Software is the foundation of all technological advancements we experience in our lives.
Whether Amazon's drone deliveries or Snapshot’s augmented reality offerings – AI in software development makes the world go round.
Enterprises have adopted the latest technologies in their delivery pipelines, and Artificial Intelligence is no exception. The impact of AI on software development changes how enterprises run businesses.
A survey by Forrester revealed that teams are confident that AI for software development will improve agility and testing automation and provide better implementation of RPA bots with supply chain operations. AI tools aim to make software development more reliable, faster, and accessible to the masses.
What will happen as Artificial Intelligence works its way into the development cycle? How will software development change? How will you leverage AI to verify and validate ever-enhancing code suites?
Let us explore these questions and find out their answers below.
How Will AI Impact Software Development?
AI will change how information flows in the software development application pipeline. It can make development more reactive and integrated and promote code reusability. Intelligent tools and open-source AI solutions can reduce project delivery timelines and ensure continuous compliance with stringent regulatory requirements.
Development teams can use AI to build software features that enhance the functionalities of other applications and focus on areas such as quality, testing, and maintenance. AI models can uncover hidden vulnerabilities in designs and routinely conduct exploit proofing. They can prevent security oversights missing controls, and restrict unauthorized access to resources.
QA testers can use AI on the cloud to provide faster deliveries, make projects globally accessible, and reduce time-to-market.
There is no denying that AI can eliminate many blind spots in the development lifecycle, and AI's self-learning algorithms are constantly improving, which means companies will have an easier time tracking and auto-remediating security threats.
Role of AI in Software Development
AI will impact the way we develop the application and we can expect a better app developed under the existing environment. Understanding AI will shape the future of software development; most businesses today are showing interest in AI. 80% of companies smartly investing in AI.
Nearly 47% of digitally mature enterprises have defined AI strategy. It is predicted that by 2021 AI tools alone will create $2.9 trillion in business value.
If you want to adopt this strategy, then you should understand the role of AI in software development and analyze what has changed. Here are the functionalities that AI can offer into software development to deliver extremely customized products or services for your customers.
Areas where AI impacts Software Development
AI plays a key role in the design, code generation and testing of software. Let us discuss each area in detail:
Requirement Gathering
Requirements gathering is a fundamental aspect of any software development project.
Artificial Intelligence offers a broad range of powerful tools like Google ML Kit and Infosys Nia to automate specific processes that minimize human intervention to some extent. It emphasizes detecting loopholes early before moving on to the design phase.
Natural language processing (NLP) can take user requirements in simple language and automatically deliver high-level software models. Large language models can perform various NLP tasks and be trained with custom datasets. Data is the backbone of software development projects, and AI can balance trade-offs and help meet stakeholders' expectations. It can identify and prioritize requirements, define realistic project scopes, and set realistic goals.
Maintaining proper documentation throughout the project lifecycle is crucial. AI models enable better impact analysis, traceability, change management, and collaboration. They reduce project dependencies and enhance clarity throughout the entire process.
Software Design
Planning and designing projects require specialized expertise to propose definitive solutions to clients. Getting the design right in the blueprint phase is challenging for designers. Changes are iterative, and project design processes can take a dynamic approach upon further planning and investigation, lasting until the client reaches a desired solution.
Automating complex processes with AI tools can enhance project efficiency in organizations.
AIDAs (Artificial Intelligence Design Assistants) can help designers understand client requirements quickly and develop appropriate solutions. AI assistance drafts tailored solutions and customizes designs according to unique and individual specifications.
Automatic Code Generation
Developers write code from scratch, which is manual and labor-intensive. To save time and money, they can use AI-powered code generation tools.
AI services can automatically craft code to eliminate repetitive tasks and streamline deliveries across the Software Development Lifecycle (SDLC) pipeline. Automated code output effectively enhances developers' productivity, and systems can convert and execute this code.
Natural language processing in AI and software development can simplify coding complexities syntax and clean up existing codebases. It can accelerate digital project transformation, enable change management, and do much more.
AI in Testing Services
Software testing is an essential part of software development. Running source code maintenance can be costly when it is prone to several changes. AI in software testing can capture and track changes, apply modifications, and implement them.
Many tools can create test cases and perform regression testing. These solutions can make testing error-free and optimize software functionality and performance. Appvance, Functionize, and Testim.io are examples of such AI and machine learning-based testing platforms.
Deployment Control
The impact of AI on software development is evident in software deployment. It increases the efficiency of deployment control activities. Software development involves upgrading apps to newer versions.
If developers fail to execute an upgrade correctly, there will be high risks associated with software execution. AI can prevent such vulnerabilities during the upgrade process and reduce the risk of deployment failures.
Another impact of AI on software development is that it enables developers to analyze deployment processes by leveraging machine learning algorithms.
Benefits of AI in Software Development
By understanding the impact of artificial intelligence and its possibility of future enhancement in software development, you can realize the results of deploying AI technology. Here are the promising results due to the impact of artificial intelligence in software development:
#1. Enhanced Data Security:
Software security is a crucial property that you can’t overlook during development. The system generally collects data from network sensors and software installed on the customer end. AI enables you to investigate the data using machine learning to distinguish irregularities from normal behaviors. Further Software Development Companies adopting AI in their development process can also avoid delayed warning, false notifications, and alerts.
#2. Fixes Bugs & Improves Error Identification:
Examining executable files and software testing becomes much more accessible using AI. Developers can instantly find bugs in production and correct them. Better software design leads to better strategic decision-making.
Diego Lo Giudice, Forrester analyst, says,
“Software developers will be able to build better software faster, using AI technologies such as advanced machine learning (ML), deep learning, natural language processing, and business rules”.
Machine learning solutions empower developers with the ability to learn from past projects as well as analyze the performance of current projects. AI in software development produces better applications.
#3. Improvement in accuracy of estimates:
AI and predictive analytics can find correlations in data and offer accurate estimates of costs, time, and efforts associated with projects. It can analyze historical data trends and significantly impact design and software creation.
Predictive analytics in AI software development can reduce risks, use resources wisely, and prevent surprises. Accurate estimates can help companies prevent project delays and assign developers the right roles and responsibilities.
If necessary, AI-driven predictive analytics can predict future outcomes and make data-driven decisions to adjust plans according to changing industry trends and past data.
