DeepSeek and Open-Source AI: Navigating the Path to Sustainable Monetization

In early 2025, Hangzhou DeepSeek Artificial Intelligence Basic Technology Research Co. Ltd. (DeepSeek), a Chinese artificial intelligence (AI) start-up, released a suite of open-source generative AI models that rivalled leading Western alternatives in performance, despite operating with significantly less capital and hardware infrastructure. Founded by former hedge fund manager Liang Wenfeng, DeepSeek quickly emerged as a disruptive force in the global AI landscape by championing open access to advanced foundation models. The company’s R1 model, launched at the start of the year, drove viral adoption across markets and outperformed expectations in both cost efficiency and user engagement. However, DeepSeek’s commitment to open-source ideals has created a critical strategic dilemma. Without clear monetization channels such as licensing fees or subscription models, the company faces mounting pressure to sustain its rapid growth and high-cost research and development (R&D) operations. At the same time, DeepSeek must navigate geopolitical risks, platform dependencies, and intensifying global competition, all while preserving the transparency and community goodwill that underpinned its early success.

The case places students in the role of Liang and his executive team as they assess how to translate technical momentum into financial sustainability. Students are challenged to evaluate the disruptiveness of DeepSeek as an open-source entrant and critically assess three primary monetization paths: commercial licensing, strategic partnerships, and value-added services. Each path presents distinct trade-offs between control, scalability, and long-term defensibility. The case also explores key challenges and strategic tensions that complicate monetization decisions. It prompts reflection on broader questions about the future of the AI industry, particularly how values such as openness and accessibility influence strategic choices in an increasingly competitive and regulated landscape.

For instructors teaching tech-savvy students in engineering, computer science, or related fields, an optional discussion extension is provided to explore the architectural foundations of DeepSeek’s AI models.