AI in Software Development

How Do Developers Feel About Using AI Coding Assistants

AI is revolutionizing software development through tools that improve accuracy and productivity. It is automating tasks, accelerating the development process, and improving code quality. AI is helping in writing code, testing, debugging, resource allocation, and automation. It also checks the code quality, finds errors, and suggests improvements.

Most developers have a cautious and mixed attitude towards AI. Will the IT companies continue to hire dedicated developers, or will they turn to AI?

GitHub is saying that 88% of Copilot users have reported an increase in productivity while using a coding assistant. According to Daniel Koch, Senior Director of Creative at HubSpot, their engineering team has improved productivity three times by using an AI coding assistant. Also, Lori Beer, JPMorgan Chase’s global chief information officer, reports that AI coding assistant tools have allowed their software engineers to improve productivity by 10% to 20%.

Recommended reading: AI Automation: What It Is and How It Works in 2025

According to a survey report published on GitHub, 97% of respondents said that they have used AI coding tools at work at some point, a finding consistent across the U.S., Brazil, Germany, and India.

Source: https://github.blog/news-insights/research/survey-ai-wave-grows/

Sure enough, there are advantages. Many recognize the potential of artificial intelligence tools that can improve efficiency and automate tasks. However, there are also genuine concerns about accuracy and job security. As artificial intelligence tools keep evolving, the developer community needs to be aware of both the potential risks and benefits.

Can AI Take Over the Role of Software Engineers?

No, AI cannot replace software engineers in its current state because AI cannot:

• Manage the development process. In its present condition, the generated code is not 100% accurate and requires human review.
• As of now, it is difficult for AI to solve complex problems.
• AI needs engineers to provide specific inputs to get the desired output.

We did a little research and here is what some leading experts have to say:

Corey Coto, the Senior Vice President of product development at Pluralsight says, “AI won’t replace all software developers and engineers. AI will help developers accomplish more by freeing them up to work on higher-level problems. Companies that invest in increased automation to chain tools and AI together will amplify the impact human developers make.”

However, AI is certainly going to change how software engineers work. We conducted a small survey at the newwavedevs company, which is an IT staff augmentation, and in its opinion, AI coding tools will enable engineers to complete tasks earlier and improve their productivity.

Recommended reading: Revolutionizing Document Scanning and Capture with Artificial Intelligence (AI) Technology

How AI Will Impact the Developers

1. They will switch from design to platform thinking. Previously, developers used to write code for outcome-oriented design. With AI, the developers can focus on how platforms function in goal-oriented design.
2. AI will also draft user stories, requirements, and acceptance criteria. Developers will use tools to send information to business analysts, who will then align it with the overall strategy.
3. AI is already assisting basic UI design work so that human developers can focus on complicated interactive design elements. AI is laying the groundwork, and the developers are creating UI so that users can navigate easily.
4. Development teams will use AI to create code for review. With the assistance of AI, they will improve overall delivery.
5. The importance of testing will increase even more as AI produces more code. Teams need the architecture to test from every angle. Test architects will check end-to-end functionality. There will be new regression tests if there are issues.

AI is unlikely to replace human developers in the near future. The tech firms will keep looking for an IT staff augmentation company to hire skilled workers. The demand to hire IT professionals won’t reduce. However, many IT firms are likely to look for people who can use the AI tools to further improve the coding process.

Apply AI Where It Drives Revenue, Not Just Cost Savings

Automation isn’t just about finance, it also impacts fulfillment. With OrderAction, you can process sales orders faster by extracting and validating order data from emails, PDFs, EDI, and more.

Book a demo now

How AI Can Assist Developers

Artificial intelligence tools can improve efficiency and the overall development process. There are Generative AI tools that use ML to predict coding sequences. For example, GitHub Copilot can help developers brainstorm coding solutions, which changes their role from writers to decision makers. AI helps them reflect on the code at a higher level.

Here are the key areas where AI can help -

• Creating documentation - Generative AI tools leverage NLP for generating and maintaining documentation, which turns code into readable explanations. AI helps in documentation for projects, libraries, and APIs. AI can localize technical documents into several languages, which makes open-source projects accessible globally.
• Creating small code snippets - Developers can use AI to carry out code refreshes and small edits. It is perfect for updates to existing code. The tools can be used to find bugs, make adjustments, and improve the existing program. They can also identify inefficient or redundant parts to optimize the code and make it more efficient.
• Improving code readability - AI tools can improve code readability by making code suggestions, improving documentation, and automatically formatting. They can identify potential issues, optimize the code structure, and make important suggestions.
• Detecting errors - AI tools are also influencing testing and quality assurance. AI-based testing tools analyze code, identify potential vulnerabilities, and generate test cases automatically. ML techniques learn from past outcomes and predict code areas where there can be bugs. Developers can then identify and fix issues.
• Writing user stories - AI offers decent help in generating user stories and adapting them to how a team prefers. The tools help in addressing common concerns.

Recommended reading: How AI Algorithms Transforming Intelligent Process Automation

What AI Models Help Developers?

Here are some popular AI models for developers -

1. Qodo

Qodo makes intelligent code suggestions. It provides tailored suggestions, including docstrings. It breaks down source code or snippets with detailed descriptions. Qodo includes usage scenarios and insights. It also facilitates teamwork through Git integration, which enables code sharing.

2. GitHub Copilot

It can auto-complete code, streamline coding, and improve productivity. GitHub Copilot comes from a collaboration between Microsoft, OpenAI, and GitHub. It provides code suggestions and completes lines based on comments. There is a chatbot for developers that allows suggestions, questions, and debugging. The tool integrates seamlessly with popular IDEs like Neovim, Visual Studio, and JetBrains. It supports programming languages like Python, JavaScript, Golang, and TypeScript.

3. Amazon CodeWhisperer

Powered by Amazon’s advanced AI technology, this coding assistant improves both the speed and accuracy of coding. It completes functions, makes intelligent code suggestions, and also generates documentation easily. It offers tailored functions and snippets. It suggests subsequent lines and can also complete entire function bodies.

Steps to Adapt

We will see more of AI in software development. Thus, the developers need to adapt to include artificial intelligence in their coding work.

• Test no-code/low-code solutions - Low-code aids both non-technical people and professionals to collaborate. It allows people with different skills to work together.
• Explore the possibilities of AI - We see the use of AI in many industries. It is here to stay. The software industry needs to embrace it and find ways to make coding easier, quicker, and more efficient.
• Plan the implementation of AI in the long term - Developers must find ways to apply human intuition and problem-solving skills with the productivity and efficiency of AI.
• Analyze the risks - We already have many AI models. Development teams must analyze them and identify the one that works best for their needs. Select a tool that is a good match.

Software development is changing. AI cannot replace human developers, but the tools are helping them write better programs. With the increasing popularity of artificial intelligence, we will surely have smarter tools that will aid the process even more in the future.

Recommended reading: How AI is Transforming Financial Institutions