Fixed-Price vs Time-and-Materials for AI Projects: How to Choose

The choice between fixed-price and time-and-materials (T&M) is one of the most consequential decisions you'll make at the start of an AI project. Each model allocates risk differently — and for AI projects specifically, where scope can be hard to define upfront, the choice requires careful thought.

Fixed-Price: When It Works for AI

Fixed-price works best when the scope is bounded and the success criteria are measurable. "Build a RAG system over our 10,000-page knowledge base that answers employee questions with source attribution, achieving 85%+ retrieval accuracy on our benchmark query set" is fixable. "Build AI for our business" is not. The key is that both parties agree in writing on what done looks like — before any code is written.

Time-and-Materials: When It Works for AI

T&M is appropriate during discovery and exploration phases — when you genuinely don't know what the solution looks like yet. It's also appropriate for ongoing AI operations and improvement work that doesn't have a natural completion point. The trade-off: you absorb scope risk. If the problem turns out to be harder than expected, you pay for the extra time.

Milestone-Gated: The Best of Both

Sophisticated AI firms offer a hybrid: fixed-price per milestone. You agree on what each phase will deliver, what it costs, and when payment is due. You hold approval rights at each milestone gate. This gives you the cost predictability of fixed-price with the flexibility to change direction between milestones. It's the model Kovil AI uses for all project-based engagements.