The march of open-source software (OSS) through the enterprise technology stack is expected to continue, driven by the rapid development of artificial intelligence (AI) and the emergence of transformative funding solutions that address sustainability concerns. According to venture investors, this shift in market preferences represents a significant opportunity to fund the next generation of OSS-based category leaders in enterprise software.

OSS has transformed from being merely a cheaper option to the superior choice for enterprise infrastructure, offering higher quality, stronger security, better privacy, unparalleled extensibility, and access to innovation compared to proprietary rivals. Today, 96% of all software relies on open source, and large enterprises are increasingly inclined to invest in OSS-based solutions to capitalize on these advantages.

The rise of open-source AI is a significant trend shaping the market. The rapid development of foundational large language models, related AI infrastructure, and their applications has ignited debates around the crucial AI challenges. Many of these issues, such as transparency, adaptability, and security, can be addressed through openness. A new cohort of open-source AI models, including Meta's Llama and Mistral AI, is now raising the tide and boosting the global AI ecosystem.

Open source is exceptionally well-positioned to address the demands of customizing AI to specific enterprise needs, whether by building tailored AI infrastructure, fine-tuning models on proprietary data sets, or building AI agents for specialized tasks. The future of AI is likely to be open, with new AI infrastructure companies emerging each month and the current top AI OSS projects developed by startups consisting of LangChain, LlamaIndex, Hugging Face, Dify, and Ollama.

The rise of open-source AI is also influencing and amplifying other open-source trends. AI is changing how software is built and consumed, with important consequences for open source. Historically, open source has thrived in developer-centric areas such as software development tools and infrastructure, including databases. However, over the past two decades, many enterprise suites like ERP and CRM have evolved into essential platforms as new application layers have been built on top of them.

Open source is actively capturing the modern enterprise infrastructure and has a strong chance to eventually disrupt closed-source ecosystems of legacy enterprise suite vendors with better alternatives. Examples include Odoo, an open-source ERP platform, which recently raised another funding round at a $5.3 billion valuation and challenges SAP's dominance in certain niches. New notable players are emerging in similar areas, such as Twenty, which offers an open-source enterprise CRM (alternative to Salesforce), Plane, which provides an open-source project management system (alternative to Jira and Asana), and Cal.com, which offers a scheduling platform (alternative to Calendly).

The rise of AI agents is accelerating this trend. To succeed at scale, these agents will require extensive customization and close integrations with internal enterprise data sources and workflows (as human employees have), driving the adoption of AI-native, adaptive, open-source business application platforms.

However, the increasing reliance on open source also raises concerns about software supply chain security. With the average software application now relying on over 500 open-source dependencies, software supply chain security has become a critical concern for enterprises. Many OSS projects are developed by unpaid enthusiasts who lack the resources for ongoing maintenance, leading to potential vulnerabilities. The adoption of AI coding tools, such as GitHub Copilot, will further accelerate code creation, increasing the overall code base and potentially worsening these security challenges.

To address these growing risks to IT infrastructure, enterprises will need to adopt next-gen tools that leverage both modern AI and OSS in software composition analysis, vulnerability detection, software bills of materials, alerting, observability, AIOps, and other areas of devops and devsecops. According to Gartner, the cost of software supply chain attacks is expected to rise from $46 billion in 2023 to $138 billion by 2031.

Sustainability remains one of the core challenges for the open-source ecosystem. While some projects can be commercialized, the majority of OSS cannot and therefore continues to rely on unsustainable, non-profit sources of funding. In the world of commercial OSS organizations, discussions about the evolution of open-source licenses are set to intensify. Pressured by large cloud vendors, probably a few more tech companies will shift to source-available and other licenses that are not OSI-approved.

For free community-driven OSS, a systemic, sustainable, and efficient funding model is still missing. This gap poses growing risks to the global software infrastructure. However, 2024 has introduced several promising ideas and experiments that may pave the way for viable solutions in 2025. One such initiative is the Open Source Pledge, which encourages companies to compensate OSS maintainers with at least $2,000 per full-time developer they employ. Another initiative involves index-based, programmatic funding to support the long tail of small but crucial OSS projects.

Finally, a potentially transformative solution for sustainable funding of OSS can be the open source endowment. It's a financing model that has sustained leading universities for centuries, and the global OSS community has a lot in common with them. In summary, 2025 promises to be an exciting year for the evolution of open source software, driven by the increasing and interlinked adoption of AI and OSS across all levels of the enterprise tech stack, alongside the next-gen commercial and non-profit solutions addressing OSS sustainability.