Table of Contents
» What is AI?
AI, or artificial intelligence, is a term used to describe the ‘intelligence’ of computer systems, as opposed to human thinking. In this context, ‘intelligence’ refers to the ability to think, predict, and identify patterns and action sequences. AI is a growing phenomenon, although it has been in development for many years. Image sourced from statista.comAI-powered tools have a vast number of uses, ranging from powering smart homes to improving sales tactics. It can be applied to something simple, such as asking your phone’s voice control to show you restaurants nearby. It can also be integrated into hugely complex systems, like computers designed to solve complex equations for commercial technology. In practice, the most useful capabilities of AI systems include:-
- Predicting human reactions to specific events.
- Predicting the outcome of a sequence of events.
- Identifying patterns.
- Extrapolating information from input.
- Understanding human behavior and thoughts.
» How is AI Used in Software Development?
Software development aims to create useful digital products that simplify and streamline everyday processes. The goal is to expand the capabilities of individuals and businesses. Successful software products need to be highly usable, scalable, and adaptable. A good example of this is cloud-based communication software, such as VoIP phone systems or the cloud-based PBX from Vonage. Their success comes from embracing a specific audience, huge scaling potential, and the ability to add or remove services as needed. It’s vital that development teams understand their audience intimately and are able to anticipate and react to any potential issues that arise. While it’s possible for development teams to gain this understanding for themselves, AI may be able to do it better. For one, AI removes human bias from the so-called ‘human experience’. If you’re a developer, you might think that you understand how your audience feels based on your own perspective. However, an AI program can build this understanding in shorter time periods, looking at far larger datasets than any human developer. So, AI can be used in software development to ensure software caters to its entire audience. AI’s role in software development is a supportive one. It enhances what development teams are able to offer to customers by providing a different viewpoint and predicting events and reactions that might have been missed by developers.» 6 Ways AI Enhances Software Development
How exactly does AI enhance the software development process? AI can be used in the development of any digital product, from a simple B2B website design to a complex system of applications. Image sourced from statista.com You’ve already seen that AI essentially presents more information for development teams. With that in mind, let’s take a deep dive into how development can be supported and enhanced by the inclusion of AI programs.1. Faster Development
For a number of reasons, AI can lead to faster development times. The major factor here is that AI is able to take over some of the more repetitive tasks associated with software development, such as repeated testing and debugging. With less time spent on these tasks, developers can devote time and resources to innovating within their software. Testing and debugging can also be done concurrently with amendments. This allows the software to be rolled out faster than if each task were to be done sequentially.2. Easier Decision-making
Image sourced from signal-ai.com How does AI support decision-making? By learning!One of the major advantages of AI is that it learns using objective, real-world data, allowing it to act on a large variety of perspectives and user journeys. It, therefore, allows development teams to make fast, informed decisions where they might lack a user's perspective. Consider the example of visual design and branding for a new piece of software. This doesn’t seem like a huge area of development. It can, however, mean the difference between widespread adoption and market failure. So, you’ve got your basic software, and now you’re choosing between a sleek, neutral design or playful, bright, colorful branding. Everyone on your design team will have an opinion formed by research and their own experiences using similar software. This can create chaos in the office, with so many contrasting opinions and perspectives. AI can support decision-making at every stage of the software development process, from initial consultations to continued testing and rollout. This is because AI can learn to predict outcomes and reactions in a huge range of situations using collected data.It is most effective when used in conjunction with developers, checking and testing the decisions made by AI. Remember, AI removes human bias, but it also removes a lot of human experience and nuance.3. Predicting and Managing Errors
One of the major talents of AI that developers are particularly keen on is the ability to make predictions. Certain AI models have been developed to predict how human users of software will use the program and react to potential issues. This can also be applied to development teams themselves. Common development errors are learned by AI and predicted at certain points in the development process. By being able to predict common mistakes made by developers, an AI program saves time and reduces the cost of fixing errors. AI can also detect errors in the software or bugs. Bugs are common in the development process, and finding them is an integral part of being able to roll out the software for general use. For example, some AI programs can run usage sequences based on typical user experiences. If a problem arises, the program will notify the developers, and can be fixed before further testing.4. Supports Testing
On the subject of testing, artificial intelligence programs can be extremely useful for automated testing. All software should be tested manually before release to ensure that it works for its intended audience. Purely automated testing can miss important errors because, simply put, machines cannot always think like individual users. However, routine testing and testing with large data sets can be done using AI, supporting the development and testing team. For example, consider a new CRM system in development. It has two sets of users to consider. The first is the customer inputting their data to sign up for newsletter updates or make a purchase. The second is the brand, using the system to collate customer data. The development team needs to manually test the system with mapped-out user journeys. This is a job best suited to individual testers who understand how users will interact with the system. However, the forms and data processing also need to be tested using a large volume of data. This is where AI comes in. You can use AI to automate simple, routine tests to save your development team time and resources, best devoted to more complex testing.5. Collate and Action Feedback
As we’ve already established, AI learns based on data input into the system. A critical part of software development is testing and collecting feedback at each stage. This is the most effective way of maximizing the usability of your product and ensuring its long-term success. Where does AI come in? Integrating an AI tool into your feedback system allows you to collect and collate data. The AI program can then process the data into actionable insights. While it will always be necessary for a development team to spend time reviewing and learning from feedback, the use of an AI tool can make life easier. AI can identify key points of feedback and save time actioning feedback on common errors.6. Transforming How We Think
Fundamentally, what does AI provide us with? A new perspective. As a program designed to ‘think’ like a human user, AI will never ‘think’ in quite the same way as an end-user or developer. While this might sound negative, this is actually one of the most useful features of AI in software development. Software developers are always looking to go beyond what was previously thought possible and trying to find new ways of helping end users. This has long involved seeking out new innovations and technological capabilities. Even the most creative of development teams are limited based on their unique perspectives and experiences. AI can learn on a much wider scale than human developers can. Based on huge datasets - which may, in practice, be hundreds of unique experiences - AI programs can introduce new perspectives to software development. This means identifying needs that developers might have previously never considered. For example, consider a team developing a domain checker to find, purchase, and manage available domains, supporting new businesses in the tech field. Following extensive research, the team has come up with a list of requirements for the end user. The software should:-
- Automatically detect the availability of the target domain across all sites worldwide.
- Integrate into existing CMS and web hosting software.
- Be scalable for agencies running multiple websites.