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Gartner identifies the top 5 strategic technology trends in software engineering for 2024

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Gartner, Inc. announced the top five strategic technology trends in software engineering for 2024 and beyond. Analysts presented these findings during the Gartner Application Innovation & Business Solutions Summit, which is taking place here through today.

Meeting business objectives is one of their top three performance objectives for 65% of software engineering leaders, according to a Gartner survey of 300 software engineering and application development team managers in the U.S. and U.K in the fourth quarter of 2023. By investing in disruptive technologies, software engineering leaders can empower their teams to meet business objectives for productivity, sustainability and growth.

“The technology trends Gartner has identified are already helping early adopters to achieve business objectives, “said Joachim Herschmann, VP Analyst at Gartner. “These disruptive tools and practices enable software engineering teams to deliver high-quality, scalable AI-powered applications, while reducing toil and friction in the software development life cycle (SDLC), improving developer experience and productivity.”

The top five strategic technology trends for software engineering for 2024 are-

Software engineering intelligence

Software engineering intelligence platforms provide a unified, transparent view of engineering processes that helps leaders to understand and measure not only velocity and flow but also quality, organizational effectiveness and business value.

Gartner predicts by 2027, 50% of software engineering organisations will use software engineering intelligence platforms to measure and increase developer productivity, compared to 5% in 2024.

AI-augmented development

Software engineering leaders need a cost-effective way to help their teams build software faster. According to the Gartner survey, 58% of respondents said their organization is using or planning to use generative AI over the next 12 months to control or reduce costs.

AI-augmented development is the use of AI technologies, such as generative AI and machine learning, to aid software engineers in designing, coding and testing applications. AI-augmented development tools integrate with a software engineer’s development environment to produce application code, enable design-to-code transformation and enhance application testing capabilities.

“Investing in AI-augmented development will support software engineering leaders in boosting developer productivity and controlling costs and can also improve their teams’ ability to deliver more value,” said Herschmann.

Green software engineering

Green software engineering is the discipline of building software that is carbon-efficient and carbon-aware. Building green software involves making energy-efficient choices for architecture and design patterns, algorithms, data structures, programming languages, language runtimes and infrastructure.

Gartner predicts by 2027, 30% of large global enterprises will include software sustainability in their non-functional requirements, up from less than 10% in 2024.

The use of compute-heavy workloads increases an organization’s carbon footprint, and generative AI- enabled applications are especially energy-intensive, so implementing green software engineering will help organizations prioritize their sustainability objectives.

Platform engineering

Platform engineering reduces cognitive load for developers by offering underlying capabilities via internal developer portals and platforms that multiple product teams can use. These platforms provide a compelling “paved road” to software development, which saves time for developers and improves their job satisfaction.

Gartner predicts that by 2026, 80% of large software engineering organizations will establish platform engineering teams, up from 45% in 2022.

Cloud development environments
Cloud development environments provide remote, ready-to-use access to a cloud-hosted development environment with minimal effort for setup and configuration. This decoupling of the development workspace from the physical workstation enables a low-friction, consistent developer experience and faster developer onboarding.

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