Delegate the mechanical "science" of innovation—data synthesis, pattern recognition, quantitative analysis—to AI. This frees up human innovators to focus on the irreplaceable "art" of innovation: providing the judgment, nuance, cultural context, and heart that machines lack.

Generative AI is a powerful tool for accelerating the production and refinement of creative work, but it cannot replace human taste or generate a truly compelling core idea. The most effective use of AI is as a partner to execute a pre-existing, human-driven concept, not as the source of the idea itself.

True creative mastery emerges from an unpredictable human process. AI can generate options quickly but bypasses this journey, losing the potential for inexplicable, last-minute genius that defines truly great work. It optimizes for speed at the cost of brilliance.

AI models operate in a 'probability space,' making predictions by interpolating from past data. True human creativity operates in a 'possibility space,' generating novel ideas that have no precedent and cannot be probabilistically calculated. This is why AI can't invent something truly new.

As AI agents eliminate the time and skill needed for technical execution, the primary constraint on output is no longer the ability to build, but the quality of ideas. Human value shifts entirely from execution to creative ideation, making it the key driver of progress.

Despite AI's capabilities, it lacks the full context necessary for nuanced business decisions. The most valuable work happens when people with diverse perspectives convene to solve problems, leveraging a collective understanding that AI cannot access. Technology should augment this, not replace it.

AI can generate hundreds of statistically novel ideas in seconds, but they lack context and feasibility. The bottleneck isn't a lack of ideas, but a lack of *good* ideas. Humans excel at filtering this volume through the lens of experience and strategic value, steering raw output toward a genuinely useful solution.

Citing the president of the Santa Fe Institute, investor James Anderson argues that current AI is the "opposite of intelligence." It excels at looking up information from a vast library of data, but it cannot think through problems from first principles. True breakthroughs will require a different architecture and a longer time horizon.

The tendency for generative AI to "hallucinate" or invent information, typically a major flaw, is beneficial during ideation. It produces unexpected and creative concepts that human teams, constrained by their own biases and experiences, might never consider, thus expanding the solution space.