Deep|LLM: Enterprise AI Application Research (Vol.1) - Spend is Still Growing; Growth Is Shifting from Seats to APIs and Production Workflows

Over the past few months, enterprise adoption of AI has become one of the market’s central debates. From the coding-agent surge early this year to the tokenmaxxing discussion in May-June to the more recent open-source shock, whether—and when—enterprise AI can take the baton from coding and become the next growth engine for model vendors’ ARR is now one of the questions investors care about most. We have therefore launched a large-scale survey and will keep interviewing 10–20 experts a week and updating our conclusions, aiming to build as complete a picture as possible. In the first part of the survey, we interviewed 13 experts, covering key topics below:

• AI budgets and spending
• Open-source model usage
• AI penetration
• Tokenmaxxing or budgeting
• Headroom in AI cost optimization
• AI spending outlook and ROI
• New use cases

1. AI Budgets and Spending

The survey includes 12 enterprise samples plus 1 cross-client enterprise AI transformation consultant. The table below summarises each sample’s AI spend trajectory and budget expectations.

Enterprise AI spend is still growing, but the trajectories start to diverge in 2H26