AI Transformation Cost
How Much Does AITransformation Cost?
The honest answer depends on three things: scope, complexity, and how much internal lift your team provides.
What you get at each investment level
These ranges reflect real projects. Cheaper proposals often exclude the integration, training, and support that make AI systems work in production.
Single Process Automation
$15K–$50K
60–90 days
Best for
First AI project with a clear ROI target
One workflow automated end-to-end. You pick the process with the highest cost or the clearest ROI, we build and deploy the system, and you own it at the end of the engagement.
Includes
- ✓Discovery and workflow mapping
- ✓AI system design and build
- ✓Integration with existing tools
- ✓Team training and handoff
- ✓30-day post-launch support
Department-Level AI
$50K–$150K
90–180 days
Best for
Operations, finance, or customer service transformation
Multiple connected workflows in a single department. A finance team automates invoice processing, approval routing, and reconciliation reporting. An operations team automates scheduling, exception handling, and performance dashboards.
Includes
- ✓Everything in Single Process Automation
- ✓Multiple workflow builds with shared data layer
- ✓Department-level reporting and dashboards
- ✓Change management support
- ✓60-day post-launch support
Enterprise AI Program
$150K–$500K+
6–18 months
Best for
Companies making AI a core operational capability
Cross-functional, multi-phase program. AI embedded across operations, finance, and customer-facing workflows. Includes governance framework, training program, and ongoing advisory.
Includes
- ✓Everything in Department-Level AI
- ✓Cross-functional workflow integration
- ✓AI governance and data management framework
- ✓Org-wide training program
- ✓Ongoing advisory relationship
What drives the price
Five factors determine where your project lands in the range.
Data readiness
Clean, accessible data in usable formats is the biggest factor in project cost. Poor data quality adds weeks of prep work before any AI system goes live.
Integration complexity
Connecting AI to legacy systems, proprietary databases, or platforms with limited APIs takes more time and costs more than connecting to modern SaaS tools.
Number of workflows
Each additional workflow adds scope. A single focused workflow is faster and cheaper than five loosely connected ones.
Change management scope
The more staff affected by the new system, the more time needed for training, communication, and adoption support.
Training requirements
Highly regulated industries or workflows with strict compliance requirements add documentation, testing, and validation work.
What you should not pay for
These patterns show up in proposals from large consulting firms and small AI shops alike.
6-month discovery phases before any build starts. Discovery should take 2-4 weeks. If a firm wants 6 months to assess before they build anything, walk away.
Junior consultants at senior rates. Ask who will do the actual work and check their experience. Many large firms staff projects with analysts billing at partner rates.
Tools and systems you do not own after the engagement ends. You should leave every AI project with working code, documentation, and the ability to run the system without the vendor.
Vague deliverables and open-ended timelines. Every project should have a scope document with specific deliverables and a fixed end date.
How Dooder prices projects
Fixed-scope pricing
You know the cost before work starts. No open-ended retainers, no surprise overages.
Transparent deliverables
Every project has a scope document listing exactly what gets built and when it is done.
You own everything built
Code, models, and documentation all transfer to you at project close. No lock-in.
90-day delivery
Every project delivers a production system within 90 days of kickoff. We do not run 6-month discovery phases.
Related reading
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