Code Smarter, Not Harder: The Role of AI in Programming
.b378a3d0.svg){kind=small}
Got a big business goal of optimizing software development costs for this year? Want to leverage AI to improve your business, but not sure how to get started? This blog post can enlighten you on using AI to foster your software development process.
Did you know that 55% of companies already use AI, and another 45% plan to use it soon? Companies like Salesforce and Meta have improved the productivity of their software developers by 30%.
There is a lot of content on the web that talks about how AI is going to disrupt the software industry either by eliminating software development jobs or through significant productivity improvements. The real impact would be somewhere in the middle. This blog post explores how AI tools can help optimize your investment in programming and software development.
Leveraging AI in Programming and Software Development
Through prompt engineering, developers can generate code snippets, get answers to specific questions, get concise summaries from long documentation, and perform other development-related tasks. Tools like ChatGPT, GitHub copilot, etc., help automate repetitive coding tasks leading to significant timesaving.
Role of AI in Various Areas of Software Development
Since AI can handle several important tasks in software development, developers no longer have to be the jack of all trades. Areas where AI can assist are:
Benefits of using AI in Software Development
As discussed above, AI tools help reduce manual coding efforts by automating code generation, debugging, and other development-related tasks. Some of the key benefits of using AI in SDLC and operations are:
1. Increased Productivity and Efficiency
We all strive to boost productivity and achieve great results. AI helps you achieve exactly that. Using AI, you can automate repetitive tasks like, code reviews, test case generation, testing, documentation, etc. Thus, developers can save time and energy, and focus on more complex tasks. AI-powered tools like continuous integration and continuous deployment (CI/CD) solutions automatically manage builds, run tests, and deploy applications. This facilitates seamless project management. Also, software developers spend a lot of time researching and learning new tools. GenAI can be used as a partner to brainstorm ideas and ask it to generate sample code for a complex idea. Programmer still has to take the sample code in the actual solution. This can increase productivity a lot.
2. Enhanced Code Quality
You know how important code quality and accuracy are in software development. Poor code affects the overall efficiency of the project. Here’s one of the critical areas where you can leverage AI in programming. AI-driven code review tools help you analyze code, identify critical errors, and suggest improvements. Besides this, AI tools adhere to coding standards and best practices helping you produce consistent, robust, and maintainable code.
3. Cut down Development Costs
Who doesn’t like to save money? With reduced efforts in traditional extensive manual coding and testing, you can achieve notable cost savings. Despite the initial investment in AI infrastructure, the long-term ROI is substantial.
4. Faster Time- to-Market
With AI, you can complete projects faster and deploy high-quality software quickly. Your products reach the market swiftly, giving you a competitive edge and enabling you to quickly respond to market demands.
5. Deliver Better User Experience
Artificial Intelligence empowers you to create smooth, engaging user experiences tailored to individual preferences and needs. Using AI in programming reduces the learning curve, enhances user satisfaction, and makes your software more accessible.
Popular AI-based Software Development Tools
Be it for code generation, app building, testing, or any other software development activities, there are plenty of AI-based tools and IDEs that are now available in the market. Here we’ll familiarize with a few hand-picked tools that can help accelerate your software development process.
- GitHub Copilot: a code completion tool that assists developers to write code and generate suggestions directly within their IDE. It leverages machine learning models to provide context-aware code completions, making coding faster and more efficient.
- ChatGPT: a language model that understands and responds to natural language input, giving contextually relevant answers and generating coherent text.
- Microsoft Intellicode: a coding productivity tool that integrates into Visual Studio and provides intelligent suggestions based on coding patterns, helping developers write better code faster. It even gives context-aware recommendations and automates repetitive coding tasks.
- Open AI Codex: a model developed by OpenAI to assist developers in writing software and automating coding tasks. It understands and generates code in multiple programming languages.
Who Can Use AI in Software Development?
AI makes software development more collaborative and helps bridge the gap between technical and non-technical users. AI tools are no longer limited just to data scientists and developers. With the coming of low-code app platforms like Oracle Apex, Microsoft Power Apps, etc., any enthusiasts with minimum technical expertise can use AI to create apps. As a result, AI tools and technologies are accessible to a wide range of industries and professionals.
Challenges of using AI in Software Development and How to Avoid it
- Debugging may be difficult in the future: If developers use AI-generated code without clearly understanding how it works, it may become difficult to debug when errors occur in the future. To avoid this, developers should not blindly use the AI-generated code. Instead, they should clearly understand the code and maintain proper documentation for the same.
- Over-reliance on AI tools: As AI tools easily come in handy, developers may rely too much on AI. This can hinder their creativity, problem-solving, and critical thinking skills. To manage this problem, encourage developers to use AI as an assistance tool. Not as a replacement for their skills and expertise.
- AI Hallucination: Due to incorrect assumptions made by the model or insufficient training data, AI models sometimes generate nonsensical, misleading results. This can have significant consequences for your software development project. To prevent this issue, make sure the AI tools you use are well-tested, unbiased, and trained properly on high-quality data.
The Takeaway
As we’ve explored throughout this post, integrating AI into your software development can bring exponential benefits. As AI tools continue to evolve, it democratizes software development, by enabling innovation, and transforming industries. It makes development processes more streamlined than ever before.
For business leaders and executives, the message is clear: investing in AI integration is investing in your company’s growth and overall competitive edge.
However, you need to be also aware of the downsides of AI. So, ethical considerations and the role of human oversight are crucial to ensure responsible and balanced integration of AI into the software development lifecycle.
If you want to up your productivity and delight your customers with the best services and experiences, leverage AI.
We can guide you in your AI journey and help you achieve your goals faster. Reach out to us.
Expeed Software is one of the top software companies in Ohio that specializes in application development, data analytics, digital transformation services, and user experience solutions. As an organization, we have worked with some of the largest companies in the world and have helped them build custom software products, automated their processes, assisted in their digital transformation, and enabled them to become more data-driven businesses. As a software development company, our goal is to deliver products and solutions that improve efficiency, lower costs and offer scalability. If you’re looking for the best software development in Columbus Ohio, get in touch with us at today.
Do You Have a Data Analytics Vision?
May 31, 2024
The State of Web Application Development (Is WebAssembly the Future?)
May 31, 2024
Code Smarter, Not Harder: The Role of AI in Programming
January 31, 2025
