The Potential Impact of Artificial Intelligence Assisted Software Development

The Potential Impact of Artificial Intelligence Assisted Software Development

Artificial intelligence (AI) is growing rapidly and it is imperative that any software solution company that would like to stay relevant in the present business landscape pays careful attention to AI developments that improve and streamline the software development process. It is safe to state that the core concepts that govern software development remain the same but the pipeline is going to undergo a considerable transformation at almost every stage. AI is poised to make the development process more efficient, less stressful, and even enjoyable. 

Technology as a whole is growing at breakneck speed as access to elastic computing power through public cloud systems allows developers to deploy heavier workloads, achieve greater parallel processing power. Businesses are investing unprecedented funds for data collection and last but not least, microservices. Microservices enable the distribution and integration of previously monolithic systems. This results in tools that comprise multiple platforms or systems. The points below expound on the areas AI can improve and assist in the development process and post-development. 

Augmented Analytics

The ideation stage could benefit from AI. Consider an e-commerce website, the sales or marketing team would traditionally analyze the data to find where users exit an ordering funnel and then devise a strategy to improve conversion. AI could be used to blend analytics with performance data to come to determine the cause of users exiting the funnel. 


Writing test cases for legacy system is a time-consuming task. Automated test creation tools could map out the application’s functionality with code and analytics data. Developers could then make minor modifications and complete the testing process quickly and efficiently. This would reduce the chances of existing functionality breaking as well. 

System Maintenance 

A predominant cost factor in system maintenance is associated with managing redundant features. The identification of redundancies in a large system is an arduous, time-consuming, and expensive endeavor. There is a good chance of errors that could arise in the process as typically people are given the task of correlating data with different sources. This is where AI tools could be used to avoid the problem of human error, such tools could connect and reference data across multiple sources faster and more efficiently.   

In conclusion, AI-assisted software development is still in its infancy but companies must keep a watchful eye on how the technology develops. Development companies must recognize and leverage elastic infrastructure. This ensures that the company is able to add or remove resources better by efficiently handling load variation. It is a good idea to equip development teams to strategically collect and process data, this would prove to be an important asset that can assist AI systems. It will always benefit a development company to include of stream in the overall investment strategy that focuses on AI growth. This will put the business ahead of the competition effectively making them “early-adopters” of a sector that is bound to grow exponentially. 

AI by no means is a technology that can completely overhaul the software development process but rather a set of tools that enhance the software development process. This could result in cost-effective software projects with minimal human error and semi-automated software development. 


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