Has AI Rendered This Job Obsolete? A Career Projection for Software Developers
Whenever you open an app on your phone or a webpage on your computer, you are seeing the results of a software developer’s hard work. While software was initially created by developers line by line, technology has rapidly advanced, providing them with tools that have made the development process more efficient and automated.
Now, with the rise of artificial intelligence (AI), large portions of the software developer’s job are being completed by AI-powered tools. The question is, with the rise of AI, will you still need developers for your upcoming projects?
What is a Software Developer?
Over the last two decades, software developers have become some of the most vital employees on the planet. According to Statista, software developer jobs have been on the rise since their inception, with a staggering 3.2 million new jobs added between 2020 and 2024 alone. Software developers’ skill sets aren’t just about apps and websites; software developers are responsible for creating products that drive every technological device we use.
Software developers use programming languages and tools to build and deploy software applications. On a more granular level, they are responsible for managing their software throughout the entire development lifecycle. The developer works closely with clients, designers, project managers, product managers, quality assurance engineers, and other stakeholders to create each component of the software and then integrates them to form a cohesive product.
AI’s Role in Software Engineering
When AI first emerged on the market, there was a concern that it would replace software developers. However, as AI’s role in the field has been explored, it’s become clear that rather than taking over for software developers, it’s simply streamlining their workflows by completing the more repetitive aspects of the process, including:
- Code generation and completion
- Code review and testing
- Debugging and problem-solving
- Software maintenance
For software engineers, AI has had a dramatic impact on the efficiency of coding. In fact, GitHub reported a 55-60% time reduction when the AI-assistant Copilot performed a coding task. At Grio, our software developers are also seeing dramatic increases in productivity with the implementation of AI-powered tools, including Copilot, Cursor, and Windsurf.
Not only are software developers more efficient, but a second report by GitHub also found that 60-75% of developers feel more fulfilled in their jobs because AI-powered assistants, such as Copilot, let them focus on the more creative and interesting aspects of coding.
Where Projects Still Need Software Developers
While AI appears to have improved the software developers’ overall experience, it still has a long way to go if it wants to fully replace developers. In fact, according to the Bureau of Labor Statistics, jobs for software developers, quality assurance analysts, and testers are expected to grow 17% between 2023 and 2033.
This predicted increase in developer roles is likely caused by three things:
- Higher demand for developers who can provide AI integrations.
- Demand for AI-related experts, including machine learning developers and data scientists.
- AI’s inability to match a human’s creativity or innovation.
However, that’s not to say that the software developer’s job won’t undergo changes as the use of AI continues to expand. To stay competitive, software developers will need to focus their time on honing new and previously under-prioritized skills, including:
- Prompt Engineering: To maximize the potential of AI-powered tools, developers will need to learn how to engineer prompts that optimize output while minimizing errors.
- Architecture Planning: Developers are now spending more time on big-picture project management. While AI completes small pieces of the puzzle, developers are still essential for successfully combining the individual pieces into a cohesive product.
- Communication: Where before developers spent their time communicating with product managers, designers, and clients, their communication circle must now expand to include AI-related experts. Developers who can effectively bridge the gap between data and design will become increasingly valuable to software teams.
- Creativity and Innovation: With the use of AI for repetitive tasks, developers can spend more time bringing their uniquely human creativity and innovation to their projects. Where developers have previously balanced analytical and creative thinking, their ability to now give machine-generated products a human touch will become increasingly important.
Seasoned software developers and students entering the field may also consider a job shift toward AI-focused positions, such as a data scientist or machine learning engineer. These jobs combine the typical software engineer skill set with those of a mathematician, and will be crucial positions as AI continues to expand.
Challenges for Software Engineers Integrating AI
Just like with any new tool, multiple parties must invest in AI’s implementation if it’s to be used successfully. The creators of AI tools must work to make integration as seamless as possible to minimize the learning curve, companies must invest in training for their developers, and developers must dedicate time to learning how to use the tools.
Once developers have begun to incorporate AI coding assistants in their workflows, they still face additional changes, some of which include:
- Staying Up-to-Date: Given the vast number of use cases that AI coding assistants provide, software developers must continually improve their workflows and stay informed about tool improvements to remain competitive in their field. Maximizing the potential of AI will require intelligent implementation, targeted measurement, and continuous improvement.
- Monitoring Security and Data Privacy: The challenge of security and data privacy is not unique to developers, nor are developers immune from the pitfalls that cyber threats pose. As developers increasingly rely on cloud-based AI assistants, they will need to understand and proactively manage how their code privacy is protected, what proprietary information they use and share, and how these models utilize their code. Although most creators of these tools have made privacy and security commitments, it is also up to developers to perform their own due diligence.
- Code Bias: When models are trained on biased or non-inclusive data, it introduces biases into the AI. While this may not immediately seem like a challenge for developers, biases are likely inevitable in AI coding assistants. Developers may see suggestions based on libraries that were preferred in the training data, recommendations that violate updated privacy protocols or regulatory requirements, or code that infringes on licenses. If developers don’t oversee the AI assistant’s work, this can lead to a loss of trust or legal ramifications for software developers and their clients.
Successful Software Developers Make Successful Products
At Grio, our AI initiative is allowing our developers to lead the AI transition. Whether we are creating AI integrations for your existing apps or utilizing AI assistants to get your app to market more quickly, our developers are here to ensure that you stay competitive in the age of AI.
To discover how our software developers can utilize AI-powered tools to turn your great idea into an even greater app, contact us for a free consultation.
