What is Generative AI?
Generative AI refers to artificial intelligence systems that create new content — text, images, audio, video, code, and 3D models — rather than simply analyzing or classifying existing content.
Generative AI refers to artificial intelligence systems that create new content — text, images, audio, video, code, and 3D models — rather than simply analyzing or classifying existing content. It represents a fundamental shift in computing from analysis to creation.
Key generative AI modalities: text generation (GPT-4, Claude, Gemini), image generation (DALL-E, Midjourney, Stable Diffusion), code generation (GitHub Copilot, Cursor), audio generation (ElevenLabs, Suno), video generation (Sora, Runway), and 3D model generation.
The economics of generative AI are fundamentally different from traditional software. Traditional software has near-zero marginal cost per user. Generative AI has significant marginal cost per query — every generated output costs compute. This is what Richard Ewing calls the Cost of Predictivity.
In 2026, generative AI has moved from novelty to production infrastructure. Companies are using it for customer support, content creation, code generation, design, data analysis, and decision support. The winners are organizations that understand the unit economics — cost per useful output — not just the technology.
Why It Matters
Generative AI is the most transformative technology of the decade, but its variable cost structure breaks traditional software economics. Understanding generative AI unit economics is essential for building sustainable AI features.
Frequently Asked Questions
What is generative AI?
Generative AI creates new content (text, images, code, audio, video) rather than just analyzing existing content. It powers chatbots, code assistants, image generators, and creative tools.
How much does generative AI cost?
Costs vary by modality: text generation $0.001-0.10/query, image generation $0.02-0.20/image, code generation $0.01-0.05/completion. Use the AUEB at richardewing.io/tools/aueb to model your specific costs.
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Richard Ewing is a Product Economist and AI Capital Auditor. He helps companies translate technical complexity into financial clarity.
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