Agent-based pricing allows companies to charge based on the work done by AI agents, which can replace a significant portion of traditional sales development roles.

The pricing model for AI services is evolving; companies might pay for successful outcomes, qualified leads, or resource utilization, reflecting a shift in how value is perceived in AI-driven businesses.

Pricing strategies for AI agents can vary; if the service is used by humans, it may follow a per-user pricing model, while machine-to-machine services might adopt usage-based pricing.

AI companies should avoid charging as a tool, as it limits their budget and potential for growth; instead, they should focus on the value delivered by their agents.

The mission behind Paid is to provide AI companies with the tools they need to manage pricing and understand their business fundamentals better, as traditional SaaS pricing models don't work for AI businesses, which require new approaches like outcome-based and agent-based pricing.

The potential for AI in sales is vast, as a significant portion of sales representatives' time is spent on non-customer-facing tasks.

The pricing model for AI tools is shifting towards usage-based pricing, making it easier for companies to justify ROI and shorten sales cycles.

The marketing narrative around agents often suggests they can replace human workers, which can lead to inflated pricing models for AI software.

Companies that sell AI solutions to enterprises can command higher budgets when they position themselves as replacements for traditional roles, like customer support or analytics teams.