So far you've been learning about text-based GenAI, but marketing AI has been advancing at a very rapid speed. But how do marketers actually use it?
There are two main approaches: traditional campaign pipelines and newer direct-generation models. Each has distinct advantages and limitations.
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Have you noticed how long traditional marketing campaigns take from concept to launch?
Traditional marketing uses a three-step pipeline: Research & Analysis, then Strategic Planning, then Content Creation & Execution.
Your brief → Research converts to insights → Strategic planning creates campaign framework → Content creation produces final materials.
This sequential approach works but creates natural delays at each step.
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Why can this feel inefficient in today's fast-moving market?
Direct-generation models take a different approach - they create marketing content directly from campaign briefs without extensive planning phases.
Think of it like an experienced marketer: you hear the objective, understand the audience, and create compelling content all in one fluid process.
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Which sounds more agile - translating everything through planning documents or going straight to execution?
The biggest advantage of direct generation is speed to market. Traditional pipelines add delays: research time + strategy development time + content creation time.
Direct AI can produce campaigns much faster because it eliminates the planning bottlenecks. Some AI systems create full campaigns in under an hour.
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How important is launch speed when you're responding to trending topics or competitor moves?
Direct-generation models also preserve creative qualities like brand voice, emotional tone, and audience connection that get diluted through multiple planning stages.
Traditional processes often produce generic content because insights get filtered through multiple stakeholders without creative context.
