Jensen declared the “ChatGPT moment of agentic AI has arrived.” This transition from chat to agents transforms the unit economics of compute — and reveals the real state of enterprise AI adoption.

The Agentic Inflection — Confirmed and Dollarized
Traditional chat: ~100-500 tokens per interaction. Agentic systems: hundreds of thousands of tokens per session, running for minutes to hours, spawning sub-agents. Each token is dollarized — inference performance equals revenue.
Named catalysts: Claude Code and Claude Cowork (Anthropic), OpenAI Codex/GPT-5.2, Cursor. In 2025, global AI inference revenue officially surpassed training revenue for the first time.
Token Economics — The New Currency

The 280x inference price collapse continues. But output tokens cost 4-10x more than input because generation is sequential. The energy variance is 75x between efficient and frontier models. A single agentic workflow consuming 100,000+ tokens at GPT-5 pricing costs $1.00+ per execution. At enterprise scale — millions daily — this creates a multi-billion-dollar inference economy.
The Enterprise Adoption Reality

What’s Working
- Code generation: 91% of enterprises use AI coding tools in production
- Customer service: Agents saving teams 40+ hours monthly
- Finance: Automated forecasting accelerating close by 30-50%
- Sales: 2-3x improvements in pipeline velocity
What’s Stalling
- The 95/5 divide: 95% of organizations getting zero return on GenAI investment
- Shadow AI: 90% of employees use personal AI tools; only 40% of companies have official subscriptions
- Legacy integration: 46% cite system integration as primary challenge
- Governance: Only 21% have mature governance for autonomous agents
This analysis is part of NVIDIA & The State of AI from The Business Engineer by FourWeekMBA.









