As digital systems and AI erode consumer trust, people are hungry for authenticity. Companies that can establish and prove their trustworthiness will have a significant competitive advantage, as trust is now a scarce and powerful profit motive.
The guest argues that over 60% of what's labeled 'AI' is the opportunistic application of existing technology for profit. It's driven by classic capitalist motives like winning market share, rather than genuine, process-changing innovation.
A key advantage humans will retain over AI is the ability to translate rich, multi-sensory physical experiences—like touch, smell, and memory—into abstract thought and creative insight. This 'last mile of human experience' is not yet transferable to technology.
Companies primarily use AI for chores like writing emails. While efficient, this focus on automation without a parallel emphasis on creative problem-solving can lead to every brand sounding and looking the same, stifling true innovation.
AI models are trained on vast datasets of existing knowledge. Like a librarian who has read every book, their answers represent an average of what they have 'read.' This makes AI an aggregator of existing ideas, not a generator of truly novel, outlier concepts.
AI's success hinges on its application and the competencies built around it. Simply deploying AI tools without a strategy is like handing out magic markers and expecting art—most will go unused or be misused. The failure point is human strategy, not the tool itself.
Instead of using restrictive surveys, companies can find breakthrough innovations by using AI to analyze unstructured customer stories. Asking open-ended questions like 'Tell me about your experience' allows AI to identify latent needs and emotions that surveys completely miss.
After querying AI with your known questions, ask what important patterns exist in the data that you failed to ask about. This forces the AI to surface non-obvious connections, acting as a powerful check against your own functional fixedness and biases.