• AI coding tools have reshaped the tech industry.
  • Developers are leveraging AI tools for enhanced productivity, smoother workflow, and accelerated development cycles.
  • This has led to a shift in the in-demand skills among developers, with a focus on problem solving and ethical use.
  • Tech talent can stay ahead of the curve by treating AI as a partner and not a threat. 
  • This means upskilling, joining AI developer communities, and actively showcasing their work.
  • Employers need to encourage AI collaboration and train employees.

 

Person holding phone while coding on laptop


Gone are the days when artificial intelligence was just a fictitious entity in high-action thriller movies or an obscure fixture of the future in sci-fi flicks. Today, AI has permeated nearly every strata of our lives and is reshaping our interactions with not just the internet, but softwares as well. 

This has left tech developers scrambling to leverage AI capabilities to gain an edge. Here’s everything you need to know about the application of AI in assisted software development and how it’s reshaping the tech market for IT professionals and tech leaders who are striving to get their workforce AI-ready.

How AI Tools Are Transforming Coding Practices

With AI tools like Claude and Copilot revolutionizing workflows, it’s led AI to become a collaborator in application development. While this has directly accelerated development cycles for businesses and software engineers, there are a few key ways these tools are changing key practices.

  • Code Autocompletion & Generation 
    Developers are relying on AI tools for assistance in writing boilerplate code, functions, and even entire modules, redefining the limits of AI assisted software development.
  • Bug Detection & Optimization 
    Since AI can review code, it’s often harnessed to suggest fixes and optimize performance of programs (like SonarQube AI plugins or DeepCode).
  • Collaboration & Documentation 
    Developers are using tools like ChatGPT to produce clear documentation or break down complex code logic in simpler terms.
  • Natural Language to Code 
    New developers can now even describe what they want their program to do in plain English, while AI tools turn these instructions into functional code.

These transformations in application development using AI have meant lower barriers for new developers and a significant reduction in repetitive tasks. But over-reliance on these tools is a major concern due to the inconsistency of code quality. It’s crucial not to take AI-generated solutions at face value without human oversight.

In-Demand Skills in an AI-Enhanced Development World

This involvement of AI in application development has caused a shift in the demand for skills.

  • AI-Augmented Programming

    Rather than fearing AI, developers need to learn how to work with it and harness it for better software development.

  • Problem Solving

    When routine tasks are handed off to AI tools, humans are left free to think about logic, design thinking, and architecture.

  • Basic Knowledge of AI/ML Concepts

    Even non-AI developers are required to understand the basics of how AI tools work.

  • Ethical AI Use

    Tech talent is expected to exercise responsible use of AI tools. Fairness, security, and accountability are major concerns when using AI-generated code.

How Tech Talent Can Prepare

 

Woman with binary code projected on her face against a blue background

  • Curiosity is Rewarding

    Keep experimenting with different tools to code small projects or troubleshoot bugs. 

  • Continuous Upskilling

    As tools and tech hiring trends evolve, so should IT professionals. Take micro-courses on AI in software and application development.

  • Portfolio Building

    If you’ve worked on projects with AI assisted software development, showcase your experience through a digital portfolio.

  • Get Active in the Community

    Joining AI developer communities is a great way to learn from your peers and keep abreast of industry trends. 

How Employers Can Leverage AI to Stay Competitive

This new era of collaborative coding means tech employers need to adapt to stay competitive. 

  • Streamlining Development Cycles: By adopting AI coding assistants, product delivery can be accelerated.
  • Reskilling Teams: Bolster tech talent with internal training on AI in application development.
  • Rethink Hiring Criteria: Work with a direct hire staffing agency to recruit candidates with AI literacy, critical thinking, and adaptability.
  • Integration of AI into DevOps: Use AI for CI/CD optimization, predictive analytics, and automated testing.
  • Encouragement of AI-Enhanced Collaboration: Create a space where developers can rely on AI for better communication of ideas, documentation, and cleaner code.

The future of AI in application development is efficient, smart, and collaborative. And harnessing this potential of AI is crucial for developers hoping to stay ahead of the curve. Trust Harvey Nash for industry expertise and candidate sourcing.

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