What is best practice and use cases of AI within marketing?

AI in marketing is best implemented by targeting narrow, well-defined workflows that leverage existing data, such as automating repetitive tasks to boost productivity by an average of 30% and freeing teams for strategic work [3]. Start with an audit of current exposure to shifts like the "search revolution" from SEO to GEO (Generative Engine Optimization), and adapt lead-generation visibility accordingly [2]. High-impact strategies emphasize readiness in data, infrastructure, and culture, applying techniques like generative AI, predictive analytics, natural language processing (NLP), and machine learning to data-heavy marketing processes for efficiency and growth [8]. For successful adoption, prioritize projects testable with small user groups, clear training paths, and economical cloud-based solutions, especially for SMEs [4][6]. Key use cases include enhancing consumer interactions and response times through AI-driven customer support, automating marketing tasks to improve overall productivity, and reshaping purchasing decisions amid evolving search behaviors [1][2][3].