In a bid to forecast tech trends for 2025, The New Stack’s editors posed 14 key questions to over 120 industry experts. The resulting insights reveal critical developments in open source, AI use, and IT infrastructure. Key findings show that while security and maintainers’ time pose significant risks to open source, experts anticipate a decrease in unmaintained components due to better practices. Additionally, the future of AI tools remains uncertain, with concerns about the abandonment of many internal projects. As for software testing, developers will likely maintain their current manual testing time, stressing the ongoing need for oversight. Overall, mixed opinions exist on the migration to public vs. private clouds, indicating diverse strategies among enterprises.
As we look forward to 2025, The New Stack has conducted extensive research to understand the future of technology in the open-source landscape, AI development, and IT infrastructure. In this article, we’ll explore key insights from industry experts that reveal potential trends and challenges on the horizon.
Top Takeaways
Security and the time of maintainers are significant concerns for open-source software. With the rise of new tools to automate dependency management, we anticipate a decline in unmaintained components. Experts suggest that the transition to more automated processes will lead to an approximate reduction of 5-10% in outdated open-source components.
Another pressing issue is the competition for AI stacks. There is no clear consensus on whether large platform companies will dominate this space. Various predictions indicate that specialized companies could increasingly challenge these big players.
Also noteworthy is the expectation that many internal AI agent projects may be abandoned by the end of 2025 due to shifting priorities and the rise of ready-made solutions. There are concerns that developers will face challenges related to AI-generated code, particularly around code quality and integration into existing workflows.
Open Source and Software Security
Many experts emphasize that improving software security will be a priority in the coming years. Increased awareness of software supply chain security, as highlighted by notable incidents like Log4Shell, will likely drive organizations to prioritize maintaining their dependencies more effectively.
The increasing adoption of automation tools will enable teams to manage their dependencies better, fostering a healthier ecosystem for open-source technologies.
AI’s Role in Development
AI assistance in coding is set to transform developer workflows. However, developers will likely spend similar amounts of time on manual testing due to the complexities introduced by AI-generated code. Experts suggest that while AI tools can improve efficiency, they may not significantly reduce the time spent on manual checks.
Concerns are also raised about less experienced developers relying on AI without sufficient skills to identify errors, potentially leading to quality issues in the produced code.
Cloud Migration Trends
When considering cloud environments, experts suggest that migration to public clouds will continue to outpace movements toward private or on-premises clouds. Factors such as cost-effectiveness and the quest for flexibility in IT spending are vital components influencing these decisions.
Some organizations may find that public clouds do not always provide the necessary cost benefits, leading to a nuanced approach where hybrid models become increasingly attractive.
Conclusion
The insights gathered from experts indicate a landscape rich with change and adaptation. As organizations navigate the evolving realms of open-source software, AI development, and cloud infrastructure, they will face both challenges and opportunities. Monitoring these trends closely will be essential as they determine the tools and strategies that will shape the next few years in technology.
Tags: Open Source, AI Development, Cloud Migration, Software Security, IT Infrastructure.
What is AI-Assisted Coding?
AI-assisted coding helps programmers by using smart tools to suggest code or automate tasks. This makes coding faster and easier.
How will open source contribute to AI development?
Open-source projects allow everyone to contribute to AI improvements. This helps share knowledge and speeds up innovation in AI technologies.
Can AI replace programmers completely?
AI can’t fully replace programmers. It helps them with tasks, but human creativity and problem-solving are still very important.
What are some examples of AI tools for coding?
Some popular AI tools include GitHub Copilot, TabNine, and Kite. These programs suggest code snippets and make coding more efficient.
How can developers benefit from using AI tools?
Developers can save time, reduce errors, and learn new coding techniques by using AI tools. This leads to better software and more enjoyable coding experiences.