Table of Contents
What an AI automation agency actually does
An AI automation agency identifies which parts of your business operations can be automated, builds the systems to do it, and (if they are worth hiring) maintains and improves those systems over time. They sit at the intersection of business operations consulting and technical implementation.
What they are not: a software vendor selling you a platform to build your own automations. If you are expected to do the building, you are buying a tool, not a service.
The three types of automation vendors
Platform vendors
Sell you a tool (Zapier, Make, HubSpot). You build the automations yourself. Works for in-house teams with technical resources. Not a service.
Build-and-forget agencies
Build your automations as a one-time project and hand them over. No ongoing support. Automations degrade as your business changes.
Managed AI agent agencies
Build, deploy, and maintain your automations on an ongoing basis. Automations improve over time. Agency is accountable for results.
For most SMEs, the managed AI agent model delivers the best outcomes because it aligns the agency's incentives with your results.
Questions to ask before you sign anything
Can you show me the automation working before I pay for it?
Do you maintain it after launch, or is it handed over to us?
How do you measure success and what metrics do you commit to?
What happens if the automation breaks or produces incorrect outputs?
Who owns the automations — us or you?
What does your intake and discovery process look like?
Can you share case studies with actual numbers from similar businesses?
How long until first results?
What happens if our business changes and the automation needs updating?
What does your ongoing relationship look like after launch?
Red flags that predict a failed engagement
Warning Signs
- No clear discovery before quoting
- Cannot show a working demo before signing
- Proposal full of technology names but no business outcomes
- No defined timeline or milestone structure
- Automation handed over at end with no ongoing support model
- No case studies or references
What a good proposal looks like
Problem definition
Clear articulation of the business problem being solved
Proposed automation architecture
Step-by-step breakdown of how the system will work
Integration list
All tools and platforms that will be connected
Timeline with milestones
Specific dates and deliverables at each stage
Defined success metrics
Baseline measurements and target outcomes
Pricing with clear scope
What is included and what costs extra
Support model post-launch
How ongoing maintenance and improvements work
Pricing models explained
Project-based
Fixed PriceFixed price for defined scope. Clear, predictable.
Risk: No incentive to maintain post-delivery.
Retainer
RecommendedMonthly fee for ongoing management. Best alignment with results.
Ask: What the retainer covers explicitly.
Revenue share
Performance-basedAgency takes a percentage of revenue generated. Strong incentive alignment.
Requires: Robust attribution tracking.
Platform + setup fee
DIY ModelYou pay for software plus a one-time build. Ongoing responsibility is yours.
Works for: In-house teams only.
How to evaluate results objectively
Framework for Success Measurement
Before you start, agree in writing on:
- The baseline metric
- The target metric
- The measurement method
- The review cadence
Without a baseline, there is no way to evaluate results. Any agency that resists establishing baselines is not confident in their outcomes.
See exactly what Converze does before you decide.
The intake is free. The AI maps your workflow, identifies your bottleneck, and introduces the agent that will handle it. You see a concrete plan with real numbers before we talk about price.