Five Underappreciated Truths About the AI Economy: Learnings From DVC’s State Of AI Report

Thought Leaders Five Underappreciated Truths About the AI Economy: Learnings From DVC’s State Of AI Report Published July 30, 2026 By Marina Davidova, Co-founder & Managing Partner, DVC Add Unite.AI to your preferred sources on Google At DVC, we’ve spent a decade watching the AI market up close — backing companies and working closely with the portco founders. This year, we decided to share the framework we’ve built with the world. This is how the State of AI Report was born: a living, continuously updated analysis of the AI economy across every layer, from silicon and energy to foundation models and applications. We update it with AI and review it personally — because in a market that moves this fast, a static annual snapshot is outdated the moment it’s published.Here are 5 findings both founders and investors should pay attention to.1. The Rules of Scale Have Been RewrittenNever in the history of technology have five-person teams routinely challenged $100 billion incumbents and won, disrupting their business models and offering the market expansion to $500B. Perplexity added 50% to $300M ARR in a month. Higgsfield went from zero to $300M in a year. Cursor hit $500M ARR in June 2025, $1B by fall, $2B by February 2026. None of them built their own factories. They competed at the application layer, expanding their markets tenfold while infrastructure scaled beneath them.2. The SaaS Playbook Doesn’t Apply HereTraditional SaaS valuation rests on one premise: margins of 70–80% that compound as the business scales. AI companies don’t work like this. Even the best ones pay what we call the “inference tax” — 40 to 60 cents of every dollar goes to compute, foundational models, cloud, silicon, and energy. OpenAI’s gross margin in H1 2025 was ~42%. Anthropic’s ~40%. Cursor ~35%. GitHub Copilot is currently 0–15%, subsidized for strategic lock-in.AI companies are closer to industrial manufacturers than to software vendors. Jensen Huang said it best: think of a datacenter as a factory — electrons go in, intelligence comes out. Your “AI agent for banking AML and compliance” isn’t SaaS. It’s a silverware customization service. The spoons are mass-produced in a factory, from sheet metal, sourced from mills that process ore from mines.Does this mean paying SaaS multiples is wrong? No. But let’s be honest: we’re paying for extraordinary revenue growth potential, not long-term terminal value. That’s a different bet. We should make it knowingly.3. Foundation models are becoming a commodity — faster than anyone expectedSixteen companies now have frontier-capable models. GPT-4-class performance cost $37.50 per million tokens in 2023. By 2025: $0.14. DeepSeek V3 brought it to $0.006 — a 99.6% decline in two years, and 6,000× cheaper than where this started.When the model layer becomes a commodity, the advantage shifts to whoever controls access to the user. Distribution, workflow depth, and interface ownership — not model quality — will determine who defines the next decade. The model quality won’t be that important.4. The Business Model Is Still Being InventedThere are currently three ways to make money in AI, and none of them is obviously right. You can charge per token — simple, scalable, and racing toward zero; prices dropped 10× in 18 m