– Some parts of it are fun and don’t take too long to complete. Others will seem to take forever and exhaust your finances. After all, even the most experienced developer can only type so fast.
Let’s call this the human bottleneck. People have their limits and you can’t expect them to work at the speed of light. Your outsourced team is no exception. Technology, however, can make the process a lot quicker. Leveraging AI in software development is a new trend that many businesses are literally cashing in on.
How? The potential of artificial intelligence to streamline processes is substantial. There are many ways in which it can do this. In the next few paragraphs, we’ll try to cover the most important ones.
The ways to implement AI
How can artificial intelligence fit into your workflow? There are three main types of AI you can use.
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Rule-based systems — the simplest form. They rely on predefined rules programmed into the system. Said system makes decisions based on input data. This is great for sorting and classifying information.
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Expert systems — the more complex version. These systems rely on an inference engine (the rules) and a knowledge base. This is a good choice for tasks that require domain-specific knowledge (i.e. legal advice, medical diagnostics, and similar fields).
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Machine learning — the most advanced option. An ML algorithm can learn from data and make predictions. It performs natural language processing and predictive modeling with a high degree of accuracy.
Despite some concerns, the use of artificial intelligence is on the rise. AI is changing the role of developers. No, not replacing them, just changing their approach to work. After all, software development needs a human brain to give it direction.
The benefits
So what exactly are the benefits of using AI in software development? You’ll save time. You’ll save money. End of story, right? Should you go for it?
Well, hold on a minute. There’s more to it than that! There are a number of other perks to leveraging AI in software development. It’s time to tackle each — one by one.
1. Automating repetitive tasks
We have already mentioned repetitive tasks. Guess what? Automation will take care of those. AI is great with this sort of thing. For example, documenting new versions and features, entering data, or even debugging the code base are all repetitive tasks present in all development projects. Instead of having your developers deal with this manually, it’s possible to employ a rule-based system and make the process automatic.
2. Improving accuracy
Many people believe that automation leaves ample room for error. It doesn’t necessarily have to be so, especially when you consider that human errors also occur. This rings particularly true in the world of outsourced development. Miscommunications, misunderstandings, language, and cultural barriers do play a part.
When implemented correctly, AI can correct both and improve overall accuracy. Designed to mitigate mistakes, it can speed up the development process and boost the quality of your code.
3. Increasing the scale of development
Next comes the question of flexibility. Delivery performance isn’t just about speed. It’s also about the ability to adapt to new circumstances. A sudden influx of new users due to the growing popularity and demand of the app is one such situation.
Is your remote team able to scale it quickly? If not, AI could make a substantial difference and allow you to move swiftly from limited to large-scale operations. You can use artificial intelligence to deal with the unexpected surge while you define a more permanent solution.
4. Making software testing easier
Testing is an unavoidable part of development. Another time-consuming task, that’s for sure. Fortunately, machine learning can fit into the quality assurance process. It enables automated software testing and can reduce the overall failure rate. This, in turn, shortens the development process.
Your remote team can benefit from it throughout the various stages of the software testing life-cycle. ML can improve test definition, implementation, code generation, and code completion. It can also boost execution and exploratory testing, as well as bug management. Last but not least, ML also works for maintenance and grouping, where it heals broken code.
5. Improving error management
Yes, fixing stuff on the go is what AI is great for. Here’s an example. Error management accounts for the largest chunk of downtime in software development. It can get particularly problematic in SaaS and cloud-based platforms which need to be accessible at all times. Of course, detecting, diagnosing, and fixing errors requires time, especially in outsourced development where communication can be slow. Downtime equals financial loss.
Machine learning can proactively flag and fix errors in the system logs without direct human involvement. This can be done in the development and post-development phase.
6. Replacing templates with AI
Finally, we should touch upon an important segment of today’s app development — templates. Serving as ready-made bits of code or predefined structures, they are ‘accelerators’ and can indeed speed up the process. Examples include buttons, scroll bars, layouts, certain functions, and even entire widgets.
However, they are also very much a one-size-fits-all solution and can lead to ‘bloating’ (i.e. having too much code in the app).
Soon, AI could replace them. It’s perfectly possible to prompt artificial intelligence to generate the required amount of code. Just give it clear instructions and style guidelines, and you’re ready to roll. It’s one of the most recent improvements in leveraging AI in software development, and arguably the most impressive.
The future of leveraging AI in software development
This concludes the list of the most important current benefits. They include saving time and money by reducing intensive human labor, as well as automation and improved accuracy. Leveraging AI in software development also facilitates scaling, testing, and error management, and can potentially replace templates.
So what comes next? How will the coders and testers benefit from it in the future? Incoming trends in software outsourcing aren’t easy to predict. One thing is certain — AI will remain in the spotlight. Doing online business without it will become unimaginable. If any part of your enterprise depends on software, adopting such new technologies is the best way to stay competitive and succeed.
