Are the days of manual coding entirely behind us? Some IT professionals think so. Our latest survey of 319 IT professionals in the U.S. shows that 72% of IT workers use AI-generated code in their development processes. From automatically detecting bugs to generating original code snippets, there is almost nothing artificial intelligence (AI) can't do in software development.
Experienced technology professionals know that AI can handle mundane or repetitive coding tasks—but our latest research shows that the impact extends to even more intricate processes such as code creation, optimization, and testing. This game-changer promises faster development cycles and more robust, reliable software.
We surveyed IT professionals to discover how AI has revolutionized the IT sector, particularly in development and the use of AI in coding. According to our respondents, generative AI usage in coding is on the rise—and that train won’t be stopping anytime soon.
- 72% of IT workers are using AI-generated code in their roles.
- More than 30% of IT workers state that code generation is AI’s most valuable feature.
- Despite concerns about accuracy, outlook remains positive. Over one-third of respondents rate generative AI’s code as “highly accurate.”
- More than 50% of IT workers think the future of coding includes AI.
According to our respondents, generative AI code is widely adopted among the 3,000,000 IT professionals in the United States. A significant portion (34.8%) of the professionals surveyed reported using AI-generated code extensively in their development processes. An additional 21.94% use it occasionally, and another 15.05% sparingly. Combined, that’s a significant 72% of IT workers using AI in their roles.
Plus, even some of those not currently using AI (10.66%) said they planned to adopt it. Potential barriers to team-wide AI adoption include not being willing or able to invest financially in the technology, teams not being ready for AI use, and organizations not seeing the value of generative AI. One possible solution to increase powerful generative AI tool adoption rates is lowering the threshold to access the technology in the future.
This burgeoning technology has rapidly become one of the most exciting and transformative in our lifetimes. In fact, 72% of developers already use AI to write code.
While AI has been a hotly debated topic over the past few years, this data speaks to a substantial growth trend in AI adoption in IT and the technology sector at large. Despite concerns over AI ethics, contradictions in the use of GenAI, and other commonly cited issues with the technology, the data is clear: Tech workers use, or plan to begin using, AI for complex projects like coding and development in large percentages.
This poses both a question and a challenge for the innovative technology team. Are you using AI? If not, you may fall behind in the industry, especially if your competitors already use it. If you use AI code generation already, great! But can you do more with the tool?
The sky's the limit when it comes to the frontier of generative AI for coding in tech. We have yet to see all this innovation can do for us.
What projects are those 72% of IT workers using AI for? It may come as a surprise, but our data shows that AI is most often used to create and test new code—not just edit existing code. Some of the top uses cited by tech workers are code generation (37.62%), bug detection (35.42%), and automated testing (34.48%).
Some common uses of generative AI in development include:
- Code creation and synthesis: A good code AI tool can generate entire code blocks or functions based on clear directions and documentation.
- Auto-complete: Within an app or tool, AI can suggest the next part of your code as you type, similar to predictive text in Gmail or text messaging.
- Template generation: Many devs use code AI to create boilerplate code or snippets for common patterns, such as CRUD operations or API endpoints.
- Error detection and correction: A specialized tool for AI code can automatically identify errors in your existing code and suggest fixes.
- Performance optimization: AI can analyze code to recommend speed, memory usage, or other performance metrics optimizations.
- Assist with modernization initiatives: Modernization can be a huge time sink for businesses still using legacy applications. According to a 2024 Gartner report, AI can help explain those applications and create replacements, reducing costs by up to 70%.
While many of the listed suggestions relate to QA and testing, it’s important to understand that the use of AI goes far beyond QA. While 31.35% of IT professionals use AI for code editing and review and 33.86% use it for performance optimization, most IT professionals use AI to create code.
This shift toward AI code creation is fascinating. It indicates that even in IT, where the end user is likely relatively skilled in technology use and has at least basic development skills—they still prefer to use AI to create and improve code. This speaks volumes about how AI can help your team maximize efficiency in all types of development.
If you haven’t explored the use of AI for code generation, you’re missing out on significant opportunities to increase your team’s efficiency on current tasks and solve new problems more quickly. According to Harvard Business School, generative AI can actually improve productivity by up to 40% when used within its capabilities by a highly skilled worker. You can’t say no to that kind of advantage, especially in a highly competitive and fast-moving industry like IT.
One of the most common arguments about AI is whether the output generated is accurate. According to our research, more than a third of IT workers report AI-generated code to have high levels of accuracy—a finding that may surprise skeptics. With 33.86% of IT workers rating AI-generated code as highly accurate and 21.63% as mostly accurate, there's a clear indication of trust in AI's current capabilities.
That said, accuracy was also the biggest challenge in implementing AI code. 46.08% of respondents cite accuracy as the main challenge—though only 10.34% find the code inconsistent, and an extraordinarily minimal 0.63% find it inaccurate. Of course, there’s room for improvement, but these are positive results overall.
This data should be heartening for anyone still deciding whether to implement AI or GenAI in development projects. AI-generated code is shown to have a high level of accuracy—even for an audience that’s very concerned about that aspect. In 2025, AI can (and should) be a reliable tool in the developer's toolbox.
Small repetitive tasks are a great place to start if you’re unsure where or when to add AI to your processes. Identify tasks where AI can add value, such as auto-completion or debugging. Once you’re confident using coding AI, you can bring this new tool to every project and process you encounter.
Finally, we asked the million-dollar question: Will AI replace the need for traditional coding skills in the future? We found that expert opinions remain mixed. Most developers (46%) envision a future where AI complements their skills, but human judgment remains vital.
However, some IT professionals are even more optimistic, with 12.85% viewing AI as the future of coding. In a world where AI-driven solutions already dramatically enhance productivity and efficiency and reduce the likelihood of human error, this may not be an entirely unreasonable view. The future of artificial intelligence is very, very bright.
Generative AI coding tools are designed to empower developers, not replace them. AI’s role in the technology landscape of the coming years will probably not overtake the developer but rather work alongside the experienced developer. A developer’s role may change to account for AI’s ability to take over repetitive tasks.
Still, no responsible development in AI will truly overtake the human capability for creation and advanced problem-solving. A machine’s AI code generation can complete specific tasks for us, but a human will always need to train the machine and guide the project's strategic vision.
The throughline is clear throughout our collected data: AI is here to stay, especially in the technology sector. In fact, the question is less about if IT professionals are using AI and more about how much they’re using it. The use of generative AI, especially in development and coding, is so widespread in 2025 that it’s not to be questioned. Most IT professionals are already using it.
Going forward, this means we can expect to see the use of AI for code generation become even more prevalent. As the remaining issues with using AI for debugging, integration, and security are addressed—especially partnered with advancements in accuracy—the use of generative AI for coding will continue to grow to widescale adoption.
What does that mean for your team? The truth is that even if you’re on the fence about using generative AI for coding, if you aren’t adopting the technology, your team is likely to get left behind. In fact, individual team members are probably already using AI in their day-to-day work with or without company policies on the technology. AI code generation, bug detection, and automated testing are key areas where AI adds value, streamlining essential tasks—and if you’re still doing them manually, that’s putting you behind your competitors.
If you’re ready to invest in a cutting-edge generative AI solution for your team, look no further than Now Assist. Our out-of-the-box GenAI experience is designed to make your team more effective and efficient using the power of artificial intelligence.
