In short
How AI coding tools (e.g., “vibe coding” with natural-language prompts) affect software developers, productivity, and hiring demand, and what bottlenecks emerge (code review and testing).
Guest backgrounds
No named guests; the host is Sanjit Singh, U.S. Software Analyst at Morgan Stanley.
Key claims
AI is redefining developers rather than replacing them; software market and developer headcount should grow (estimates: $24B in 2024 to $61B by 2029; 30M paid developers in 2024 to 50M by 2029; BLS ~2% job growth through 2033).
Notable examples
teams report nearly doubling code capacity, cutting pull-request time by half, and 20% fewer incidents via increased test coverage; but “pull request fatigue” rises (3 reviewers vs 1) and automated testing gets overwhelmed because AI changes trigger full test runs. Future view: integrated AI + human workflow across coding, testing, security, and deployment.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Chapters
Tap a time to open that second in VOAI's Impact on Software Development
0:14 to 1:40
Exploring how AI is perceived to impact jobs within the software industry.
“There's been a lot of news stories and anecdotal accounts about AI taking over jobs, especially in the software industry.”
Growth in Developer Demand
1:40 to 3:08
Discussion on the increasing demand for software developers despite AI advancements.
“Companies may need fewer developers for repetitive work, but the overall demand for skilled engineers remains robust.”
The Future of Software Development
3:08 to 3:44
Insights on the future relationship between AI and human developers in software creation.
“Instead, large enterprises will likely favor an integrated approach where AI agents and human developers work side by side.”
Transcript
Automatic transcript. May contain errors.0:00Welcome to Thoughts on the Market. I'm Sanjit Singh, the U.S. Software Analyst at Morgan Stanley. Today, how AI is transforming software and what that means for developers. It's Friday, October 24th at 10 a.m. in New York. There's been a lot of news stories and anecdotal accounts about AI taking over jobs, especially in the software industry. You may have heard of Vibe Coding, where people can use natural language prompts, guiding AI to build software applications. So yes, AI is creating a world where software writes itself. But at the same time, the demand for human creativity only grows. The introduction of AI coding systems has dramatically expanded what software can do, fueling a surge in both the volume of code and the complexity of projects.
0:42But instead of shrinking the developer workforce, AI is actually supporting continued growth in developer headcount, even as productivity soars. We're estimating that the software development market will grow at a 20 % compounded growth rate, reaching$61 billion by 2029. And that's up from$24 billion in 2024. And in terms of the developer population, firms like IDC expected to jump from 30 million paid developers in 2024 to 50 million by 2029. That's a 10 % annual growth rate. Even the most conservative estimates, like those from the U.S. Bureau of Labor Statistics, see developer jobs growing at roughly 2 % per year through 2033, outpacing overall employment growth.
1:25So what does this mean for people behind the code? AI isn't replacing developers, it's redefining them. Routine tasks are increasingly handled by AI agents, and this frees up developers to become curators, reviewers, architects, and most importantly, problem solvers. The upshot? Companies may need fewer developers for repetitive work, but the overall demand for skilled engineers remains robust. As AI lowers the barrier to entry, the pool of people who can build software applications expands dramatically. But at the same time, the complexity and ambitions of projects rise, keeping experienced developers in high demand.
2:00No doubt AI coding tools are delivering real productivity gains. Some teams are reporting nearly doubling their code capacity and cutting pull requests times in half after adopting AI code assistance. Test coverage has increased sharply, resulting in 20 % fewer incidents for some organizations. But there is a catch with all this AI-generated code. It's creating significant new bottlenecks downstream. An example of this is code review, which is becoming a major pain point. Many organizations are experiencing pull request fatigue, with developers rubber-sampling changes just to keep up. Some teams now require three reviewers for AI-generated change, compared to just one before.
2:40And in terms of automated testing, systems are getting overwhelmed because every change made with AI sets off a complete round of tests. Now, we estimate productivity gains from AI and software engineering at about 15 to 20 percent. But in complex projects, the gains are much lower, as the volume of new code often means more bugs and more rework, and hence more human developers. So where do we go from here? In our view, the future isn't about fully autonomous software development. Instead, large enterprises will likely favor an integrated approach where AI agents and human developers work side by side.
3:17AI will automate more of the software development lifecycle, and that only includes not just coding, which coding typically accounts for 10 to 20 % of the software development effort, but other areas like testing, security, and deployment. But humans will remain in the loop for oversight, design, and decision-making. And as software gets cheaper and faster to build, organizations won't just do the same work with fewer people, they will likely do more. In short, the need for skilled developers isn't going away, but it's definitely evolving. And in the age of AI, it's not about man versus machine, it's about man with machine.
3:51And so with more software, we see more developers. Thank you for listening. If you enjoyed the show, please leave us a review wherever you listen and share thoughts on the market with a friend or colleague today.
4:06Sanjit Singh:and based on information available when created. It is not an offer or solicitation, nor is it tax or legal advice. It does not consider your financial circumstances and objectives and may not be suitable for you.
From the publisher
Our U.S. Software Analyst Sanjit Singh explains how AI is reshaping software development and why the future for the sector may be brighter – and busier – than ever.
Read more insights from Morgan Stanley.
----- Transcript -----
Welcome to Thoughts on the Market. I’m Sanjit Singh, the U.S. Software Analyst at Morgan Stanley.
Today: how AI is transforming software and what that means for developers.
It’s Friday, October 24th, at 10am in New York.
There's been a lot of news stories and anecdotal accounts about AI taking over jobs, especially in the software industry. You may have heard of vibe coding, where people can use natural language prompts, guiding AI to build software applications. So yes, AI is creating a world where software writes itself. But at the same time, the demand for human creativity only grows.
The introduction of AI coding assistants has dramatically expanded what software can do, fueling a surge in both the volume of code and the complexity of projects. But instead of shrinking the developer workforce, AI is actually supporting continued growth in developer headcount, even as productivity soars.
We’re estimating the software development market will grow at a 20 percent compound annual growth rate, reaching $61 billion by 2029. And that’s up from $24 billion in 2024. And in terms of the developer population, [research] firms like IDC expect it to jump from 30 million paid developers in 2024 to 50 million by 2029 – that’s a 10 percent annual growth rate. Even the most conservative estimates, like those from the U.S. Bureau of Labor Statistics, see developer jobs growing roughly 2 percent per year through 2033, outpacing overall employment growth.
So, what does this mean for people behind the code?
AI isn’t replacing developers. It’s redefining them. Routine tasks are increasingly handled by AI agents, and this frees up developers to become curators, reviewers, architects, and most important problem-solvers.
The upshot? Companies may need fewer developers for repetitive work, but the overall demand for skilled engineers remains robust. As AI lowers the barrier to entry, the pool of people who can build software applications expands dramatically. But at the same time, the complexity and ambitions of projects rise, keeping experienced developers in high demand.
No doubt, AI coding tools are delivering real productivity gains. Some teams are reporting nearly doubling their code capacity and cutting pull request times in half after adopting AI assistants. Test coverage has increased sharply, resulting in 20 percent fewer production incidents for some organizations. But there is a catch with all this AI-generated code. It’s creating significant new bottlenecks downstream.
An example of this is code review, which is becoming a major pain point. Many organizations are experiencing pull request fatigue, with developers rubber-stamping changes just to keep up. Some teams now require three reviewers for AI-generated change, compared to just one before. And in terms of automated testing, systems are getting overwhelmed because every change made with AI sets off a complete round of test.
Now we estimate productivity gains from AI in software engineering at about 15–20 percent. But in complex projects, the gains are much lower, as the volume of new code often means more bugs and more rework – and hence more human developers.
So where do we go from here?
In our view, the future isn’t about fully autonomous software development. Instead, large enterprises are likely to favor an integrated approach, where AI agents and human developers work side by side. AI will automate more of the software development lifecycle. And that not only includes coding – which, coding typically accounts for 10-20 percent of the software development effort – but other areas like testing, security, and deployment. But humans will remain in the loop for oversight, design, and decision-making. And as software gets cheaper and faster to build, organizations won’t just do the same work with fewer people – they likely will do more.
In short, the need for skilled developers isn’t going away. But it’s definitely evolving. And in the age of AI, it’s not about man versus machine. It’s about man with machine. And so with more software, we see more developers.
Thanks for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.