How AI Is Reshaping the Software Development Life Cycle
AI was a massive driver of change in 2024. This year, organizations that are already incorporating AI into their processes will start to see the return on their investments, enabling them to refine and refocus their use of AI in software development.
GitLab’s research found that 78% of organizations are either actively using AI in their development processes or plan to implement it within the next two years. These use cases are likely disparate, reactive applications of AI. In 2025, the most strategic organizations will evolve their AI strategy by adding AI agents and assistants across their entire software supply chains and driving efficiencies in platform engineering.
The trend toward increased productivity in development will result in a greater focus on return on investment (ROI) and quantifying AI’s impact. Let’s walk through three trends shaping software development.
AI Agents Will Drive Change
AI agents are poised to revolutionize the software supply chain by automating and optimizing processes, from continuous integration to continuous deployment. This shift from piecemeal AI applications into fully integrated AI-powered workflows will initially gain traction in open source ecosystems like software libraries, where AI agents will likely be built and shared with the community.
As developers and organizations witness the benefits of AI-driven automation in open source projects, we can expect a rapid expansion into commercial enterprise solutions. Internal development teams and platform engineers will increasingly have the task of building, extending and integrating AI agents across the entire software supply chain.
AI Will Revolutionize How Platform Engineers Work
With the proliferation of pattern recognition, AI can reduce the friction of automating software releases into production. Teams can use AI to further platform engineering goals such as codifying training, policies and checks and balances, identifying areas for improvement, and surfacing best practices.
The movement to further embed AI in platform engineering will lead to a rise in application development driven by AI-assisted tools, enabling organizations to meet specific needs more efficiently. By creating reusable building blocks that encapsulate common functionalities for software delivery, platform engineers will help empower nontechnical team members to easily assemble delivery pipelines using intuitive low-code techniques for testing, environment management and release orchestration.
Focus on Cloud Cost Optimization and Data Governance
As budgets tighten in 2025, organizations will intensify their scrutiny of operational efficiencies and cloud spending. Instead of prioritizing development speed, companies will focus on ROI and total cost of ownership (TCO), conducting granular cost assessments at the application level. We will likely see a rise in the practice of FinOps, which serves as a liaison between finance, product and engineering teams. FinOps provides a framework for evaluating issues, identifying new efficiency opportunities and building remediation plans.
Organizations will compare an application’s revenue to development and maintenance costs, potentially accelerating the shift to on-premises or hybrid environments. The complexity and expense of cloud native modernization, as well as increasing data privacy and AI regulations will drive a renewed emphasis on data control and governance. By aligning technical operations with financial objectives, organizations can ensure they receive the highest return on their cloud infrastructure and software development investments.
Wrapping Up
This year, the most competitive organizations will be those that take a strategic and intentional approach to AI. By incorporating frameworks to optimize cloud spending, using AI to drive efficiencies in the software supply chain and using AI to uplevel platform engineering efforts, they will see massive transformations and opportunities for innovation, both within individual organizations and across the broader technology ecosystem.
