The new generation of AI automates workflows, acting as "teammates" for employees. This creates entirely new, greenfield markets focused on productivity gains for every individual, representing a TAM potentially 10x larger than the previous SaaS era, which focused on replacing existing systems of record.

While current AI tools focus on individual productivity (e.g., coding faster), the real breakthrough will come from systems that improve organizational productivity. The next wave of AI will focus on how large teams of humans and AI agents coordinate on complex projects, a fundamentally different challenge than simply making one person faster.

Rather than radically restructuring teams around AI, the immediate future involves individuals augmenting their personal workflows with AI assistants. This "cyborg model" treats AI as a personal tool for finishing tasks, fixing errors, and handling busy work, creating a hybrid where each person learns to use AI to enhance their own abilities.

The true market opportunity for AI is not merely replacing existing software but automating human labor. This reframes the total addressable market (TAM) from the ~$400 billion global software industry to the $13 trillion US-only labor market, representing a thirty-fold increase in potential value.

Adding a chat interface or minor "AI features" won't unlock new budget. To capture significant AI spend, your product must either replace human headcount, make users dramatically more effective, or provide an order-of-magnitude productivity increase.

The new AI technology landscape is a layered 'Collaborative Intelligence Stack.' It starts with hardware and models but culminates in 'AI teammates'—agentic AIs that augment human workers. The largest future value lies in this top layer, which could capture 10-20% of the $30 trillion global knowledge worker spend.

The next frontier for AI isn't just personal assistants but "teammates" that understand an entire team's dynamics, projects, and shared data. This shifts the focus from single-user interactions to collaborative intelligence by building a knowledge graph connecting people and their work.

The transition from AI as a productivity tool (co-pilot) to an autonomous agent integrated into team workflows represents a quantum leap in value creation. This shift from efficiency enhancement to completing material tasks independently is where massive revenue opportunities lie.

Elad Gil argues that the total addressable market for AI companies is not limited to traditional seat-based software pricing. Instead, it encompasses the multi-trillion dollar human labor market that AI can augment or automate.