year.
The most of any job today declining doesn't mean disappearing and means the ceiling.
Is falling bookkeeping,
accounting and auditing clerks down 5% but on a base of 1.5 million people,
that's 85,000 jobs gone.
When you think about percentages,
they actually hide scale.
It's actually one of the largest absolute declines in the country happening one small business at a time payroll and timekeeping clerks down 15%.
This one's harder because it pays $58,000 above the national median and it's losing 25,000 out of 159,000 jobs.
Payroll is rules-based, high volume, repeatable, the shape of work software handles it really well.
What doesn't compress is the judgment around it, the exceptions, the audits, the person who knows why this quarter looks strange.
Data entry cures, they're down 25%, they're paying $41,000 a year and they're losing a quarter of the occupation.
And number one, word processors and typists, down 34%.
The occupation with the fastest projected percentage,
decline in America is word processors and typists.
People who type letters, reports and other documents from rough drafts, corrected copy or recordings.
So what separates the growing careers from the declining ones?
Look past the titles and start looking at the tasks.
Eric Buren of Sun gave me a useful way to do that.
I think almost every project can be divided into three parts.
There's defining the question, there's executing it once you've got it defined, and then there's evaluating it.
Did it really?
Did it really give you what you wanted?
How do you need to change things?
And through most of history, you know, people did all three parts.
There wasn't anyone else, right?
But now AI agents are getting really good at that middle one, executing once you've got it defined.
So I hope all of your listeners are playing around with cloud code or these other tools, and they'll see that once you ask the right question, these tools will execute and generate software.
Let's try that with your own work.
Take your last two weeks and write down what you actually did.
How many emails, how many hours went into that, the spreadsheets, meetings, problems.
I'm doing this for myself right now because I'm trying to figure out who to hire and how to delegate even more.
The best test you can do, if you're an entrepreneur, I went on vacation in the middle of the work week with my kids with no nanny.
That meant I had very limited access to my phone.
And whenever I had that access, I saw all the problems that are happening and I'm like, OK, this needs fixing, this needs fixing.
And then I came back and built a couple of agents.
And then you put each task into one of Eric's three columns.
Define, execute, evaluate.
Say you're preparing a weekly customer report.
Define what does the team need to learn.
Execute, collect the data and build the report.
Evaluate, are the numbers right?
What do they mean?
What should we do next?
What can I learn?
AI can help across all three.
But start with one repetitive task in the middle column.
Try using AI to handle that and then check the result.
Did it save you time?
Would you trust the output?
If it works, here's the question that
matters next.
What could I take responsibility for with that time back?
Maybe you could investigate why customers are leaving instead of only reporting how many left.
And I think as someone who runs a business, I love seeing entrepreneurship within my company where people start automating some of their tasks, but then they're seeing other loopholes that we can be fixing.
And I think this is our humankind in general.
Whenever people say, oh, AI is going to take over, I think we're going to figure out more problems to solve.
So here's the thing.
Your profession doesn't have to.
Disappear for your job to change completely.
The title can stay the same while the work underneath changes.
So this week, choose one task to improve and one responsibility you want to grow into.
What would those be in your job?
By the way, this define, execute, evaluate framework came from one of my favorite episodes on this podcast with Eric Bjornason, the Stanford economist who studies what AI actually does to wages and hiring.
I sat down with him and asked how you tell which parts of.
Your job get more valuable when AI gets cheaper.
The full conversation is right here and in the link in the description.
Thank you so much for watching this episode up to the very end.
I'll see you very soon on this channel.
Don't forget to subscribe.
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Podcast Summary
Key Points:
AI is augmenting rather than replacing most jobs, with high exposure to AI often meaning job growth due to evolving demands.
Occupations like healthcare managers, data scientists, and software engineers are growing rapidly because they require human judgment, oversight, and decision-making that AI cannot replicate.
Roles involving clinical training, healthcare operations, and IT management are rising due to system complexity, aging populations, and the need for human accountability.
AI excels at executing repetitive tasks, freeing professionals to focus on defining problems and evaluating outcomes—key skills that remain highly valuable.
The most declining jobs (e.g., customer service, data entry, word processors) are rule-based and repetitive, making them vulnerable to automation despite still having active demand.
A three-part framework—define, execute, evaluate—helps identify which parts of work will grow in value as AI handles execution.
Job titles may stay the same, but work responsibilities shift toward higher-level decision-making and strategic oversight.
The future of work lies in leveraging AI to automate routine tasks while humans take on more complex, judgment-driven roles.
Summary:
This episode explores how AI is reshaping the job market, not through mass replacement but through augmentation. While many routine, repetitive roles—like customer service, data entry, and word processing—are declining due to automation, new careers in healthcare, IT management, and data science are flourishing. The growth is driven by human needs for judgment, oversight, and strategic decision-making, which AI cannot replicate.
Jobs with high AI exposure are not disappearing; instead, they are evolving. For example, healthcare roles like nurse practitioners and physician assistants grow due to shortages and regulatory barriers to automation. Similarly, software engineering and IT management remain strong because they require accountability and complex planning.
The core insight is that work is shifting from execution to definition and evaluation—tasks where human judgment, ethics, and long-term thinking matter most. A simple framework—define, execute, evaluate—helps professionals assess which tasks can be automated and which should be taken on personally. The message is clear: jobs don’t vanish; they transform.
By using AI to handle routine work, individuals can reclaim time and focus on higher-value responsibilities, leading to greater productivity and career growth. The future belongs not to AI replacing humans, but to humans mastering how to work alongside AI.
FAQs
Gemini and Chrome is a browser integration that helps users with complex online tasks, such as restoring vintage motorcycles or summarizing long articles, by providing intelligent assistance and problem-solving.
Careers like medical and health services managers, data scientists, nurse practitioners, physician assistants, and computer and information systems managers are among the fastest-growing professions.
AI does not replace most jobs—it augments them by automating repetitive tasks. The human role becomes more valuable in areas requiring judgment, decision-making, and accountability.
Healthcare demands are rising due to an aging population, and many training tasks—like teaching nurses or pharmacists—require human supervision and cannot be fully automated by AI.
Use the 'define, execute, evaluate' framework: AI excels at executing tasks once defined. Focus on repetitive, rule-based tasks and assess whether the remaining work requires more human judgment.
Yes, roles like customer service reps, bookkeepers, and data entry clerks are declining, especially those involving repetitive, rule-based work that AI can automate.
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