The discussion in 2023 regarding marketing technology trends is primarily centred around generative AI. We shed light on how organisations are investing in generative AI and its perceived value.

Key points from our research:

  • Generative AI Adoption: A significant number of marketers are embracing generative AI. About 32% of marketers indicate that their organisations are already using generative AI tools, and an additional 43% are actively considering its implementation
  • Potential Economic Impact: Generative AI holds substantial economic potential. McKinsey estimates that it could contribute between $2.6 trillion to $4.4 trillion to the global economy annually. This value is distributed across customer operations, marketing and sales, software engineering, and research and development (R&D)
  • Top Use Cases: The primary applications of generative AI, as perceived by marketers, are in written content creation and copywriting. These tools assist in automating formulaic and repetitive marketing tasks, thereby enhancing productivity and allowing marketers to focus on more complex and creative responsibilities
  • Specific Use Cases: Beyond written content, SEO keyword research and summarizing emails, meetings, and actions are the second and third most popular use cases for generative AI. These applications emphasize the technology's ability to streamline repetitive tasks
  • Value and Uncertainty: Marketers recognise the potential of generative AI, viewing it as both an opportunity and a potential threat. It offers productivity gains and the ability to deliver more relevant messages, but there is still some uncertainty about its long-term impact
  • Human-AI Collaboration: While generative AI can automate various tasks, there is consensus that a human layer is essential for shaping narratives and ensuring content is effectively delivered

In summary, generative AI has become a focal point in marketing discussions, with a significant number of marketers already using or considering its adoption. The technology is primarily leveraged for automating written content creation and other repetitive tasks, offering both productivity gains and some challenges, and emphasizing the importance of human-AI collaboration.


marketing   AI  

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