Table 2.

Description of barriers

CodeBarrierDescription
F1Data quality issuesIncomplete, inconsistent, or biased data undermining personalization accuracy
F2System integration issuesLack of interoperability between AI systems and legacy infrastructure
F3Change resistanceOrganizational reluctance to adopt or trust AI systems
F4Skill deficiencyShortage of AI-literate marketing professionals
F5Ethical concernsAlgorithmic bias, fairness, and manipulation concerns
F6ROI uncertaintyDifficulty in quantifying AI’s financial impact
F7Data privacy concernsLegal and consumer mistrust regarding personal data use
F8Limited awarenessLow perceived relevance or understanding of AI benefits
F9High costsSignificant implementation and maintenance expenditure
F10Infrastructure limitationsInsufficient computing, storage, and connectivity resources

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