{"id":15992,"date":"2026-05-22T11:33:53","date_gmt":"2026-05-22T18:33:53","guid":{"rendered":"https:\/\/intuitblog.com\/?p=15992"},"modified":"2026-05-22T12:21:53","modified_gmt":"2026-05-22T19:21:53","slug":"how-to-use-ai-in-software-development","status":"publish","type":"post","link":"https:\/\/www.intuit.com\/blog\/innovative-thinking\/how-to-use-ai-in-software-development\/","title":{"rendered":"How to Use AI in Software Development"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">AI has crossed the line from experimental to expected in software development. In <a href=\"https:\/\/survey.stackoverflow.co\/2025\/ai\" target=\"_blank\">Stack Overflow\u2019s Developer Survey<\/a>, 84% of respondents said they use or plan to use AI tools in their development process, up from 76% in 2024. Among professional developers, 51% use AI tools daily.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Generative AI and large language models (LLMs) now show up across the full development cycle. From coding to design architecture, AI in software development is fundamentally changing the work.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This guide covers how to use AI in software development. We\u2019ll touch on the tools worth knowing and how to think about integrating them into real workflows.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Key Points<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Stack Overflow found that 84% of developers now use or plan to use AI tools, up from 76% in 2024, with 51% of professional developers using them daily.<\/li>\n\n\n\n<li>The productivity case for AI in software development is clear: According to DX, more than 9 in 10 developers use AI for code generation, refactoring, or review.<\/li>\n\n\n\n<li>Trust hasn\u2019t kept pace with adoption. Stack Overflow found that 46% of developers distrust the accuracy of AI tool outputs, compared with just 33% who trust them.<\/li>\n\n\n\n<li>Learning how to use AI responsibly in software development is vital. Not only can this build trust with the user, but it also helps make sure the end product works as intended.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Where AI Fits in the Software Development Process<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">AI now plays a role in nearly every stage of software development, beginning with the first conversations about what to build. The depth of integration varies by stage, but the common thread is that AI handles the repetitive lift while humans keep the judgment calls and ownership of the final product.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Here\u2019s where AI shows up across the lifecycle and what it does at each stage.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Planning and Design<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The software development lifecycle begins with requirement gathering, planning, and design\u2014all areas AI supports. Developers and product teams use it to:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Turn high-level concepts into structured requirements through natural language processing (NLP)<\/li>\n\n\n\n<li>Brainstorm features based on user needs and business goals<\/li>\n\n\n\n<li>Predict future requirements to inform early design and planning<\/li>\n\n\n\n<li>Support core architecture decisions on system structure and technical design<\/li>\n\n\n\n<li>Analyze large datasets using neural networks to generate scalable frameworks<\/li>\n\n\n\n<li>Suggest layouts and designs based on available resources and constraints<\/li>\n\n\n\n<li>Create visual assets like icons or images using text-based prompts<\/li>\n\n\n\n<li>Automatically create mockups to validate concepts or pinpoint errors<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Coding and Development<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">A <a href=\"https:\/\/github.blog\/news-insights\/research\/survey-reveals-ais-impact-on-the-developer-experience\/\" target=\"_blank\">GitHub survey<\/a> found that 70% of developers say that using AI coding tools gives them an advantage. That makes sense from a productivity perspective alone: Generative AI speeds up routine coding tasks, giving developers more time to solve more complex problems.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Machine learning models (MLMs) can learn and adapt to changing needs, suggesting new lines of code or generating boilerplate sections from a short description. Some even have autocomplete features that further speed up workflows.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Testing and Debugging<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Testing and debugging are critical in software development, but they can be time-consuming. Generative AI tools help change that math through automation.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">AI tools can identify system vulnerabilities. They analyze patterns in existing data to identify inefficiencies. They can also predict errors or suggest real-time solutions to prevent them. Some debugging workflows now run with minimal human oversight, though the harder bugs still benefit from a developer\u2019s eye.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Test case generation is another natural fit. AI can create and optimize test cases directly from user stories, saving significant time at a stage when teams often feel pinched.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Deployment and Maintenance<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Shipping software is the high-stakes moment in the lifecycle, and the work doesn\u2019t end at launch. Once a product is live, the team has to keep it running smoothly across whatever conditions the real world throws at it.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">AI helps on both fronts. <a href=\"https:\/\/www.intuit.com\/blog\/innovative-thinking\/what-does-a-software-engineer-do\/\" >Software engineers<\/a> use AI to streamline product deployment by automating routine release tasks and monitoring product performance to detect anomalies. Even within different environments, AI adjusts configurations to prevent failures before users notice them.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The support is continuous rather than one time, which is important because production issues rarely arrive on a schedule.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Benefits of Using AI in Development<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Here\u2019s what the data shows in making the case for artificial intelligence in software development.&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Nearly 60% of executives say AI boosts ROI and efficiency (<\/strong><a href=\"https:\/\/www.pwc.com\/us\/en\/tech-effect\/ai-analytics\/responsible-ai-survey.html\" target=\"_blank\"><strong>PwC<\/strong><\/a><strong>). <\/strong>In software development, AI automates routine, repetitive tasks. In development specifically, that translates to AI handling routine work like code suggestions, autocompletion, and boilerplate generation.<\/li>\n\n\n\n<li><strong>60% of business leaders regularly use AI to support decision-making (<\/strong><a href=\"https:\/\/www.deloitte.com\/us\/en\/insights\/topics\/talent\/human-capital-trends\/2026\/decision-making-with-ai.html\" target=\"_blank\"><strong>Deloitte<\/strong><\/a><strong>). <\/strong>AI can quickly parse through vast datasets to predict potential outcomes and make suggestions. Developers can use those suggestions to make smarter decisions about code, features, and resource allocation.<\/li>\n\n\n\n<li><strong>92% of software developers use AI in code generation, refactoring, and code review (<\/strong><a href=\"https:\/\/getdx.com\/blog\/ai-engineer-vs-software-engineer\/\" target=\"_blank\"><strong>DX<\/strong><\/a><strong>). <\/strong>The productivity gains are well-documented, but the more interesting finding is that AI tools may also help improve overall software quality when used thoughtfully.<\/li>\n\n\n\n<li><strong>96% of business leaders believe Gen AI will improve customer interactions (<\/strong><a href=\"https:\/\/www.liveperson.com\/blog\/explore-digital-transformation-trends\/\" target=\"_blank\"><strong>LivePerson<\/strong><\/a><strong>). <\/strong>In software development, AI can provide personalized recommendations using real-time user data.\u00a0<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">The clearest pattern across the data is that the biggest gains come when AI handles repetitive lifting and developers focus on work that requires creative judgment.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Popular AI Tools Developers Are Using<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Building real <a href=\"https:\/\/www.intuit.com\/blog\/innovative-thinking\/ai-skills-to-boost-your-tech-career\/\" >AI skills<\/a> means getting hands-on with the tools developers actually use. Things change fast, but a handful of platforms have emerged as common starting points.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In software development, some tools focus on early-stage work like ideation and architecture. Others are built around the coding process itself.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If you\u2019re <a href=\"https:\/\/www.intuit.com\/blog\/innovative-thinking\/how-to-learn-artificial-intelligence\/\" >learning AI<\/a>, a few options to explore include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/github.com\/features\/copilot\" target=\"_blank\"><strong>GitHub Copilot<\/strong><\/a><strong>: <\/strong>Offers inline code suggestions and cuts down on the need for boilerplate coding. It\u2019s designed to speed up end-to-end coding processes.<\/li>\n\n\n\n<li><a href=\"https:\/\/cursor.com\/get-started\" target=\"_blank\"><strong>Cursor<\/strong><\/a><strong>: <\/strong>Geared toward newer developers. Its capabilities include automated code generation, debugging, and refactoring.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.qodo.ai\/\" target=\"_blank\"><strong>Qodo<\/strong><\/a><strong>: <\/strong>A leading code review platform designed to identify bugs and system vulnerabilities. It also automates quality checks within different codebases and scales reviews.<\/li>\n\n\n\n<li><a href=\"https:\/\/docs.aws.amazon.com\/codewhisperer\/latest\/userguide\/whisper-legacy.html\" target=\"_blank\"><strong>Amazon CodeWhisperer<\/strong><\/a><strong>: <\/strong>Offers code suggestions within integrated development environments (IDEs). It\u2019s optimized for cloud-based development and has built-in security support.<\/li>\n\n\n\n<li><a href=\"https:\/\/code.claude.com\/docs\/en\/overview\" target=\"_blank\"><strong>Claude Code<\/strong><\/a><strong>: <\/strong>An agentic AI tool that supports the full development workflow. It can read your codebase, run commands, edit files, and execute tests.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Each tool has its sweet spot, and there\u2019s a lot of overlap across the category. Some tools require more human oversight than others, and the right choice usually depends on the specific work being done. In practice, most developers end up using more than one, especially when domain-specific tasks or particular IDEs come into play.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong><em>Dig deeper:<\/em><\/strong><em> Wondering if you can integrate AI development tools with software development platforms? The short answer is yes, but it depends on the systems in place. Intuit&#8217;s engineers have built internal tools like Query Kickstart, a generative AI\u2013powered tool that accelerates SQL query authoring for data workers. It&#8217;s a concrete example of AI integrated directly into the development workflow. Learn more about<\/em><a href=\"https:\/\/www.intuit.com\/technology\/\" target=\"_blank\"><em> <\/em><em>how our tech stack empowers engineers<\/em><\/a><em>.&nbsp;<\/em><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Challenges and Risks to Watch For<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">AI systems are prone to issues like security vulnerabilities and bias. Some of the biggest challenges of using AI in software development include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Security risks: <\/strong><a href=\"https:\/\/www.businesswire.com\/news\/home\/20250730694951\/en\/AI-Generated-Code-Poses-Major-Security-Risks-in-Nearly-Half-of-All-Development-Tasks-Veracode-Research-Reveals\" target=\"_blank\">Veracode<\/a> found that large language models introduced vulnerabilities classified within the Open Web Application Security Project (OWASP) Top 10 in 45% of test cases. Treat AI-generated code like any other untrusted contribution. Review it, test it, scan it, and keep sensitive data out of prompts.<\/li>\n\n\n\n<li><strong>Overreliance: <\/strong>AI can help developers move faster, but leaning on it too heavily can weaken learning and make errors harder to spot. In an <a href=\"https:\/\/www.anthropic.com\/research\/AI-assistance-coding-skills\" target=\"_blank\">Anthropic study<\/a>, software engineers who used an AI coding assistant scored 50% on a follow-up skills quiz, compared with 67% for those who coded by hand.<\/li>\n\n\n\n<li><strong>Accuracy:<\/strong> AI-generated code can look polished while still being wrong or poorly suited to the product context. Developers need to verify outputs for quality and accuracy. Stack Overflow\u2019s Developer Survey found that 46% of developers distrust the accuracy of AI tool outputs, compared with 33% who trust them.<\/li>\n\n\n\n<li><strong>Consistency and transparency: <\/strong>Outputs can sometimes change across <a href=\"https:\/\/www.intuit.com\/blog\/innovative-thinking\/how-to-train-ai-model\/\" >AI models<\/a> and prompts, even when given the same prompt. <a href=\"https:\/\/arxiv.org\/abs\/2408.04667\" target=\"_blank\">One study<\/a> found accuracy swings of up to 15 percentage points across runs, even when LLMs were configured for deterministic behavior. That\u2019s why human oversight remains critical.\u00a0<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>AI Is Changing How Software Gets Built<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Figuring out where to start with AI in software development can feel like a lot, but it doesn\u2019t have to be overwhelming. Start small and build your knowledge over time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Choose 1 or 2 tools and use them for a specific task. That might be generating or debugging code or writing documentation. Take your time and learn the tools&#8217; strengths and weaknesses before adding more to the mix. Keep going until you\u2019re confident using AI to support your workflow.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Through all of it, keep the bigger picture in view. AI isn\u2019t a replacement for the developer doing the work. Its job is to handle the repetitive lift so the creative and architectural work can be, well, creative and architectural.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Above all, keep building upon your skills. Continuous upskilling is what keeps developers ahead of that curve. And working in environments where AI is part of everyday development tends to accelerate the learning.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Ready for the next step? Explore <a href=\"https:\/\/www.intuit.com\/careers\/teams\/software-engineering\/\" target=\"_blank\">Intuit\u2019s software engineering jobs<\/a> for an idea of what\u2019s out there.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>FAQs<\/strong><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Are there security risks associated with using AI for coding? <\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">A Veracode study found that 45% of AI-generated code introduced vulnerabilities in the OWASP Top 10. That\u2019s why an overreliance on AI can be problematic, and why human oversight is vital. Development teams should have proper controls, encryption, and internal usage policies.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>What type of software development projects benefit the most from using AI? <\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Software developers can use AI tools for virtually any project, but a few categories tend to see the biggest gains:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Projects with repetitive coding work. Boilerplate generation, scaffolding, and routine refactoring are where AI tools save the most time, especially on large codebases.<\/li>\n\n\n\n<li>Test-heavy projects. AI can generate test cases from user stories, suggest edge cases, and flag likely bugs before code ships.<\/li>\n\n\n\n<li>Enterprise applications with complex workflows. End-to-end AI development platforms support large-scale projects where consistency, compliance, and cross-system integration matter.<\/li>\n\n\n\n<li>Legacy code maintenance. AI can summarize unfamiliar code, explain dependencies, and help developers safely modernize older systems.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>How can development teams measure the success of using AI as part of their workflows?<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Successful AI adoption shows up in concrete metrics. Some useful indicators for development teams include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Cycle time.<\/strong> How long does it take to go from a feature request to production? AI tools that help should compress this number over time.<\/li>\n\n\n\n<li><strong>Code review velocity.<\/strong> AI-assisted code review and generation should let teams ship more pull requests per sprint without sacrificing quality.<\/li>\n\n\n\n<li><strong>Defect rate.<\/strong> Tracking bugs in AI-assisted code versus non-AI-assisted code reveals whether the tools are improving quality or just changing where errors appear.<\/li>\n\n\n\n<li><strong>Developer satisfaction.<\/strong> Quarterly surveys that ask developers whether AI tools make their work easier.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI has crossed the line from experimental to expected in software development. In Stack Overflow\u2019s Developer Survey, 84% of respondents said they use or plan to use AI tools in their development process, up from 76% in 2024. Among professional developers, 51% use AI tools daily. Generative AI and large language models (LLMs) now show<\/p>\n","protected":false},"author":151418452,"featured_media":16023,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_yoast_wpseo_focuskw":"","_yoast_wpseo_title":"How to Use AI in Software Development | Intuit Blog","_yoast_wpseo_metadesc":"Discover how developers use AI for code generation, debugging, testing, and code review. 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