Overview

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AI is transforming how marketers research audiences, plan campaigns, and evaluate tools, but using it effectively requires more than generating outputs. In Leverage AI in Marketing, you’ll learn how to turn AI-generated data into actionable marketing strategy. You’ll begin by analyzing AI-generated market insights, including trend data, competitor positioning, and audience sentiment. You’ll learn how to evaluate outputs using a practical framework (recency, source reliability, audience specificity, and strategic fit) so you can separate useful insights from noise. Next, you’ll build a structured approach to AI-assisted research. You’ll define research questions, match tools to specific needs, and run targeted queries that produce relevant outputs. You’ll then synthesize findings into campaign-ready summaries that directly inform marketing decisions. Finally, you’ll evaluate AI tools for real-world adoption. Using a five-part framework (capability, compliance, integration, reliability, and cost), you’ll compare tools and make defensible recommendations for your marketing tech stack. This course is designed for marketers, strategists, and marketing operations professionals who want to use AI with clarity and confidence, not just speed.

Syllabus

AI Strategy: Analyzing Market Insights

AI tools can surface market research at a speed and scale no human team could match. But volume of output is not the same as quality of insight. This module focuses on developing the judgment to tell the difference. You will explore how AI tools generate trend data, competitor positioning, and audience sentiment, and learn a practical framework for evaluating whether any given output is reliable and relevant enough to shape a campaign. By the end of this module, you will be able to confidently assess AI-generated market research before it influences your strategy.

AI Strategy: Research and Application

Having reliable AI-generated insights is only useful if you have a process for turning them into campaign strategy. Many marketing teams use AI research tools reactively, opening a platform and seeing what comes up rather than building research around the questions a campaign actually needs answered. This module introduces a structured approach to AI-assisted research that starts with clear research questions, matches tools to question types, and synthesizes findings into a campaign-ready summary. By the end of this module, you will be able to run a structured AI research session from brief to output and produce findings that translate directly into campaign strategy.

AI Strategy: Evaluating Tools

Not every AI tool that promises to transform your marketing workflow actually will. Choosing the right tool for your tech stack requires more than a compelling vendor demo. It requires a structured evaluation process that tests each tool against the criteria that matter most in your specific environment: capability, compliance, integration, reliability, and cost. This module gives you a practical framework for making AI tool adoption decisions that are defensible, sustainable, and aligned with your actual workflow needs. By the end of this module, you will be able to evaluate AI tools systematically and produce a clear, criteria-based recommendation for any marketing use case.