AI doesn't disrupt randomly. It follows predictable patterns that create equally predictable opportunities.
The Task Decomposition Pattern
AI excels at specific tasks but struggles with job complexity. Understanding task decomposition reveals where opportunities concentrate.
Marcus analyzed job decomposition: - Lawyer: Document review (automated) + Strategy (human) + Relationship (human) - Accountant: Calculation (automated) + Judgment (human) + Advisory (human) - Designer: Generation (automated) + Taste (human) + Vision (human) - Writer: Drafting (automated) + Voice (human) + Insight (human)
He built businesses at the human-AI intersection, where automated efficiency met irreplaceable human value.
The Capability Ladder Pattern
AI climbs capability ladders predictably. Today's human-only tasks become tomorrow's AI capabilities, but new human-only rungs appear above.
Jennifer tracked capability progression: - 1990s: Calculation automated → Humans moved to analysis - 2000s: Analysis automated → Humans moved to synthesis - 2010s: Synthesis automated → Humans moved to creativity - 2020s: Basic creativity automated → Humans moved to wisdom - 2030s: Pattern continues upward...
She positioned herself on future rungs, developing capabilities AI wouldn't reach for years.
The Trust Gap Pattern
AI capabilities often exceed human trust. This gap creates massive opportunities for trust bridge builders.
David identified trust gaps: - Medical AI: Accurate diagnosis but patients want human doctors - Financial AI: Better predictions but clients want human advisors - Legal AI: Comprehensive research but parties want human counsel - Educational AI: Personalized learning but students want human mentors
His businesses bridged these gaps, using AI capabilities while providing human trust.