5 Ways AI Simplifies the Software Development Process

Until the last decade, software development was a new chapter in the history of enterprise evolution. However, with time, the industry has evolved on its own. The industry is undergoing continuous churn. As a result, there are new technological evolutions each year.

AI in software engineering is a new saga in the continuous evolution of the software engineering sector. AI is a technology that can conclude tasks that require human intelligence and discernment, for instance, the ability to perceive, reason, and generalize.

Companies try to aim for faster time to market and greater productivity while keeping costs to a minimum. AI solutions is helping to accomplish this by automating dangerous and repetitive tasks.

A software development company uses algorithm-based machine learning to accelerate the software development lifecycle (SDLC), and AI helps the developers optimize the application development process workflow.

Using AI in software development, development teams can improve their planning process. They can also manage quality assurance (QA) activities and enhance the user experience. As per a study, AI-powered software development increased a developer's productivity by 10 times.

Having understood the positive impact artificial intelligence has on the software development process, let us look at how AI enables an enterprise software development company to develop better web applications.

AI Software Development Process: Steps for Successful AI Software Development

The impact of AI and ML in software development has been immense. Let us look at the steps that can be followed for AI-based software development.

1. Defining Use Case

• AI in software development requires that specific problems or challenges are clearly defined before initiating the development process.

• The planning team should be particular about defining the core problem. The success of the project depends on how well the challenge is explained and understood by the development team.

2. Verify Availability of Data

• After acquiring a good understanding of the real problem, focus on putting in place the resources that can gather the necessary data to conduct the required analysis.

• Make sure you utilize the most accurate data set in the correct quantity. This will allow you to move swiftly through the AI software development process. In addition, this will enable you to reap the full benefits of AI in software engineering.

3. Data Exploration

• Performing an essential data exploration before jumping into the central programming part of the project is critical.
• It helps to ensure that the AI's data assumption and understanding align with your expectations.

4. Defining a Clear Methodology for Building and Validating AI and ML Models

• To approve the hypotheses and improve their execution, developers must run tests to uncover any significant variables or features.

• Successful integration of features is necessary to ensure the success of the AI/ML in software development model. Therefore, the role of a subject matter expert is much more crucial than an algorithm in the effort to define a methodology for building an AI or ML model.

5. Select Between Data-Driven AI and Model-Driven AI

• A data-driven AI model is used to develop a system that can help identify the correct answer based on patterns of responses it has seen and the training it has received.

• On the contrary, the purpose of model-driven AI is to capture knowledge and enable decision-making through clear-cut representation and rules.

6. Ensuring Implementation of Key Steps in the Development

• There are three key steps necessary in the implementation of AI software development. The steps are as follows -

  • Develop an AI strategy
  • Determining and Ensuring Your AI Readiness
  • Preparing a proof of Concept

7. Ensuring Cloud Software Implementation

• Earlier enterprises interested in AI/ML-powered software solutions had to invest significantly in buying servers powerful enough to support the technology. This was a significant deterrent to the acceptance of the technology.

• However, the problem has been overcome with the advent of cloud technology. Cloud satisfies the computing needs of ML without spending loads on it.

8. Testing AI Softwares

• AI in application development has changed how a software development company used to go about its usual development process.

• Testing, a crucial part of the development process, has been automated with the help of AI-based technologies. Software developers globally are leveraging AI to test and verify the source codes.

• AI-driven software testing includes developing test cases, developing test scripts, and maintaining the test case and script.

9. Automate and Rollout the Software

• Once even testing is done, the AI-based software model must be rolled out into production.

• A wise idea would be to initiate a limited rollout over the first few weeks and months. Then, the development can grow further based on the feedback received from the limited rollout of the AI/ML model.

10. Retrain the AI Software Frequently

• Unlike humans, AI systems can not learn different things simultaneously. Therefore, in case you want the AI to grow and do much more, then it needs to be trained even more through the training for that particular task.

5 Ways AI Helps to Simplify the Software Development Process

1. Increased Speed and Scale of Development

• AI/ML models help developers shorten the processes, especially software testing. AI can run various tests automatically rather than manually by quality assurance analysts.

• AI helps to conduct fast and accurate testing that helps to cut down the failure rate and the development process.

• AI software development companies use the technology to streamline processes, reduce waste, and automate repetitive manual processes.

2. Error Management

• Error management is perhaps the most time taking process in software development and management. This is especially true for software as a service (SaaS) or a cloud-based platform-as-a-service.

• Your customers depend upon your product round the clock, and each minute of downtime can cost your reputation. Artificial intelligence can help you to detect and diagnose errors in the application without human involvement in an affordable manner.

3. Better Decision Making

• AI software development tools can enable strategic decision-making while reducing the footprint of human intervention. AI is considered wise and can learn from human actions and patterns. It observes actions and consequences closely.

• AI tools can research on your behalf. Such tools analyze the data and provide the best insight possible. Based on the insights, the development teams can define what kind of software features can assist the organization in meeting its expectations.

4. Accurate Estimate

• Software developers usually find it difficult to estimate the project's exact timeline and value. The AI models trained from past projects can help you calculate the timeline, budget, and resource requirements.

• Without AI, it isn't easy to estimate the roadblocks that can appear during the software development project.

5. Writing Better Codes

• AI software development tools can be helpful for software programmers in cutting down repetitive tasks.

• This helps the developers to gather more time that can be utilized for conceptualizing better application features and robust programming. In addition, the developers can also enhance their skills while finding creative methods to use Artificial Intelligence.

Wrapping Up

Artificial intelligence is the future. The AI use cases in software development will increase more and more soon. AI-powered software development helps to enhance the process, lifecycle, and ultimate software application.

AI has already proved as an effective IT solution enabler. It helps build error-proof applications rapidly and with increased scalability and maintainability. Since developers spend roughly 50% of their time on non coding activities, AI has a huge potential to save the day for the development teams.