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AI is revolutionising the way software engineering teams conceptualise, construct, and evaluate applications. AI-augmented development has become a strategic trend with profound implications for the industry. It presents a solution to the ever-growing need for faster software production, aligning with the increased reliance of businesses on digital applications to meet their operational and customer needs.
Gartner predicts that by 2026, generative AI will significantly alter 70% of the design and development efforts for new web applications and mobile apps. In response to the increasing business requirements, IT leaders must spearhead the integration of AI-enhanced development tools and methodologies that empower software engineers to produce top-tier applications.
1. Generative AI and its Transformative Potential in Application Development
The integration of AI in software development promises to revolutionise various aspects of the process. For instance, AI coding assistants can significantly reduce the time and effort software engineers invest in tasks such as coding, documentation, debugging, and refactoring. These tools are evolving, enabling engineers to handle even more complex activities with ease.
AI-augmented testing tools are also making waves, accelerating the testing process by optimising test efforts and offering early feedback on the quality of release candidates. This enhances the consistency of testing across various dimensions, including unit, API, functional, and nonfunctional testing.
Design-to-code tools are becoming increasingly AI-augmented, streamlining front-end development by generating production-ready HTML, CSS, and JavaScript directly from UX design tools like Figma.
2. Unlocking the Potential of AI-Enhanced Software Engineering
In the current landscape of rising demand for enterprise software, look to tap into the potential of AI-enhanced software engineering tools for optimal results. To effectively harness the power of AI in software development, IT leaders should consider the following key recommendations. Firstly, to enhance efficiency, designate senior members within software engineering teams to oversee the seamless integration of AI-driven coding assistants. Collaboration with security, legal, and compliance departments is also crucial to address and mitigate potential risks associated with AI-generated code and text, ensuring the integrity and compliance of the software.
Secondly, focus on optimising the testing process. Employ AI-augmented testing tools to generate test code, create test data, and develop stubs. By making AI augmentation an integral component of your continuous quality strategy, software development and testing become more efficient and robust.
For accelerated development, embracing design-to-code tools is recommended. These tools can convert front-end designs into functional code, streamlining the development process. In doing so, it is essential
to involve UX designers and front-end developers to ensure the seamless adoption of these tools and alignment with the established design system.
It’s important to justify the investment in generative AI technology by clearly articulating its value proposition. This technology should not be viewed merely as a cost reduction tool or a replacement for staff; instead, it should be positioned as a force multiplier that enhances the productivity and efficiency of software engineering teams.
By harnessing generative AI tools, software engineering teams can create more value, streamline processes, and accelerate innovation. To establish a clear understanding of this value, define and measure productivity metrics that reflect the impact of generative AI on project outcomes and delivery timelines. Moreover, set expectations with business executives that their increasing demand for quicker delivery of digital products will naturally lead to a heightened need for software engineering talent.
As we move into 2024, Gartner anticipates that generative AI and machine learning will significantly alter the landscape of web and mobile application design and development. The demand for software engineers who can effectively utilise these AI tools will surge, and it's crucial to dispel misconceptions about AI's capabilities. These tools are not replacements for engineers but force multipliers that enhance productivity and creativity.
AI-augmented development is a strategic trend with far-reaching implications. It offers a solution to the ever-growing need for faster software production in response to increased business reliance on digital applications. Ultimately, integrating AI-augmented tools into the DevOps cycle promises streamlined workflows and improved developer experiences.
Gartner analysts, including Van Baker, will explore the topic and other innovative and transformational opportunities with a global community of experts and peers at the Gartner IT Symposium/Xpo™ 2023 conference, taking place from 6-9 November 2023 in Barcelona, Spain.
