How much does AI implementation cost?

AI implementation cost breaks down into three main buckets: discovery and scoping, build and integration, and ongoing maintenance. Understanding each helps you budget accurately and compare quotes from vendors.

Cost Ranges by Project Scope

• Single workflow automation -- $25,000-$75,000. One process (data entry, document processing, intake routing) with clean, structured data and no legacy system integration. Typical timeline: 6-10 weeks.
• Multi-workflow automation -- $75,000-$150,000. Three to five interconnected processes, moderate data cleanup required, integration with one or two existing tools (CRM, ERP, billing). Timeline: 3-5 months.
• Enterprise AI rollout -- $150,000-$300,000+. Department-wide transformation, legacy system integration or replacement, custom model fine-tuning, compliance requirements. Timeline: 6-12 months.

What Drives Cost Up

• Messy or siloed data that must be cleaned and normalized before AI can be trained on it
• Legacy software with no API -- requires custom middleware or replacement
• Regulated industries (healthcare, finance, government) requiring compliance documentation
• On-premises deployment vs. cloud -- on-prem adds 20-40% to infrastructure cost

AI Audit as a Cost Control Tool

The most effective way to control AI implementation cost is to start with a structured AI workflow audit before any development begins. An audit produces a written scope, identifies which processes have the highest ROI, and surfaces data readiness issues that inflate project cost when discovered mid-build. Code and Trust's AI Audit is the starting point for every implementation we deliver.