When users access SaaS tools through their own AI environments like Codex, they use their own AI model tokens, not the SaaS vendor's. This eliminates a huge cost center for SaaS companies, shifting their business model toward making their apps agent-friendly rather than paying for AI features.

OpenAI's model router is a strategic pivot to monetize its vast free user base. By routing high-value queries (e.g., shopping, legal advice) to powerful agentic models, OpenAI can take a cut of resulting transactions. This avoids intrusive ads while capturing value from commercial intent.

The current ecosystem of insecure, community-submitted AI agent skills is unsustainable. The likely monetization path is a trusted, centralized "app store" that vets skills for security, offers them via subscription, and takes a revenue share from developers.

Companies like Z.ai are not abandoning open source but using it strategically. They release lightweight models to attract developers and build a user base, while reserving their most powerful, agentic systems for proprietary, revenue-generating enterprise products, creating a clear monetization funnel.

Despite being open-source, leading Chinese AI firms are profitable. They generate hundreds of millions in revenue by selling managed services and API access, saving customers the complexity of self-hosting, GPU management, security, and deployment.

To maintain independence and trust, their public benchmarks are free and cannot be influenced by payments. The company generates revenue by selling detailed reports and insight subscriptions to enterprises, and by conducting private, custom benchmarking for AI companies, separating their public good from their commercial offerings.

The creator of OpenInspect highlights a key business model challenge: the agent orchestration layer is difficult to monetize. Value is captured by the underlying sandbox environment providers (e.g., E2B) and the foundational model companies (e.g., OpenAI), leaving the easily-replicated 'in-between' agent logic with little pricing power.

The nascent AI agent ecosystem lacks effective discovery mechanisms for third-party tools ('skills'). This creates an opportunity for curated marketplaces that help users find, vet, and even pay for high-quality, trustworthy agent capabilities, solving a key bottleneck to adoption.

AI21 exemplifies a winning AI business model: give away the foundational model (Jamba) to drive adoption, then monetize a proprietary orchestration layer (Maestro) that helps enterprises manage multiple models for cost and performance, capturing value higher up the stack.