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6 Ways Artificial Intelligence Improves Software Development

Artificial intelligence is transforming software development. From the code to the deployment, AI is slowly but surely upping its game and helping us discover a brand new paradigm for inventing technology.

Algorithm-based machine learning is being used to accelerate the software development lifecycle and AI is supporting developers to optimize software workflow at every stage of the development process.

We can expect big things in the future as AI brings in disruptive developments for software developers. As AI redefines how developers work and how their codeis built and managed, the industry should improve in leaps and bounds in terms of productivity, quality, and speed.

Artificial intelligence is a term for computer systems that can perform tasks that require human intelligence and discernment, like the ability to reason, perceive, and generalize. The computer should be able to sense its environment and take action according to what it learns.

AI algorithms can improve project planning, aid with automation QA (quality assurance), and enhance user experience. A recent report found that AI-enhanced software development increased the productivity of a developer by 10 times.

Here are some ways AI can power your software development and deployment processes by automating various cognitive and physical tasks.

1. Increase in the Speed and Scale of Development

How DevOps will change once AI is rooted within every part of it can be judged by key aspects of software delivery performance. Deployment frequency, lead time for changes, and time to restore service are all key performance indicators that are time-based. Machine learning or deep learning can shorten several processes, especially the testing of software. AI can run tests automatically, rather than them having to be run manually by quality assurance analysts. Not only does this save time but it ensures more scenarios are tested. AI is, in fact, critical to the quality assurance process as manual quality assurance has a high chance of error. AI enables a computer to do fast and accurate testing that reduces the failure rate and shortens the development process.

Software developers need to use AI to streamline processes, reduce waste, and hand over repetitive manual processes to a computer that can do it faster and better. A machine learning-backed hyperautomation platform will also automatically verify deployments, saving even more time. AI can help to code too, increasing speed and accuracy.

Source: Pixabay

2. Changing The Role of Developers

The role of software developers is evolving because of AI. It can help them with their code, but we’re years from the time where it will write code on its own or replace them. However, when developers automate tasks and assign them to an artificially intelligent machine, they can concentrate their abilities on a different set of tasks and develop skills that help them work collaboratively with AI.

With AI taking on simple tasks, programmers have time to concentrate on more complex problems. This is how their roles will transition. This will thus improve the software development process rather than replacing it. In fact, with AI in the picture, there will be a need for new software developers - ones who can work together with AI, not to mention those who can actually code it.

AI may write code one day, but even then it will not replace programmers. Software developers need to work with AI to write better code. Giving the tedious parts of the code to AI while taking up the challenging parts can be one way to collaborate.

There is a lot of concern that software developers will become obsolete if AI learns to write code, but software development is complex and needs a human brain to give it direction.

Increase in the Speed and Scale of DevelopmentSource: Pixabay

3. Strategic Decision-Making

AI can greatly impact strategic decision-making by automating it and reducing the need for human intervention. AI can radicalize decision-making by reducing the time spent debating on which products and features to invest in. If your AI is trained based on the success and failure of previous software, it can assess the performance of new software and minimize risk.

Expect decision-making in the software development process to be revolutionized because all decisions will be driven by analytics. As computing power and data storage increase exponentially year on year, computers will be able to augment human intelligence by helping us make smarter decisions.

Better decision-making that is rooted in past behavior and based on analytics will help mitigate risks and the costs associated with them. Decision-making by AI will also help eliminate human biases and errors. Data can help make intelligent and informed decisions. Machine learning gathers, analyzes, and leverages data and then the computer makes decisions based on this.

4. Error Management

When you provide past data and software analytics to your AI-powered programming assistant, it can learn from experience and identify common errors. If these were flagged in the development phase, it would reduce the need to roll back. Machine learning can be used by operations teams in the post-deployment phase, too, to proactively flag errors and uncover abnormalities by analyzing system logs.

Error management is responsible for most downtime in software development, especially if you run a software as a service (SaaS) or a cloud-based platform-as-a-service. With customers using your services round the clock, every minute of downtime costs you money and negatively impacts your reputation.

When an error is found in software, a developer has to manually correct it. This is a time-consuming process. With artificial intelligence, you can automatically detect and diagnose errors in the software without human interference. This process is efficient and cost-friendly.

5 surprising sneaky ways

5. Precise Estimates

Software developers are notorious for never being able to provide good estimates on timelines and costs. AI trained on data from past projects can help you provide precise estimates so you can predict the time, effort, and budget required. A sensible prediction needs expertise and understanding of context, and you can train AI for these.

Without AI, it is hard to predict the roadblocks you’ll encounter on the way and how badly they will push back deadlines. This information can help an organization decide which projects to accept and which not to. When you accurately inform clients about software delivery, it increases customer retention and bodes well for your business.

6. Connect to Real-Time Feedback

Most video conferencing software has real-time feedback from users embedded in the app to improve customer experience. Real-time input from AI-enabled software development tools can change how users use your software and how they interact with it.

Machine learning algorithms can be trained to notice how a user interacts with a certain platform. AI can create a dynamic software experience, serve variable content, and then provide the developer with statistics on what on-page element needs improvement.

Continuous feedback can ensure the customer experiences no to minimal downtime, with software more accessible if errors are fixed on the go via a continuous feedback loop.

AI is the present and the future

AI is soon going to be invaluable to all business applications in your modern software company, and you can enhance your software development process by incorporating it into as many sections as possible. Soon, AI will become a necessity for software developers. It has already taken center stage as never before, and it won’t cede the spotlight anytime soon. Whether it’s the AI-assisted automation of an office phone system, an AI-powered chatbot, or AI making decisions, soon we won’t be able to do without it.

The software development landscape is changing faster than we can keep up with it. To stay ahead of the competition, you need to be aware of new technology and adopt it as soon as possible.

As discussed above, the benefits of AI are not limited to the development process. The most beneficial aspect of AI is to reduce time in any given process, and time is a critical factor for all DevOps organizations. AI exists to support human endeavors and reduce intensive human labor. It’s already making a difference and creating waves in many fields, and software development is only one area where it will soon have a significant impact. As coders, testers, and project managers all become more productive, organizations are likely to produce higher-quality software at better prices.

AI is the present and the futureSource: Pixabay

Author:

Sam O'Brien is the Director of Digital and Growth for EMEA at RingCentral, a Global VoIP, video conferencing, and call center software provider. Sam has a passion for innovation and loves exploring ways to collaborate more with dispersed teams. He has written for websites such as G2 and Hubspot. Here is his LinkedIn.