How AI Has Changed Software Development Outsourcing

Since the expansion of the software industry in the 1970s and ’80s, businesses around the world have outsourced software development tasks to cut costs or to access specialized expertise they don’t have internally. Particularly for development agencies, a significant motivation for outsourcing has been to allow external partners to handle repetitive tasks that consume excessive time and resources.

Yet, the explosive growth of AI in recent years has enabled automation for many of these tasks, changing the landscape of software development outsourcing. 

“AI shifts the focus from outsourcing volume work to collaborative innovation,” says Clutch’s VP of Development, Sergei Dubograev. “Tasks like bug testing may now be automated, but outsourcing will pivot toward high-impact areas such as product strategy or specialized engineering.” 

While some in the development industry worry that their jobs may become obsolete in the wake of AI, Dubograev argues that AI will simply cause a shift in the types of tasks being outsourced and the expertise required to complete these tasks. “This shift underscores that AI won’t replace jobs—it changes the why, not the who, behind outsourcing,” says Dubograev.

With this in mind, businesses are looking to hand over more complex tasks that require creativity, problem-solving, and domain expertise to third-party vendors, rather than repetitive processes like ticketing systems or basic coding. 

How AI Has Changed Which Tasks Are Outsourced

As generative AI boomed in 2023, many businesses jumped at the opportunity to use AI to improve their products, processes, and operations. Afterall, AI is particularly effective for streamlining workflows and minimizing repetitive tasks. By investing in AI tools and platforms rather than outsourcing, businesses were able to reduce costs, enhance existing systems, and simplify processes. 

“The value of AI lies not in replacing what companies do but in making things faster, simpler, and more efficient, ultimately supporting better decision-making and customer experiences,” says Dubograev. 

Rather than outsourcing, many companies have been using AI to support:  

• Code Generation 
• Testing & Debugging 
• Quality Assurance
• Documentation
• Security, Threat Detection, and Compliance

Code Generation

Previously, organizations would outsource code generation to freelancers or third-party developers. Today, even ChatGPT can assist in code generation, albeit with limited capabilities — that's how common these tools are.

At the enterprise level, the IBM wastsonx Code Assistant makes writing code without prior experience simple. All you have to do is provide plain-language commands, and AI will translate them into code.

Another such tool is the Github Copilot. It has been trained in multiple languages, such as Ruby, Swift, PHP, Perl, and JavaScript. It not only suggests code but also looks for vulnerabilities. Plus, you can use it as an extension in your integrated development environments (IDEs), such as Visual Studio or Neovim.

For teams with some coding experience, TabNine is a good option. It can learn from the existing codebase and complete the code in real time. Like the Github Copilot, it also integrates into IDEs and supports popular languages.

Testing and Debugging

AI tools can also manage testing and debugging. These tools look at the surrounding code and make suggestions. They can also spot programming errors, bugs, and other issues you may have missed. Some of these tools are advanced enough to find bugs across devices and use cases.

For example, Usetrace is an automated testing tool that debugs web applications. Its AI creates automated tests mimicking user interactions. It can then run these tests on multiple browsers and devices. The tool then reports any issues it finds, such as broken links or incorrect form input handling.

AI testing and debugging tools also integrate with continuous integration and delivery pipelines to help developers detect code-related issues early in the development process, saving time and effort to resolve them later.

Quality Assurance

There's no need to get an external team on board to check your code's quality. AI tools can handle this aspect of development too. They scan the code and assess its quality based on various metrics.

Even better, they provide suggestions on improving the code's quality, such as following coding best practices or optimizing performance, which makes them especially helpful for junior developers who are still learning these skills.

For example, Testim is an AI tool that creates automated tests for code quality assurance. It provides versatile environments for testing, and its machine-learning capabilities allow it to adapt to changes in the codebase without requiring manual updates. You can execute quality assurance tests on physical and virtual devices to ensure that your code works on a wide range of platforms and devices.

Documentation

There's no shortage of AI writing tools these days. While many of them are for generic purposes, some enterprise-grade options can help with technical writing. Document360's Eddy AI assists you in writing tech documents, such as articles, FAQs, or API references.

Unlike generic tools that use their datasets to produce content, this tool lets you upload your company's knowledge base and uses that information to generate relevant and accurate content. The resulting document isn't just random text — it's based on the content you already have, making it more reliable. Many other AI tools, such as Jasper AI, also have this functionality. 

Deployment

AI tools also automate the deployment process, saving companies the money they had to spend on outsourcing partners. They can analyze your code and automatically optimize it for different environments, reducing the likelihood of errors during deployment. Some of them also provide real-time feedback on your application's performance and alert you in case of a bottleneck or abnormality.

Security, Compliance, and Threat Detection

Other aspects of human development that AI tools now take care of are security, compliance, and threat detection. Here's what they can do:

• Scan codes to identify threats like vulnerabilities or malicious code
• Monitor databases and logs in real time to detect suspicious or anomalous activity
• Ensure compliance with industry and governmental regulations by continuously scanning the codebase for violations

Since AI systems are operational 24/7 and do not suffer from fatigue, they can analyze large amounts of data much faster than humans and alert the concerned team immediately. Such quick detection and response can minimize the impact of security breaches or noncompliance. 

What AI Cannot Replace in the Development Process

As helpful as AI is in several areas of development, it cannot entirely replace human input. Human creativity and input will always be important in the outsourcing world.

“AI struggles with tasks requiring creativity, empathy, and abstract thinking. For example, chatbots can handle FAQs, but complex B2B sales still require the emotional intelligence of experienced sales consultants,” says  Dubograev. “Similarly, tasks like leadership coaching or custom UX design involve human judgment that AI can't replicate. AI excels in tasks; humans master nuance.”

A more likely outcome will be that AI and humans will work together to achieve more than they could separately. A Harvard Business Review article calls this ''collaborative intelligence.'' It further emphasizes that even though AI might change how we work, its main impact ''will be in complementing and augmenting human capabilities, not replacing them.''

A Maryville University publication identifies the key cognitive abilities that humans possess and AI lacks:

• Reasoning: AI is a mere imitation of human intelligence. It can only analyze data based on the input you have given it and follow preprogrammed rules. Humans have reasoning skills that allow them to make logical decisions even in unfamiliar situations.
• Perception: At times, data alone isn't enough. You also need to perceive your surroundings. For example, in a marketing agency, marketers rely on more than just data. They also notice seasonal trends to determine the trajectory of their campaigns.
• Creativity: There's no bounds to the human imagination. While AI can generate ideas based on data, it cannot think outside the box or develop revolutionary concepts that haven't been programmed into it. Humans, on the contrary, can do this perfectly well.
• Emotional Intelligence: Businesses are made up of humans and are therefore not emotionless. AI cannot understand and respond to emotions, making it challenging to replace human interactions.

AI can supplement human efforts instead of replacing them. We will always need human oversight to guide AI and perform the tasks that it cannot.

However, just any human oversight won't do. With AI changing everything, humans will have to keep up. For many, this means many people will need to invest in reskilling. 

According to the World Economic Forum, 23% of jobs will evolve in the next five years due to AI and other technologies like voice recognition. In the wake of this change, executives believe that 40% of the workforce will have to reskill themselves to keep up with AI and automation.

Humans must learn to work alongside AI, embracing its abilities and using them to their fullest potential. This can help them resist the wave of unemployment that experts predict AI will cause and, instead, thrive in the new age of technology.

What AI's Shortcomings Mean for Outsourcing Development

The fact that AI isn't a total replacement for humans has significant implications for outsourcing development. Companies that outsource their work to AI-driven systems must understand the limitations of these systems and how they can affect their projects' success.

For example, if a company plans to use AI for customer service interactions, it must be prepared to handle situations that require empathy or emotional understanding.

AI tools may be able to provide answers to customers using their knowledge base. But what if a customer is angry or frustrated? AI may be unable to handle the situation effectively, leading to dissatisfied customers.

A human operator with empathy and emotional intelligence can take over and resolve the issue more successfully. Similarly, if a customer has a unique problem that the AI hasn't encountered before, it may not have the ability to think creatively and come up with a solution. Again, human intervention would be required.

Here are some other ways AI outsourcing can impact the development landscape.

Higher Labor Costs

In the next two decades, automation technologies will likely eliminate 14% of all jobs worldwide and transform around 32% of the existing ones. Interestingly, these predictions were even before ChatGPT made an appearance. The emergence of new AI-driven solutions has spiked the percentage of job elimination and transformation.

In the wake of this, people will upskill themselves to remain relevant and then they will command higher salaries. As AI becomes an integral part of the development machinery, companies must hire employees with more experience and modern skills to handle the technology.

Businesses must also offer attractive incentives to keep top-performing employees from leaving to better-paid organizations. They'll have to invest in ongoing training to keep their employees up to date with whatever new advancements come in the AI space. As a result, the labor costs will soar.

Faster Development Timelines

With automation, development times will be significantly shortened. The same number of developers will be able to develop more apps and software in less time than it would have taken them without AI.

Also, as existing AI tools become more sophisticated, they'll take up even more tasks from the development process, making the timeline even shorter. Companies can produce more software in less time, increasing productivity and profits.

Better Communications

AI-powered collaborative and communication tools will further enhance the productivity of remote teams. For example, real-time translators can help people from around the world communicate seamlessly, and AI-driven chatbots can handle customer queries and complaints quickly.

With better communication tools, companies can bridge geographical barriers and have a global pool of employees working together effectively. It is well known that diversity makes a company more profitable and productive.

A McKinsey report found that companies with higher racial and ethnic diversity are 35% more likely to have higher-than-average financial returns. Similarly, those higher in the gender diversity spectrum are 15% more likely to have better financial returns than their industries.

AI tools will help make communication a breeze for teams who may not even be working in the same time zones. For example, U.S. companies working with developers in India or China can use these collaborative tools to stay in the loop and work together efficiently.

While AI Can Streamline Processes, Outsourcing is Still Necessary

AI will change how business operations take place globally. From changing the tasks to be outsourced to bringing remote teams closer, AI can significantly positively impact the workplace.

However, that's not to say humans can call it quits. Without human assistance, AI is simply a collection of computer programs. It's the human touch that will continue to make businesses thrive and evolve, so businesses should not let go of their highly skilled professionals.

As we advance, organizations will have to spend more to hire and retain employees who can efficiently form a human-AI hybrid for a futuristic workplace.