It’s no secret that the marketplace for AI instruments and companies is quickly rising. In response to Statista, for instance, the worth of the AI market in 2025 guarantees to succeed in a staggering $243.7 billion and develop at a price of 27.67% per yr, reaching $826.7 billion by 2030.
This astonishing enlargement has been made potential largely by varied AI purposes, comparable to in advertising and marketing & gross sales, customer support, automotive, and, in fact, software program improvement.
Recognizing the potential of synthetic intelligence for creating software program options, many tech firms from startups to giants like Microsoft, IBM, and Google have invested closely in AI assistants and AI-related analysis and improvement.
However is AI at all times good in software program improvement and what must you take note of when selecting a contractor that makes use of synthetic intelligence in improvement processes?
Why Purchasers Ought to Care About AI Integration in 2025
These days, AI integration has develop into a form of indicator of the speed of a tech firm and the way a lot it retains up with the instances. It’s believed that suppliers utilizing AI coding assistants like GitHub Copilot and Cursor IDE can visibly speed up coding, scale back prices, and enhance software program high quality.
Much more spectacular is the rise of AI fashions like Claude Sonnet 3.7, which now leads the sector with each its common and considering variations. These superior fashions assist builders generate, refine, and troubleshoot code extra successfully than ever earlier than.
Two years in the past, Statista calculated that software program builders utilizing an AI assistant completed their work nearly twice as quick as these working with out one. Which means one developer with AI programs might get as a lot accomplished as two human builders with out it.
Distinction in software program improvement duties with and with out AI capabilities, Statista
Nonetheless, though there are numerous advantages of implementing AI assistants into software program improvement workflows, there are additionally some knowledge safety considerations for software program firms.
As a result of many AI fashions be taught from public code repositories like GitHub, they’ll generate code that by accident violates open-source licenses. For instance, instruments like Copilot don’t present credit score to the unique authors, which is usually required.
Even worse, AI can typically copy current code word-for-word, which means software program improvement groups would possibly unknowingly use copyrighted code, placing their firm in authorized issues.
Past legal responsibility considerations, AI-generated code can introduce safety dangers. AI builders could unintentionally leak proprietary algorithms or confidential knowledge, which might break an organization’s aggressive edge.
Extra dangerous, AI-generated code would possibly expose delicate data like hardcoded credentials, database connections, or private buyer knowledge, placing each the enterprise and its customers in danger.
In 2023, for instance, Samsung Electronics banned its staff from utilizing ChatGPT and different AI-powered chatbots, changing into considered one of a number of firms to tighten measures on using generative AI for software program improvement.
The actions had been taken after the unintended leak of confidential inside supply code was found by an engineer who uploaded it to ChatGPT.
The Position of AI Inside Growth Cycles
AI instruments have develop into an everyday a part of each day work for a lot of IT professionals. Greater than 50% of all machine studying engineers use AI on daily basis, and almost as many knowledge scientists depend on it simply as usually.
Again-end and full-stack builders additionally make good use of AI in software program improvement, although a bit much less steadily, with about one in three utilizing these instruments each day. However what precisely can AI do?
Code Writing
As we already talked about, AI coding assistants like GitHub Copilot, Cursor IDE with the assistance of Claude Sonnet 3.7 and different LLM’s have considerably improved coding pace and accuracy. They don’t simply counsel snippets—they generate whole features, refactor code, and even translate it between programming languages.
Fashionable IDEs like VSCode IDE now combine AI-powered improvement modes that proactively edit information, repair errors, and generate new code.
- In GitHub Copilot, this is named Copilot Edit.
- In Cursor, an analogous function is known as Composer.
These AI-driven modes permit for hands-free code enhancements, the place the assistant not solely suggests however actively modifies the codebase in real-time.
Most used synthetic intelligence instruments amongst builders as of 2024, Statista
Code Testing: Guide and Automated
Past dashing up improvement, AI applied sciences are additionally enjoying a major position within the testing part.
As an example, as a substitute of getting a human tester click on by each button, kind, and menu, AI-powered instruments can simulate person actions to immediately spot any gaps, making testing far more thorough.
AI can even create check instances by itself by inspecting the code and foretelling the place issues would possibly pop up.
That is particularly helpful for checking if particular person features work accurately and demonstrating totally different elements of the applying operate collectively as demanded.
With instruments like Selenium and Cypress that leverage AI, builders can even check web sites by simulating how customers work together with them in a browser. Another AI-powered frameworks may even create check instances by themselves, saving builders time.
Code Safety and Management
One of many foremost considerations in software program improvement is defending code from safety dangers, comparable to unauthorized entry or knowledge leaks. AI options, in flip, can autonomously scan the code for any potential safety flaws and even counsel fixes earlier than they develop into disastrous.
How SCAND Makes use of AI in Software program Growth: With Your Full Consent
At SCAND, we’ve absolutely embraced AI assistants to make software program improvement sooner, smarter, and extra protected.
We, like lots of our colleagues, use AI coding instruments like GitHub Copilot to hurry up improvement, serving to our software program engineers write code a number of instances sooner.
However we don’t simply blindly depend on AI-generated code—our builders rigorously study and refine all the pieces to ensure high-quality software program purposes. The consequence? Quicker supply instances with out sacrificing reliability.
However AI doesn’t simply assist us write code—it additionally makes testing extra affordable. We use AI-powered instruments for each guide and automatic testing to catch points earlier than they attain manufacturing.
AI can even generate automated check instances straight from the code, ensuring nothing slips by the cracks. This implies fewer bugs, higher efficiency, and a trouble-free app interplay for finish customers.
However an important level in our use of synthetic intelligence is that we embed AI into software program improvement solely when shoppers explicitly comply with it, which implies no surprises and no hidden knowledge sharing.
For individuals who query knowledge safety when integrating AI, we are able to regionally run AI fashions like LLama (3B/8B parameters), StarCoder and DeepSeek-R1. This fashion, shoppers get all the advantages of AI whereas preserving their code utterly non-public.
It’s no secret that the marketplace for AI instruments and companies is quickly rising. In response to Statista, for instance, the worth of the AI market in 2025 guarantees to succeed in a staggering $243.7 billion and develop at a price of 27.67% per yr, reaching $826.7 billion by 2030.
This astonishing enlargement has been made potential largely by varied AI purposes, comparable to in advertising and marketing & gross sales, customer support, automotive, and, in fact, software program improvement.
Recognizing the potential of synthetic intelligence for creating software program options, many tech firms from startups to giants like Microsoft, IBM, and Google have invested closely in AI assistants and AI-related analysis and improvement.
However is AI at all times good in software program improvement and what must you take note of when selecting a contractor that makes use of synthetic intelligence in improvement processes?
Why Purchasers Ought to Care About AI Integration in 2025
These days, AI integration has develop into a form of indicator of the speed of a tech firm and the way a lot it retains up with the instances. It’s believed that suppliers utilizing AI coding assistants like GitHub Copilot and Cursor IDE can visibly speed up coding, scale back prices, and enhance software program high quality.
Much more spectacular is the rise of AI fashions like Claude Sonnet 3.7, which now leads the sector with each its common and considering variations. These superior fashions assist builders generate, refine, and troubleshoot code extra successfully than ever earlier than.
Two years in the past, Statista calculated that software program builders utilizing an AI assistant completed their work nearly twice as quick as these working with out one. Which means one developer with AI programs might get as a lot accomplished as two human builders with out it.
Distinction in software program improvement duties with and with out AI capabilities, Statista
Nonetheless, though there are numerous advantages of implementing AI assistants into software program improvement workflows, there are additionally some knowledge safety considerations for software program firms.
As a result of many AI fashions be taught from public code repositories like GitHub, they’ll generate code that by accident violates open-source licenses. For instance, instruments like Copilot don’t present credit score to the unique authors, which is usually required.
Even worse, AI can typically copy current code word-for-word, which means software program improvement groups would possibly unknowingly use copyrighted code, placing their firm in authorized issues.
Past legal responsibility considerations, AI-generated code can introduce safety dangers. AI builders could unintentionally leak proprietary algorithms or confidential knowledge, which might break an organization’s aggressive edge.
Extra dangerous, AI-generated code would possibly expose delicate data like hardcoded credentials, database connections, or private buyer knowledge, placing each the enterprise and its customers in danger.
In 2023, for instance, Samsung Electronics banned its staff from utilizing ChatGPT and different AI-powered chatbots, changing into considered one of a number of firms to tighten measures on using generative AI for software program improvement.
The actions had been taken after the unintended leak of confidential inside supply code was found by an engineer who uploaded it to ChatGPT.
The Position of AI Inside Growth Cycles
AI instruments have develop into an everyday a part of each day work for a lot of IT professionals. Greater than 50% of all machine studying engineers use AI on daily basis, and almost as many knowledge scientists depend on it simply as usually.
Again-end and full-stack builders additionally make good use of AI in software program improvement, although a bit much less steadily, with about one in three utilizing these instruments each day. However what precisely can AI do?
Code Writing
As we already talked about, AI coding assistants like GitHub Copilot, Cursor IDE with the assistance of Claude Sonnet 3.7 and different LLM’s have considerably improved coding pace and accuracy. They don’t simply counsel snippets—they generate whole features, refactor code, and even translate it between programming languages.
Fashionable IDEs like VSCode IDE now combine AI-powered improvement modes that proactively edit information, repair errors, and generate new code.
- In GitHub Copilot, this is named Copilot Edit.
- In Cursor, an analogous function is known as Composer.
These AI-driven modes permit for hands-free code enhancements, the place the assistant not solely suggests however actively modifies the codebase in real-time.
Most used synthetic intelligence instruments amongst builders as of 2024, Statista
Code Testing: Guide and Automated
Past dashing up improvement, AI applied sciences are additionally enjoying a major position within the testing part.
As an example, as a substitute of getting a human tester click on by each button, kind, and menu, AI-powered instruments can simulate person actions to immediately spot any gaps, making testing far more thorough.
AI can even create check instances by itself by inspecting the code and foretelling the place issues would possibly pop up.
That is particularly helpful for checking if particular person features work accurately and demonstrating totally different elements of the applying operate collectively as demanded.
With instruments like Selenium and Cypress that leverage AI, builders can even check web sites by simulating how customers work together with them in a browser. Another AI-powered frameworks may even create check instances by themselves, saving builders time.
Code Safety and Management
One of many foremost considerations in software program improvement is defending code from safety dangers, comparable to unauthorized entry or knowledge leaks. AI options, in flip, can autonomously scan the code for any potential safety flaws and even counsel fixes earlier than they develop into disastrous.
How SCAND Makes use of AI in Software program Growth: With Your Full Consent
At SCAND, we’ve absolutely embraced AI assistants to make software program improvement sooner, smarter, and extra protected.
We, like lots of our colleagues, use AI coding instruments like GitHub Copilot to hurry up improvement, serving to our software program engineers write code a number of instances sooner.
However we don’t simply blindly depend on AI-generated code—our builders rigorously study and refine all the pieces to ensure high-quality software program purposes. The consequence? Quicker supply instances with out sacrificing reliability.
However AI doesn’t simply assist us write code—it additionally makes testing extra affordable. We use AI-powered instruments for each guide and automatic testing to catch points earlier than they attain manufacturing.
AI can even generate automated check instances straight from the code, ensuring nothing slips by the cracks. This implies fewer bugs, higher efficiency, and a trouble-free app interplay for finish customers.
However an important level in our use of synthetic intelligence is that we embed AI into software program improvement solely when shoppers explicitly comply with it, which implies no surprises and no hidden knowledge sharing.
For individuals who query knowledge safety when integrating AI, we are able to regionally run AI fashions like LLama (3B/8B parameters), StarCoder and DeepSeek-R1. This fashion, shoppers get all the advantages of AI whereas preserving their code utterly non-public.
