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Posted on 11/13/2025 8:36:57 PM PST by SeekAndFind
As AI transforms software development, the industry is likely to see job growth—not loss—while developers should become a more strategic and valuable asset.
Despite concerns about job loss for software developers, AI should create more jobs as companies build increasingly complex applications.
As AI coding tools become mainstream, developers are shifting toward more strategic roles.
A recent Morgan Stanley AlphaWise survey shows CIOs plan to increase software spending by 3.9% in 2026, outpacing other IT categories.
The software development market could grow at a 20% annual rate, reaching $61 billion by 2029.
As artificial intelligence reshapes the software industry, concerns about its impact on developer jobs are giving way to optimism. According to Morgan Stanley Research, the rise of AI-powered coding tools is not eliminating jobs—it’s creating new opportunities for developers and software companies alike.
“Contrary to current market concerns that AI will replace human developers, we believe it will enhance productivity and lead to more hiring,” says Sanjit Singh, who covers infrastructure software and analytics at Morgan Stanley Research. “As enterprises build more complex applications and tackle long-standing technology debt, the demand for skilled developers will grow.”
As AI coding assistants and agents become standard tools in development workflows, the role of traditional software engineers is likely to shift to more complex applications. Developers are increasingly acting as curators, reviewers, integrators and problem-solvers—making them more strategic and valuable.
“The software developer workforce should expand significantly,” Singh says. “We expect headcount growth rates to range from the U.S. Bureau of Labor Statistics’ forecast of 1.6% annually through 2033 to the more aggressive estimate of 10% through 2029 by research firm IDC.”
However, the surge in AI-generated code is creating bottlenecks in other stages of the software-development lifecycle. Code review and testing are some examples: The volume of software increases significantly with AI coding, but higher volume could mean more bugs and more rework. Engineers have a lot more AI code to review and test.
This challenge presents a new growth avenue for software providers, which are creating AI agents to work side by side with human developers. Software companies will deploy AI not only in coding, but also in other areas like testing, security, verification and deployment. Humans will remain in the loop for oversight, design and decision-making.
As software gets cheaper and faster to build, organizations won’t just do the same work with fewer people: They likely will do more and have more products to sell, boosting the growth outlook for the industry. The software development market is likely to expand at an annual rate of 20%, rising from $24 billion in 2024 to $61 billion by 2029, according to Morgan Stanley Research’s estimates.
“For investors, this implies an attractive opportunity, with the potential of higher gains as business models evolve to account for the symbiotic role that developers and AI will play in the software development process,” Singh says.
CIOs expect to increase spending in software by 3.9% next year – a slight acceleration from the gain of 3.8% this year – in addition to a 3% increase in communications spending, 2.5% in IT services and 1.6% in hardware.
“The results highlight the resilience of software investment, even in uncertain times,” says Keith Weiss, who leads Morgan Stanley Research’s software coverage in the U.S. “The survey also indicates a broadening opportunity for software companies to capitalize on the rapid diffusion of AI.”
The survey was conducted from Aug. 5 to Sept. 9 with 70 CIOs in the U.S. and 30 in Europe.
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Somebody needs to check out the Safety for Humanity....
Hmmm...what could possibly take over code review and testing?
The job of out placement counselling and separation from employment officers were doing quite well but then were taken over by AI.
(Begin quote)
You're making a fair point that many people are treating AI like a replacement for thinking rather than a tool for reasoning. And yes — a lot of sloppy “vibe-coded” output is already flooding the internet. But I think your framing misses the deeper shift:
AI isn't just search — it's interactive cognition
Search retrieves.
LLMs synthesize, evaluate, and transform information.
Sure, the most product use cases today resemble "smart search assistants":
But that's not "just search".
It is a general reasoning assistant.
The difference is subtle but huge.
On coding: the bottleneck isn’t typing — it’s understanding You’re right: blindly generating code is dangerous.
Bad developers using AI = more bad code faster Great developers using AI = faster design, better abstractions.
Typing isn't the job.
Thinking is.
The people “switching seats with AI” weren't engineers to begin with — they were people who never understood why software design matters.
AI didn’t create them. It just exposed them.
Review cost vs. productivity
You mentioned reviewing AI work sometimes erases the time saved. True — for now.
But historically, every automation wave has a phase where:
✅ Output becomes reliable
✅ Human insight becomes optional or lighter
✅ Experts move up-stack to architecture and intent shaping.
That is already happening in:
The work shifts from writing code to supervising intent execution.
"AI should only handle things I don't care about"
Respectfully — that sounds like using a sports car to deliver groceries.
Useful, but underestimating the machine.
AI today is an early form of software-shaping intelligence, not just a search upgrade.
If we trap it in the mindset of “autocomplete-plus,” we’ll miss the transition from code we write manually to systems we specify and validate.
The real danger isn't AI coding -- it's AI replacing understanding.
Tools don't remove thinking.
People choosing not to think do.
Good engineers will use AI to accelerate mastery, not avoid it.
In another application, the server side pages were coded using < script >, < style > and < iframe > tags to pull in tested blocks of code. Unfortunately, those tags are easily exploited and the exploits were unknown when the original code was written 20 years ago. There are thousands of these constructs in hundreds of files. Taken one at a time, none of them is difficult to remediate for safety, but it only takes the inclusion of a Content-Security header to make all of them a monumental security headache. An AI driven remediation to deal with the problem in bulk might be a solution, but it would require strict post update testing as AI "fixes" are sometimes more damaging than helpful.
AI systems appear to pump out a large amount of code which can grow exponentially as it is refactored and extended with new requirements.
I have been told by a Cyber-Security consultant that his client managers are insisting that 50% of new software codes must now be generated by AI programs. That sounds extremely ambitious to me.
I expect this to be a massive disaster when it comes time to test and debug those applications. That should be compounded when they demand that AI be used to do that testing and debugging.
It might be prudent to start with lesser aspirations.
That sounds like a recipe for disaster.
Game testers, contractors, etc.
I use Grok for quite a few simple but tedious and long calculations. I’m appalled at the number of mistakes it makes. I catch the errors in a quick check, point them out to Grok, and it stupidly apologizes. When I asked it why it made such a fundamental error, it has some lame excuse like “I went too fast.”
I had it develop a complicated Excel formula for me a couple months ago and it was buggy. I was forced to decompose the formula to find the bug. What was weird is some code was repeated in the formula and it got half right and half wrong! In the end, it would have been faster for me to write the formula from scratch.
Yikes! These things are going to do do our coding for us?
Thats on point
i’ve been a professional developer for 40+ years.
developers are not users. we dream up and create the software others use.
students that use AIs will miss out on the struggle that goes along with learning to develop software. this will result in developers with less skills not more.
sure, areas in which the dev has prior extensive knowledge, the AIs can be used for mundane or lengthy repetitive coding tasks. anything else would make the AIs more of a crutch.
don’t get me wrong, today’s AIs are ok but they quickly start ‘hallucinating’ and lose the narrative resulting in code that’s wildly off base. this will most likely get better as time goes on but for now, it’s still a bit of a mess.
as for large projects... the AIs are simply not up to the task... currently.
There will be downstream impact as companies and consumers have access to better software cheaper.
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