As businesses anticipate a future where enhanced marketing fosters stronger, more meaningful relationships between customers and brands, successful CMOs utilize AI in these ways.
Foster innovation and tailor experiences using generative AI
The capability to develop original content, synthetic data, models of physical objects, and code to enhance customer engagement response time is offering groundbreaking innovation opportunities in marketing.
Generative AI learns from existing materials to create new, realistic artifacts that mirror the traits of the training data without duplicating them. It generates new content forms such as video, narratives, speech, training data, and product designs. It can produce within the same modality (e.g., picture to picture) or across different modalities (e.g., picture to narrative), creating entirely unique artifacts or enhancing existing ones.
Generative AI promises a new level of creativity and enriched experiences through two main approaches:
Augmented generative AI enhances current creative processes by working alongside human operators, who influence the AI's generation behavior through reinforcement, such as by indicating "more like this" or "less like this" for generated elements.
Generative AI automates the creation of unique artifacts in large quantities, requiring minimal human input aside from defining the production parameters. For instance, humans establish brand guidelines for automated copy creation.
Generative AI is rapidly becoming more prevalent in marketing, with different degrees of practical influence.
AI applications in marketing specifically include the following:
Text generators are capable of producing marketing content, news articles, and job listings. Additionally, short-form content, such as crafting subject lines, can facilitate A/B testing.
Logos can be created using generated images; human images can be produced for modeling purposes; and images can be modified to show various poses, aging, and numerous other features.
Video generated by AI can display event highlights, immersive product experiences, and multilingual versions.
Content artifacts can be combined to enhance ads and support personalization.
Computer vision (CV) can enhance image quality, generate digital twins, and produce deep fakes.
Virtual influencers and avatars can interact with customers on social media and within the metaverse, offering customer support.
Considerations for Using Generative AI Content
Most AI applications still need human intervention to establish parameters for their learning and to ensure governance. Marketing leaders should contemplate the effects on their teams, especially concerning data and asset management, skill enhancement, and capacity planning.
With the promise of Ai Generative Content come inherent risks. Concerns regarding ethics, intellectual property, and bias are just some of the potential challenges. To prevent these and other unintended outcomes, consider the following:
AI will not advance to the point of self-regulation — thus, humans will have to regulate it.
The optimal moment to pinpoint relevant risks to your organization is prior to implementing AI.
Utilizing AI responsibly is a collaborative endeavor that demands a base of transparency, trust, and security, enabling your organization to harness AI's advantages while minimizing risks.
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