Traditional marketing involves planning, launching, and then learning. AI enables an "outcome-based" model where marketers define the desired result first (e.g., profit, brand lift) and technology works backward to achieve it, aligning marketing more closely with finance and the CEO.
Websites are often structured around company departments, creating a static, unhelpful user experience. By breaking content into "atoms" or Lego-like blocks, AI can dynamically reassemble it to match a specific user's needs, shifting from a company-centric to a customer-centric digital experience.
Marketers are tempted to create simple, agent-first content to rank in AI models. However, this often alienates human users who prefer rich, multimodal content (video, audio, visuals). The key is to serve both audiences without sacrificing the human experience for purely algorithmic optimization.
Senior leaders feel pressure to be AI experts, but everyone is learning. The effective response isn't creating slide decks, but joining teams in bootcamps to use the tools and learn together. The new leadership craft is about asking better questions, not pretending to have all the answers.
Just as photography forced painters to evolve into new forms like Impressionism, the flood of AI content is training consumers to recognize generic output. This raises the standard for quality and places a higher premium on creativity that demonstrates a unique, human touch and even imperfection.
True personalization goes beyond semantic relevance. It now includes allowing the user to choose their preferred consumption format in real-time—be it audio, a visual story, or text. This "dynamic multimodality," previously too costly, is now possible with advanced AI models like Gemini.
The "garbage in, garbage out" principle for AI data is well-known. However, there's a second, equally important input: content. Focusing solely on data quality while neglecting the creativity and human-centric relevance of the content itself will lead to suboptimal AI marketing outcomes.
Contrary to social media posturing, the application of AI in marketing is not a solved problem. Leaders should be comfortable with the current ambiguity and messiness, recognizing that everyone is still learning how to infuse AI with essential human qualities like taste and judgment.