Why AI Won’t Kill Software Companies

But Will Change Everything

(Note: This is my personal view - What follows is speculative, not fact.)

Let’s be clear: I don’t know what AI will do in 5 years. No one does. But based on what I see today working as a software developer, here’s what I think might happen.

Over the last 30 years, software development has changed dramatically. Back then, most software was written in low-level languages like Assembly, C, or Fortran, which required a deep understanding of how computers work. Today, high-level languages like C#, JavaScript, and Python have made coding faster and easier. These languages let developers do more with less code by abstracting away the complex details of machine language and using syntax that’s closer to human language.

Tools like GitHub Copilot or Cursor and Large Language Models (LLMs) like GPT, Claude, and DeepSeek have taken this a step further. Now, you can describe what you want in plain English—like “add a blue button that plays the selected song”—and the AI generates the code for you. It’s like having a super-smart assistant who does the heavy lifting.

However, while AI is transforming how software is built, today it’s still just a tool. AI can handle repetitive tasks, fix bugs, and build simple components, but it’s the developers who guide the process, oversee code changes, ensure quality, and tackle complex challenges for building more complex software products.

I suspect that in the near future, we might not even call it “coding” anymore. Instead, developers will become “AI instructors.” Their job will be to describe problems in plain language, manage AI tools, and ensure everything works as intended. The focus will shift from writing lines of code to designing systems, solving problems, and guiding AI to do the work. This could make software development faster, cheaper, and more accessible to everyone.

Why Humans Still Matter

Even as AI gets better, developers won’t become obsolete. Here’s why:

1. Problem-Definers:
   AI is great at following instructions, but it needs someone to tell it what to do. Developers (or other experts) will still be needed to come up with ideas, design systems, and give the AI clear, precise prompts. This creative and strategic work is something AI can’t do on its own.

2. Code Doctors:
   AI can generate code, but it will not always be perfect and might introduce bugs. We’ll still need experienced developers to understand, review, fix and optimize the code AI produces.

3. Domain Experts:
   AI can’t replace deep industry-specific knowledge. For example, building software for healthcare or finance requires understanding complex regulations, workflows, and user needs. Developers with this expertise will be in high demand to guide AI and ensure the software meets real-world requirements.

4. Quality Guardians:
   While AI is getting better at testing software and finding bugs, humans are still essential for ensuring the software feels right to users. Does it meet their expectations? Is it secure? Does it handle edge cases effectively?

The Changing Dynamics in the Age of AI

With AI handling many tasks, software companies will require fewer developers to achieve the same level of productivity, and the role of developers will shift toward higher-level tasks like system design, AI oversight, and domain-specific problem-solving. This shift, however, poses a challenge for junior developers, as many of their traditional tasks such as writing basic code or fixing simple bugs can be handled by AI. If junior developer roles diminish, it could lead to a future scarcity of skilled senior developers, since every experienced professional today began their career by learning the basics in entry-level roles.

That said, while the overall number of developers may decrease, the demand for specific types of expertise will grow. Developers who can understand, refine, and optimize AI-generated code, or who possess deep industry-specific knowledge, will become increasingly valuable and more expensive.

AI isn’t just changing how software is built—it’s also speeding up the pace of innovation. Companies can now develop and release software faster than ever before. But this also means their competitors can do the same. The result is a faster-paced, more competitive industry where standing out requires more than just speed.

To thrive in this environment, companies and developers will need to focus on creativity and unique expertise. It’s no longer enough to build software quickly; you need to build software that solves hard problems, meets specific needs, and delivers exceptional value.

Which Software Companies Might Benefit?

Some companies that adapt to the AI-driven future will not only survive but thrive. Here’s what sets them apart:

1. Specialists:
   Companies that solve hard, specific problems like cybersecurity for nuclear plants or software for rare medical conditions will thrive. AI can’t easily replicate this kind of expertise.

2. Niche Players:
   Companies operating in small, underserved markets with little public knowledge and hard-to-reach customers have a unique advantage. Their deep understanding of these niches and strong customer relationships make it difficult for competitors to enter, even with AI.

3. Ecosystem Owners:
   Companies that own platforms with strong network effects (like app stores, collaboration tools, marketplaces or social media apps) will continue to dominate. The more users and integrations they have, the harder it is for competitors to catch up. These ecosystems create a moat that AI alone can’t break.

4. Data-Rich Companies:
   Firms with unique datasets (e.g., 10 years of farm equipment repair logs) will have a huge advantage. AI thrives on data, and companies with unique datasets can train better models, deliver more accurate results, and offer more personalized solutions.

AI could help these companies maintain their competitive advantage while reducing labor costs and potentially increasing quality and profit margins.

The Rise of Solo Developers and Small Teams

One of the most exciting opportunities created by AI is the ability for solo developers or small teams to build software that once required large teams. With AI handling much of the coding, the cost structure for these smaller players is very low. This allows them to enter markets more easily and sell software at competitive prices.

For example, a solo developer with a great idea and some industry knowledge can now build and launch a product without needing a large team or a big budget. This levels the playing field and opens up opportunities for innovation in underserved markets.

However, this also means that markets with weak software moats—where products are easy to replicate—could face disruption. Smaller, agile teams can quickly undercut existing solutions, forcing larger companies to innovate or risk losing market share.

Which Companies Might Struggle?

Some software companies will struggle because of AI:

1. Generic Software Makers:
   Companies that sell basic, undifferentiated software (like simple CRUD apps or generic tools) will struggle. AI makes it easy for competitors to replicate their products, driving down prices and margins.

2. Slow Adapters:
   Businesses that don’t embrace AI or use it effectively will fall behind. They’ll face higher costs and slower development compared to competitors leveraging AI.

3. Over-Reliant on AI:
   Companies that rely too much on AI without human oversight risk creating low-quality or flawed products. This can damage their reputation and customer trust.

Conclusion: A New Era of Opportunities and Challenges

AI is transforming the software industry, creating opportunities for specialists, niche players, and data-rich companies, while posing challenges for generic software makers and slow adapters. Solo developers and small teams can now enter markets with low barriers to entry, but long-term success will belong to companies with strong moats like deep expertise, unique data, or robust ecosystems.

The key to thriving in this new era is not just using AI to cut costs, but leveraging it to create real value. Companies must focus on solving hard problems, building unique solutions, and staying ahead of the competition through innovation and expertise. In a world where AI makes it easier to build software, the winners will be those who use it to deliver something truly exceptional.