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How will AI change software development and applications?

Software development is going to see some major transformation in the coming years. The transformation will be driven by Artificial Intelligence (AI) and Machine Learning (ML). It would be interesting to see how AI will change software development and applications. Recent developments in Artificial Intelligence are already helping developers at various stages of the development lifecycle, and it is also going to transform it further.

It is estimated that around 80% of the companies are investing in AI. On the other hand, 47% of digitally mature companies are defining AI strategies. Based on these numbers, you can understand the benefits AI provides them with.

How does AI affect software development?

Artificial Intelligence in software development has so far been successful in increasing the productivity, speed, and quality of the development process. Software developers are using AI algorithms to improve multiple stages – project planning and estimation, user experience, and quality testing.

Also, AI enables computers to think. As a field of Artificial Intelligence, computer vision allows computers to analyze digital images, videos, and other visual inputs and to derive meaningful information from that data – then act on it or make recommendations based on it.

As per Deloitte report, software development, which is AI-driven, helps developers increase their productivity by 10X than they would have worked on their own.

AI for software development

Source: Unsplash

In this article, we will discuss how Artificial Intelligence is transforming software development.

How is AI used in software?

AI software design, when done smartly, can change the way we go about developing applications. It is expected that developers can develop better apps using AI in the existing environment. AI can be used in many areas in software development processes. The popular ones are:

Requirement gathering

Requirement gathering has always been a human-driven phase. However, AI is about to change that with its broad range of tools and techniques. Using tools and techniques like Infosys Nia and Google ML Kit, you can automate certain processes in the requirement gathering phase and reduce human intervention.

AI takes the requirement gathering a step ahead as it detects loopholes even before the project moves to the design phase. Using Natural Language Processing (NLP), you can make machines understand requirements and automatically drive high-level software models.

Software design

You need specialized experience and learning to propose a solution for a project. The software design phase moves backs and forth multiple times unless the client reaches the desired solution. AI tools automate complex procedures and enable the most optimized solution for your project.

One of the best examples is AIDA – Artificial Intelligence Design Assistant. It can understand the desires and the needs of the client. Using the knowledge, it designs the project.

AI in design

Source: Unsplash

Automatic code generation

The stage which takes maximum time in software development is coding. From business ideas to writing code is a labor-intensive and skillful task, especially if the project is big. It requires both time and money.

Assume a scenario where you explain your idea to a machine through natural language. The machine (or system) understands what you are saying and converts your idea into a code that you can execute. Does it sound like a science-fiction movie story? It is not as it is very much possible through AI tools and NLP.

Software testing

Software testing is also an essential phase of software development. How well you test your code will determine the quality of your product.

You can use AI to create multiple test cases and perform regression testing. It will not automate the testing process for you, but also ensure the testing is error-free.

Image recognition

Using image recognition in different industries, such as gaming, automotive, and E-commerce is increasing every day. A widely used example of an image recognition application is Google Lens. Retailers are particularly interested in adopting this technology because it allows them to understand the context of images. It then provides personalized and accurate search results to the users, which are entirely based on their behavior and interest.

The Global Image Recognition Market stood at USD27.764 billion in 2020 and is growing with a CAGR of 17.59% to reach USD73.344 billion by 2026. Image recognition is a subfield of computer vision that identifies objects and attributes in digital images and videos.

Deployment process

Algorithms used in Machine Learning also affect software deployment. Machine Learning increases the efficiency of deployment control. Developers will upgrade programs and apps during this process. With upgrade issues, your existing application may be affected. Artificial intelligence can prevent such failures during the deployment process.

AI for deployment

Source: Unsplash

How does AI help software development & how is it beneficial?

We have seen above in what areas AI is used in software development. AI as part of Software Development will improve development, automation-testing software, and agile test automation.

Next, we move to see how AI helps in development. Artificial Intelligence, when coupled with Machine Learning and Deep Learning, has the potential to transform the software development process. In this section, we will talk about the benefits of AI Consulting & Development in the process of software development.

Changes the role of software developers

The technology is surely not going to replace developers but is certainly going to replace the role. In the coming years, you may see developers working collaboratively with AI for coding. The role of AI will be to take on simple and repetitive tasks. The developers will focus on complex problems.

Take advantage of Cloud computing

The application of AI in Cloud environments delivers an enhanced experience for customers and users. We know of the all-pervasive and intuitive examples of Alexa and Siri, which enable everything from playing a song to making a purchase.

In Machine Learning models, vast sets of structured, unstructured, or raw data are used to train the algorithms. These require the processing power of many CPUs and GPUs, which is enabled only by an ideal combination of public, private, or hybrid cloud systems. All major public Cloud service providers offer readymade configurations to developers to build, test and deploy Artificial Intelligence applications in the Cloud.

AI for Cloud

Source: Unsplash

Quick prototype

Ideas are always wonderful, but to figure out how much impact they will make requires a lot of time and planning. With the help of Machine Learning and AI, developers can shorten this process. They can create prototypes by using visual interfaces of natural language and help you decide whether you want to develop the idea for an app (new feature) or not.

Testing at high speed and scale

When it comes to quality assurance, the role of AI is becoming critical now. Until a few years back, quality assurance was a manual task. Hence, prone to errors. With AI in the picture now, it enables accurate and fast testing and improves the process where it was not possible earlier with human testing. It brings down the testing process duration and gives higher quality.

AI is being used to create test bots that identify software bugs. AI is also being used in differential testing that compares the application version and classifies differences and gives you a timely alert of any action required.

Apps are deployed faster in market

Using AI, developers can write better codes, and that is too much faster. AI enables coding apps like Deep TabNine, Kite, and Tara to bring autocomplete features into the software development process. Hence, it improves the speed of the coding.

AI automates error management

The usual process is that when an error is found in the app, the developer has to go back to the code and investigate hundreds of lines of code. It can take a lot of time to find the error. Once the error is found, the developer fixes it.

The beauty of Artificial Intelligence is that it can automatically detect, diagnose and fix the error with no involvement from the developer. It increases efficiency and brings down the maintenance cost. Not only this, but it can also fix the errors by predicting the errors by searching through the databases to point any abnormalities. Abnormalities could be bugs, misclassification, or missing code.

AI for error-free coding

Source: Unsplash

Better planning and cost estimation

It is always difficult to predict the obstacles developers or testing teams will face during the various stages. Hence, software development estimates are a challenge.

AI makes use of data from the existing data from the past project and brings other factors as well to help you determine the accurate software development estimate. It makes the life of leaders a lot easier since they can decide which projects need a green signal and which ones need to be put on hold.

Customer feedback on the go

AI-enhanced development tools enable users to provide feedback in real time, changing the way they interact with technology. Chatbots driven by AI and ML algorithms learn the user preferences and interests based on their responses to actions and engagement with the brand. This not only helps companies improve their customer service but also incorporate user feedback into future product development.

Ways to integrate AI into software development

We have talked so much about AI in software development. You must wonder how you can integrate the two. Here is an example for you.

A code line in an IDE can be predicted by AI-based algorithms. Currently, IDEs can only recommend a method to developers. Using AI, IDEs can take the next step in completing the method invocation and fill in the required arguments and parameters. In short, it will speed up the development process and also reduce syntax errors.

AI-based software development

Source: Unsplash

How does Big data relate to Artificial Intelligence?

In today’s world, Big data and Artificial Intelligence are inseparable because of AI’s ability to work expertly with data analytics. AI Machine Learning and Deep Learning combine data from multiple sources to create newer rules which will assist future business analytics for Data Science companies.

Artificial intelligence and Big data have a synergistic relationship. In order for AI to learn and improve decision-making processes, a large amount of data must be gathered and analyzed, and Big data analytics leverages AI.

Will AI replace app developers?

From the above discussion, one may wonder, whether AI will replace app developers. The answer is no, at least not soon. However, programmers have to keep themselves updated with the latest technologies. Technologies that can generate computer programs that do not involve any coding.

AI is not seen as a replacement for human intelligence and creativity, it is basically seen as a supporting tool. Humans can make use of AI to help find out possible consequences and streamline the difficult decision-making process. Although AI companies will eventually develop complex solutions, these are hard to replace with readymade tools that can be easily downloaded and easily used.

AI is gradually penetrating almost all digital spaces, like the gaming industry. Artificial Intelligence has revolutionized game development. AI for game development enhances the gaming experience by addressing the needs and concerns of players.

One thing is for sure, AI has the potential and it will remove many tasks programmers are doing currently. App developers should not get worried about it. Instead, they should embrace the benefits that AI profits from them. The trend is inevitable, and hence it is better to enhance the skill set to adapt to the changing landscape.

Conclusion

The market is seeing tremendous growth in using AI in software development. Artificial Intelligence software engineering is also growing exponentially and will continue to remain in high demand in 2022.

With AI-based tools, it is now possible to automate the ML model training, thus improvising ML consulting that most developers seek. It helps reduce the workload of data scientists.

Also, many AI-oriented solutions in the market automate or streamline the key components of requirement gathering, model deployment, and scaling. Artificial Intelligence has a significant impact on the design and creation of software. Undoubtedly, software development companies have to adopt the potential benefits of AI. It will be a game-changer in the future.

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