The founder of Absurd, an AI video ad agency, explains their model of charging upwards of $30k per video. By handling the entire creative and distribution process as a service, they capture more value and avoid the commoditization and lower price points inherent in building a self-serve SaaS video editor.
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The largest advertisers on platforms like Meta launch over 10,000 new creatives a year, equating to more than 40 per workday. This massive scale of experimentation is manually impossible for most companies, creating a clear market need for AI platforms that automate and scale video production.
Upcoming tools like Sora automate the script-to-video workflow, commoditizing the technical production process. This forces creative agencies to evolve. Their value will no longer be in execution but in their ability to generate a high volume of brilliant, brand-aligned ideas and manage creative strategy.
For a true AI-native product, extremely high margins might indicate it isn't using enough AI, as inference has real costs. Founders should price for adoption, believing model costs will fall, and plan to build strong margins later through sophisticated, usage-based pricing tiers rather than optimizing prematurely.
The primary barrier to properly valuing creativity in advertising is the industry's reliance on a service-based, billable-hour model. This is a fundamental flaw that prevents creative work from being valued on its impact and outcome, unlike in the tech industry.
Traditional SaaS companies are trapped by their per-seat pricing model. Their own AI agents, if successful, would reduce the number of human seats needed, cannibalizing their core revenue. AI-native startups exploit this by using value-based pricing (e.g., tasks completed), aligning their success with customer automation goals.
Standard SaaS pricing fails for agentic products because high usage becomes a cost center. Avoid the trap of profiting from non-use. Instead, implement a hybrid model with a fixed base and usage-based overages, or, ideally, tie pricing directly to measurable outcomes generated by the AI.
The real economic value of generative video lies in advertising, not filmmaking. Unlike movies with finite consumption, there is unlimited demand for personalized, diverse ad content. This makes advertising a perfect fit for the technology's scalable content creation capabilities.
The dominant per-user-per-month SaaS business model is becoming obsolete for AI-native companies. The new standard is consumption or outcome-based pricing. Customers will pay for the specific task an AI completes or the value it generates, not for a seat license, fundamentally changing how software is sold.
To profitably scale a SaaS with paid ads (Meta, YouTube), you cannot rely on low-ticket monthly subscriptions. The customer acquisition cost will almost always be too high to be sustainable. You must have a high-ticket enterprise plan to ensure a positive return on ad spend from day one.
In a world where AI makes software cheap or free, the primary value shifts to specialized human expertise. Companies can monetize by using their software as a low-cost distribution channel to sell high-margin, high-ticket services that customers cannot easily replicate, like specialized security analysis.
