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Software and how it’s developed have changed permanently this year. AI has revolutionized software development, transforming it from a manual process of hand-coding machine-level instructions to a more automated approach.
In fact, 95% of global respondents from GitLab’s “2024 Global DevSecOps Report” said they currently use AI in the software development life cycle in some way or plan to use it. Developers will uncover even more use cases as the quality and output of AI coding tools improve.
However, while AI promises to simplify developers’ work, automate repetitive tasks and provide a return on business value, it’s not without trade-offs or existential concerns about application safety and career progression. Modern organizations are navigating new complexities while working to realize and measure business impact.
Here are three trends I anticipate we’ll see in the coming year.
We’ll see business leaders prioritize simplification and clarity in software development and innovation.
However, this simplification won’t take place overnight. Take AI coding assistants, for example. Developers will need time to adapt to these tools, and the tools themselves will require training. Once this is achieved, developers will experience a dramatic reduction in their workload.
Furthermore, developers will increasingly adopt unified platforms with a single data source to address complex digital infrastructures and unsecured software supply chains. This transformation is already underway. For example, Cube, a Netherlands-based software development company, built a real-time value stream dashboard that identifies roadblocks and slowdowns in a single pane of glass. By gaining visibility into what’s happening and when during the process, it can address issues more quickly and efficiently.
Finally, value stream management methodologies will revolutionize software delivery by enhancing transparency, security, productivity, efficiency and collaboration.
AI, once seen as a potential job threat, has evolved into a tool that empowers developers to focus on higher-level tasks. However, the increased reliance on AI-generated code necessitates addressing the AI skills gap, especially among junior developers.
According to GitLab’s report, 67% of organizations globally already automate part or all of their software development cycles. Developers can now turn their attention to innovative work that allows them to discover and learn new skills that will help expand their technical expertise and advance their career development.
To maintain this, organizations must focus on safeguarding the talent pipeline to ensure a sufficient number of senior developers have the skills to refine and correct AI-produced code. And in 2025, they’ll be doing just that.
AI systems with comprehensive access to and understanding of data across the entire software life cycle will become even more widespread.
The initial hype surrounding AI has passed, and in some cases, the technology has fallen short of initial expectations. Developers have benefitted from AI, leading to faster code production, but this has yet to translate directly into broader organizational value.
Current AI implementations often function in isolated pockets, leaving teams without a unified context. This siloed approach limits AI’s ability to deliver business value because it fails to connect the separate parts of the software delivery life cycle.
AI will become significantly more effective if applied to the entire software development life cycle. It can address developer-specific tasks and contribute to broader business goals in development contexts, like optimizing processes across departments. A more integrated approach will enable the creation of more intelligent and broadly capable AI tools for developers.
A clearly defined, organizationwide AI strategy is essential to optimize costs and maximize business outcomes.
Despite the challenges of cutting-edge development, the future of software development is bright. The industry’s focus on simplification and AI automation promises to revolutionize development processes and enhance efficiency. To fully realize this potential, organizations must invest in developing AI skills to maintain quality and drive innovation.
Organizations that prepare for these changes and implement a cohesive AI strategy will gain a competitive edge in 2025 and beyond.