5 Ways AI Improves Software Development | Trends + Examples
As per a McKinsey survey, 56% of businesses have already adopted AI. And the most common use case was product and service development.
It's not surprising, though, if you think about the current consumer base.
Customers are changing fast. A 2022 Accenture survey of 25,000 global participants shows 60% of consumers are changing their priorities. For these changing customers, AI is helping to:
Keep up with fast-changing than ever requirements
Automate repetitive tasks and deliver results faster
Provide top-notch customer service
These are the top changes AI software development brings at a high level. In this post, we will further see the use of AI in software development at the ground level across different SDLC(Software Development Life Cycle) phases.
1. Improve requirement gathering
A project with incorrect or not enough initial data is doomed right from the start. AI helps businesses to take a more data-driven approach by listening to customers. One way of doing it is to analyze the brand's call center data, reviews, and social media conversations using AI, then find customers' key pain points and address them head-on.
Steve Jobs, Co-Founder of Apple, once said, "You’ve got to start with the customer experience and work backwards to the technology…I’ve made this mistake probably more than anybody else in this room…As we have tried to come up with a strategy and a vision for Apple, it started with ‘What incredible benefits can we give to the customer? Where can we take the customer?’...I think that’s the right path to take." Apple continuously uses customer feedback to bring enhancements.
2. Increase in plug-and-play development
Developers now don't have to build everything from scratch. AI code assistants enable developers to write code faster by suggesting code. Also, many AI microservices have been launched. Microservices are small modules or functions which you can quickly plug into your code. This is one of the biggest benefits of AI in software development. You don't have to reinvent the wheel by spending hours on what's already available.
Sentient, the AI development company, provides microservices for:
...and many more
3. Automate testing
According to the Tech Beacon World Quality Report, 88% of enterprises are considering using AI for testing, and 80% are already in the trial or proof of concept phase. Manual testing is a laborious task whereas AI in testing provides benefits like:
Automation of repetitive test cases
Better test coverage
Saving time
Getting advanced features like visual testing, where AI can recognize patterns on the web page and run tests accordingly
And guess the best part? You don't have to write these AI scripts from scratch. Testing tools powered by AI are already available like:
Applitools
Functionize
Testim
TestCraft
Mabl
4. Optimize DevOps
Code deployment and regular maintenance are also other big tasks post testing. DevOps team can use AI to do post-prod support efficiently by:
Timely alerts
Forecast failures
Better resource management
Detecting bugs
Auto-suggesting code for bugs
Fastening deployments
Auto-running test cases
For instance, Facebook built a tool called Getafix which can automatically find fixes for bugs and engineers only need to approve it. It allows engineers to work more effectively and promotes better overall code quality.
5. Be future-ready
AI helps the development team to be future-ready in three ways:
AI automates repetitive tasks so developers can focus on solving bigger and more interesting problems for the future.
Advanced AI services/tools are easily available. So, it's easier to do a proof of concept and promote your tech stack with time rather than spending years building from scratch.
AI can help you understand user behavior and come up with future product changes.
For example, the automaker Tesla has a loyal customer base. And they worked hard smart to earn that loyalty. Its algorithms process data from its fleet of over millions of cars in real time and pass on the findings to multiple product development teams. Those data-driven insights enable the teams to develop new versions at speed. AI helps Tesla in continuous improvement not based on guesses but on data.
While there are many other advantages of AI development, these are the top five ways we see AI can turn around software development.
Shorten your development life cycle with Sentient
Jeremy Morgan, Senior Developer Advocate at Pluralsight, says, "We are not paid to write code. We are paid to solve problems." So make use of all the tools/microservices available, reduce development time, and solve problems faster.
Sentient can help you with:
Object Detection
People Counting
People Recognition
Natural Language Processing
Word-sense Disambiguation
Entity Recognition
Voice AI
Automatic Speech Recognition
Text to Speech
... and more
Take a demo now and save development time.