- Developers shift from loyalty to flexibility as OpenAI leads, but DeepSeek gains ground fast
- Microsoft struggles for developer mindshare with only a 10% adoption rate
- AI integration gets leaner as teams drop formal structures and focus on usable tools
OpenAI has been dominating the LLM space for some time, and remains the leading choice for many developers, but market dynamics and loyalty seem to be shifting, new research has claimed.
A survey by Vercel of 656 app builders found 87% use OpenAI’s models and 83% rely on its inference APIs. However, developers now use an average of two providers, and 60% have changed vendors within the last six months – raising questions about their loyalty.
DeepSeek is now used by nearly a third of businesses (29%), while Microsoft’s LLMs, by contrast, appears to be struggling, with only 10% of respondents report using the latter, and 9 out of 10 developers do not consider it a viable option.
“AI is dissolving the boundaries between roles. We’re seeing new product designers blend UX, UI, and code in one creative flow – thanks to tools like Vercel, v0, Uizard, and Cursor. Whether junior or senior leader, anyone can now build, test, and ship ideas independently – and that’s not just efficient, it’s liberating,” said Nicolas Le Pallec, CTO, EMEA – AKQA.
AI now builds around clear use cases, with developers prioritizing tools – not teams. Forty-five percent of respondents said they have no dedicated AI team, while 57% reported no specific AI leadership structure. Instead, success with AI depends on clear priorities and the right tools.
“By embracing cutting-edge AI technologies, we’re empowering our teams to work smarter and faster,” said Dr. Jan Ittner of BCG X, echoing the sentiment that an AI writer or developer tool can be more valuable than another hire.
Product AI features are now a priority for 75% of customer-facing apps, while only 39% still include traditional support chatbots. Website personalization remains underutilized at 27%, indicating room for future innovation.
Cost control is also a major priority. Over 70% of developers manually test their models, spending under $1,000 monthly – showing how much can be achieved on limited budgets. To cut costs, only 14% train their models, while 60% instead use retrieval-augmented generation (RAG) and vector databases.
The focus on tools stems from a perceived “overhype” around AI, with an average rating of 6.4 out of 10. Yet developers gave a 7.7 out of 10 when asked if AI will transform their industries in the next 12 months.
In a shifting field where speed, precision, and adaptability matter more than scale, the best LLM for coding isn’t fixed – it’s the one that solves today’s problems while keeping tomorrow’s door open.
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