AI Enablement
AI in your marketing, with people in charge
We find the marketing tasks where AI helps, decide where a person must approve, and document how the workflow runs.
01
The problem
AI projects go wrong when teams start with a tool instead of a clear problem, approved data and a person who owns the result.
Automation can amplify weak instructions, poor source material, and unclear decisions unless controls are designed into the workflow.
02
What we do
We rank possible uses by business value, data readiness, review effort, what could go wrong, and who will own them.
For each approved use, we write down the workflow, where people approve, how we check quality, and how we hand it over.
- 01
Bounded use case
Start with a specific decision or production bottleneck and define where AI assistance stops.
- 02
Human release gate
Assign review, approval, exception, and escalation responsibilities before output is used.
- 03
Evaluation plan
Document acceptable evidence, known failure modes, and the conditions for revision or rollback.
What it can include
- Use-case and workflow assessment
- Data and permission mapping
- Instruction and context design
- Human review and release gates
- Evaluation and failure-mode planning
- Operating documentation and handoff
How we work
Audit → Launch → Report and adjust
The same three steps on every service. Here is what each one means for AI Enablement.
Audit
Find what is holding results back
Review the business problem, current workflow, data permissions, failure cost, and who owns the result.
Launch
Set up and ship the work
Specify the assisted workflow, context, review gates, evaluation method, and handoff.
Report and adjust
Report and move effort to what works
Support controlled use, review exceptions and evidence, and update the instructions.
04
What you get
- Price
- Part of a monthly plan from $4,000/month. Each plan lists what ships every month. Compare plans
- How we measure it
- Document acceptable evidence, known failure modes, and the conditions for revision or rollback.
- Who approves the work
- Assign review, approval, exception, and escalation responsibilities before output is used.
05
Common questions
How do you choose an AI use case?
We assess the business problem, repetition, data availability, review burden, failure cost, and ownership before recommending a bounded intervention.
Do we need a dedicated technical team?
That depends on the approved use case, system access, data sensitivity, integration ownership, and support requirements. The diagnosis makes those dependencies explicit.
How is an AI-assisted workflow evaluated?
We define task-specific quality criteria, human review, exception logging, and business context before the workflow is relied upon.
Related expertise
More on AI Enablement
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ExploreNext step
Request an audit
In 20 minutes we look at your funnel and current channels, then tell you which plan fits.