-- Recent layoffs across leading technology companies, including Amazon, SAP, Salesforce, Shopify, and Klarna, highlight a broader industry transition. Beyond cost-cutting, artificial intelligence is fundamentally changing how software is created and maintained.
The numbers suggest the transition is already underway. A recent KPMG survey found that 67% of businesses actively encourage employees to use AI tools to increase output, with IT departments leading the charge across everything from code generation to automated testing.
The central question remains not whether AI can write code, but where it provides benefits and where it creates risks.
AI Excels in Routine Development Work
AI demonstrates the greatest impact in tasks that consume significant developer time. Code generation tools can reduce time spent on repetitive tasks by 30 to 50 percent, lowering reliance on mid-level engineers for routine tasks.
Testing and quality assurance see similar benefits. AI-powered tools can shorten testing cycles by 20 to 40 percent, automatically generating tests and spotting patterns in bug reports that humans might overlook. Documentation – often the most time intensive parts of any developer's job – requires significantly less manual work with AI assistance.
One of the most significant impacts is seen in prototypes and proof-of-concept projects. AI makes building a basic version of an app or demo for clients two to three times faster than traditional methods. For startups that need to validate ideas quickly, this speed makes a difference. Processes that once required weeks can now be completed in days.
But the scale of these gains varies by project type. Short MVP builds lasting a few months can see timeline reductions of 40 to 50 percent, primarily because much work involves repetitive setup tasks that AI handles effectively. Larger corporate applications might achieve 20 to 30 percent savings, while enterprise-level projects – the massive, complex systems that power big organizations – often see more modest gains of 10 to 20 percent as architectural complexity begins to outweigh automation benefits. Still, this translates to significant value given the scale of these projects.
Human Expertise Remains Critical for Complex Challenges
AI is less effective when projects require strategic judgment and complex problem-solving. System architecture – deciding how all the pieces fit together – remains firmly in human territory. AI can generate code, but it can't determine if that code will be able to scale to millions of users or integrate into existing systems. It does not consider business constraints, performance requirements, or the many trade-offs that make software work in the real world.
"The problem is that the tool has no idea how the system actually works," explains Dmitry Nazarevich, Chief Technical Officer at Innowise. "It doesn't know the dependencies, operational bottlenecks, or service level agreements. That entire context cannot be simply put in a prompt. That's the job of the engineering team."
Security and regulatory compliance are additional blind spots. AI produces functional code quickly, but it may often miss critical security considerations and regulatory requirements like GDPR or HIPAA. The same applies to integrating with external systems: AI tends to skip over things like error handling, rate limits, and all the little safeguards that keep software stable in production.
AI-generated code further introduces long-term maintenance issues, as it often lacks the documentation and structure needed for sustainable support. What seems like a quick and easy win in terms of development can turn into a costly burden later.
Companies Adopt Enhancement Strategy Over Replacement
Industry trends indicate that organizations increasingly treat AI as an assistant rather than a full substitute for engineering talent. The most effective model combines AI’s speed on routine tasks with human judgment for areas requiring accountability and strategic decision-making.
This hybrid model is driving demand for IT staff augmentation – teams that pair AI speed with human expertise. Industry experience demonstrates that hybrid strategies consistently reduce development time and costs without compromising stability or scalability.
About Innowise
Innowise supports clients worldwide by offering custom software development and IT staff augmentation services. Innowise operates in over 15 countries across Europe, North America, and the Middle East, collaborating with businesses of all sizes, from startups to large international corporations.
Contact Info:
Name: Egor Grischenko, VP of Sales and Business development (USA & Canada)
Email: Send Email
Organization: Innowise
Address: Rondo Ignacego Daszynskiego, 2B-22P, 00-843 Warsaw
Phone: +48 573 055 311
Website: https://innowise.com/
Release ID: 89169030
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