Generative AI Tool Selection Checklist
Tags: Frameworks
TL;DR
- A structured checklist to assess capabilities, integration, performance, data, viability, and cost
- Focuses on real use cases, acceptable error, and interoperability with DSPs/CRMs/CMS
Why it matters for HK marketers: It prevents costly missteps by aligning tool choice with goals, stacks, and governance.
Assessment framework
Objective
- Define use cases and acceptable error margins
- Identify end users (internal, agencies, consumers)
Capabilities
- Confirm support for specific needs (e.g., video creation, predictive analytics)
Ease of integration
- Check compatibility with DSPs, CRMs, CMS
- Assess interoperability/composability
Performance
- Validate effectiveness via benchmarks/metrics
Data considerations
- Review data types processed (e.g., copyrighted, PII/PHI)
- Confirm protections, transparency, and disclosures
Viability
- Ensure use case–audience fit and realism
Cost and scalability
- Analyze switching and resourcing costs, including tech and talent
So what for marketers
Run vendors through this checklist and require evidence for each section before committing budget.
Sources:- IAB_GenerativeAIPlaybook_January_26 (1).pdf
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