AI will transform the role of the junior application developer

To better understand what the broader future of work looks like, ServiceNow paired up with research partner Pearson for the third year in a row to produce the 2025 Workforce Skills Forecast. This study assesses how AI agents, and related technologies such as generative AI (GenAI) will impact workers and organizations in the next five years.

[NOTE: Experienced human writers and editors used AI to help research and draft this article.]

ServiceNow and Pearson used machine learning to mine labor market data in 10 countries (Australia, Canada, Germany, India, Japan, Saudi Arabia, Singapore, the UAE, the UK, and the U.S.). The resulting analysis maps the changing relationship between people and AI in the workplace and predicts that AI will change the mix of skills required for people and organizations to thrive.

Long-term impacts on junior application developers:

1. Job polarization: On the one hand, entry-level developers may find fewer entry points into the industry because AI will diminish organizations’ reliance on hiring for simpler tasks. On the other hand, midlevel and senior developers specializing in training, adapting, and deploying AI-based development workflows will see greater demand.

2. Shift in required skill sets: While traditional development skills will remain critical, the role will require a growing knowledge of AI tools (e.g., fine-tuning AI prompts for coding), understanding machine learning workflows, and maintaining AI ethics and decision-making frameworks.

By 2030, the impact of AI and other advanced technologies on the junior application developer role will be moderate to high.

Despite changes to the role, an additional 44,700 application developers of all levels are projected to be needed in the U.S. to satisfy increasing demand over the next five years, according to our research.

The tasks associated with a junior application developer include writing clean and efficient code, debugging, updating software, and collaborating with team members to implement new features and resolve issues. They may also assist with technical support for internal teams or customers.

According to ServiceNow University, the average annual salary for a midlevel developer who specializes in the ServiceNow AI Platform is $115,200.

The key skills/mindsets of a junior application developer include:

• Programming proficiency: Junior developers still need a solid foundation in programming languages such as Java, Python, C#, and JavaScript. These languages are used in application development and form the basis of writing efficient and functional code.
• Database literacy: Familiarity with database technologies such as SQL, PostgreSQL, and MongoDB is essential for working with data-driven applications.
• Problem-solving and debugging: Debugging and troubleshooting code are critical skills for identifying and resolving errors in applications.
• Version control systems: Tools such as Git are vital for collaborating with other developers and managing code changes in a shared environment.
• Basic knowledge of software development lifecycle: Junior developers should understand the stages of software development, including planning, development, testing, and deployment.
• Effective communication skills: Working in teams requires clear communication, especially when coordinating with senior developers, project managers, and other stakeholders.
• Growth mindset: Technology evolves rapidly, so a willingness to learn new frameworks, languages, and tools is crucial.

AI is already changing the role of junior application developers by reshaping workflows, expectations, and the skills needed to succeed in the field. While AI can enhance productivity and simplify tasks, to stay relevant as a developer requires a shift in skills and expectations that will redefine the role.

According to our research with Pearson, 36% of a U.S.-based junior application developer’s job will be transformed by AI over the next five years. Only about a fifth of that transformation will come from the introduction of agentic AI, while the rest will come from non-agentic AI technologies such as GenAI (the basis for AI-powered coding assistants) and machine learning.

The impact of this transformation on the role will be equivalent to 14.2 hours saved per week per person by 2030—2.7 hours saved due to agentic AI and 11.5 hours by non-agentic AI. Major time savings include a 45% reduction in the time spent developing and modifying software systems due to the adoption of agentic AI. Non-agentic AI will reduce by a whopping 62% the time currently spent managing and supervising technical personnel and collaborating with analysts, engineers, and programmers on system design. Junior developers will also see a 48% reduction in time needed to analyze system performance and outcomes as AI takes on the heavy lifting.

As agentic AI becomes increasingly prevalent in the workforce, junior application developers can take the following measures to remain relevant and even thrive.

• Reskill and upskill: Tech workers should prioritize learning new AI-related skills, such as AI governance, ethics, and systems architecture. As agentic AI takes on more complex roles, human supervision remains indispensable. This could include understanding how AI agents interact with workflows and learning how to collaborate effectively with them.
• Learn domain-specific and business-focused applications: If working in healthcare, finance, or logistics, workers should focus on how AI solves specific problems in that particular sector. Agentic AI creates opportunities for developers who understand both technology and its applications across industries. Additionally, those skilled in translating technical concepts into business strategies will be highly valuable.
• Lean into human judgment: While AI excels at automation and augmentation, it can’t yet replicate human creativity, emotional intelligence, or ethical reasoning. Developers should lean into these human qualities to complement AI systems. Roles requiring nuanced contextual understanding will expand, creating opportunities to integrate human decision-making with AI capabilities.
• Develop expertise in AI oversight and management: As agentic AI systems increasingly act independently, they will require sophisticated human oversight and checks to ensure proper function and ethical alignment. Learning these skills can position developers—and all tech workers—as critical contributors within AI-integrated teams.
• Embrace emerging job categories: The introduction of agentic AI will lead to entirely new job categories. Developers and other IT workers should be proactive in exploring these opportunities, especially in fields such as AI-human interaction design, AI ethics consulting, and AI maintenance.

By honing these skills and adopting a mindset of continuous learning, junior applications developers can maintain relevance and thrive alongside agentic and non-agentic AI. Remember: Agentic AI is a tool, not a replacement for human ingenuity. By focusing on adaptability, continuous learning, and leveraging uniquely human traits, application developers—and tech workers more broadly—can position themselves as indispensable collaborators in an AI-driven future.

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