Creativity and content production are in the midst of a transformation driven by changing consumption patterns, the proliferation of digital media channels, the rapid growth of video-centric advertising, rising consumer expectations for relevance, and the democratization of content creation. The pace of evolution is rapidly accelerating as use cases for artificial intelligence (AI) continue to expand across the creative and content lifecycle. There are significant barriers to these advances as enterprises grapple with siloed scope of work and decision-making, fragmented content creation environments, and inherent risks in leveraging generative AI, including: Regulatory uncertainty Unclear cost and resource concentration Potential bias Trust in AI-generated content is limited Variability in quality and consistency Brands and agencies will overcome these challenges through enterprise change management, a structured approach to testing and scaling AI use, and leveraging the right internal and external resources that can provide creative production and content creation strategy, governance, data, and insights. While machine learning has been ingrained in the marketing world for years as part of activation, optimization, and measurement, generative artificial intelligence (GenAI) is the next innovation frontier. GenAI will be a major driver of automation and efficiency, especially in repetitive tasks. Despite regulatory uncertainty and increasingly visible carbon impacts, marketers will rapidly accelerate investments in AI use cases. As demonstrated throughout 2023, they will manage risks carefully. Managing the growing complexity in the content creation space requires a measurement-driven approach and unbiased third-party production support. AI cannot (and will not) replace creativity. Global spending on creative production and content creation is expected to grow rapidly, reaching $144.1 billion by 2026, almost doubling from $73.5 billion in 2020. |
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