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AI in Software Engineering — Present and Future

ByPayal Mittal
December 23rd . 5 min read
AI in Software Engineering — Present and Future

AI (Artificial Intelligence) as we know it, is the reason behind all the advancements that we see in today’s world, on the technology front (of course!).

Soon, we will see machines or robots taking over most of the humane work.

From healthcare to insurance, banking to finance, eCommerce to Edtech and Fintech, we can see the footprints and lasting impressions of AI in every industry domain and Software/IT is no exception.

In this blog, we will have a closer look at how artificial intelligence impacts the tech industry and where we can see its implementation in the current and future states of software engineering-

Various Prospects of Artificial Intelligence in SDLC

While we talk about software engineering, software development and all related aspects of SDLC (Software Development Lifecycle) come under it.

From analyzing the requirements to designing, developing, deploying, and testing, software engineering vastly covers all these areas and more.

Let’s see the impact of AI in all these phases-

- Project planning and prototyping

The starting stage of SDLC is all about understanding client requirements & objectives, researching, planning, strategizing, and analyzing.

It is of high importance to get the facts straight at the early stage to ensure project optimization in terms of budget, duration, quality, technical effectiveness, etc.

Think about all the scenarios where AI can come into the picture for the rescue and all mundane processes become automated, saving a lot of time and manual effort, while also increasing efficiency to greater levels.

Deploying AI tools and algorithms to predict market trends, the likelihood of change in the current IT picture, and estimation of realistic failure occurrence is huge leverage that software companies can take advantage of to implement agile methods and adapt quickly to the change.

Having a smart machine at your disposal to create a rapid AI-driven prototype, handle tasks assignment and cost estimation with client expectations can provide more clarity over the project outcomes.

- Designing

Are you hearing it now more than ever that AI is going to take over most humane jobs soon?

That’s ridiculous and scary! However, we all should agree on this point no machine, however smart it is, can ever replace the human mind, emotional reach, and organic creativity.

Whatever’s the case, but one should not underestimate the power of growing technology.

Even design system is getting enriched with smarter options like algorithm-based design systems and preferred over conventional methods. Implementing smart algorithms to create a list of all possible iterations and to visualize the dynamic data in real-time is something that can become a game-changer.

While traditional design systems are prone to errors, the permutations, neural networks, and algorithmic designs that AI provides are highly accurate and have the potential to change the entire design culture in the upcoming years.

- Development

The software development phase is where actual coding starts. AI software offers immense applications in this field, for instance-

  • To generate automated prototypes of code, which then can be modified and refined by developers as required.
  • To transform data into contingent vectors for model training and generate interconnectivity among various code levels.
  • Assisting software programmers in coding by offering better knowledge of underlying data and mentoring them to build apps in real-time while improving speed, accuracy, and efficiency.
  • For automated code retrieval of relevant human language elements from natural language queries
  • Auto-encoding and deep learning facilitate easier and efficient data reconstruction and leads to optimized results
  • Advanced AI tools can also directly convert phenomenal requirements and ideas into software models and code in real-time.
  • To automatically convert human language into code and code into machine language

These are only a few of the applications of AI in the development process, there are many others in the list and a lot more are on the way to being adopted.

- Testing & debugging

While testing the functionality of the developed software product or design in practice, AI-driven tools facilitate pattern recognition and help developers to eliminate bugs in the programming stage only.

Test bots, which are intelligent agents developed with the fusion of smart technologies like machine learning, neural networks, decision tree learning, etc., are trending in the IT market to automate various activities under testing, such as creating test models, probabilistic error prediction through big data analysis, automatic debugging, routine error tracing, pattern recognition, and integration of the routine predictions into testing models.

What’s more, AI offers a huge bandwidth to programmers in eliminating human errors, enhancing code quality, and making the entire testing process easier, clearer, and faster.

- Feedback & maintenance

In the software maintenance & support phase, the company assists clientele in updating, refining, upgrading product features and functionalities, resolving queries and concerns, whenever and however required.

AI automates this process by rendering a self-adaptive runtime decision engine to enable applications to adapt and reconfigure as per changing network requirements without relying on human support.

Also, the pattern recognition and prediction principles of AI can further help the developers to be able to enhance the project model and features accordingly in the development phase only.

Future applications of AI in Software Industry

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Artificial intelligence is our future, and we will see it applied at every step of the software development life cycle. In fact, we can expect complete automation of research & planning, design & development, testing & debugging, and software integration in only a few years.

  • Automated routines will be on the hype, and we will see enhancements in the capacity and creativity of human developers. This increased potential of the workforce in turn will help companies gain a competitive edge in the software industry vertical.
  • Software companies will invest in expanding their data team and resources while streamlining AI to all operations, to maximize ROI and improve speed, proficiency, and productivity.
  • Security is another important factor where we will see quick advancements in the future. Having AI pattern recognition and data prediction facilities, companies will be able to pinpoint the potential attack risks to weaponize themselves against them in time to avoid any crisis event.

Apart from leveraging from AI, we will also witness a major rethinking in the tech industry to reflect and address the serious impact of carbon footprints left by AI.

We will see a sudden surge of green AI into implementation for a better, sustainable, and eco-friendly future.

We are a software/IT service-provider company that deals in various technology verticals as well as smart solutions like AI, Machine Learning, IoT, etc. If you are looking for any assistance for your next project, do contact us!

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