Frontier firms now generate 8.3x as many output tokens per active user as typical firms, up from 2.6x in January, according to OpenAI Enterprise Signals 2026.
The gap isn't about prompting more. It's about connecting agents to company context and tools, then letting them finish the work.
There's no liquid Kalshi or Polymarket contract pricing this enterprise divide, so there are no live odds or volume to read. The move is visible in private adoption, not public prices.
Basis, Clay and Exa Labs show how depth turns into capability. Each team started with one consequential workflow where stakes and handoffs were clear.
Why traders might price it this way
If a market existed, traders would pay for depth over dabbling. Repeatable workflows with evidence and review hold value when demos fade, and these three have measurable stakes and controls.
What execution looks like when it works
Basis turned a single onboarding demo into a reusable skill and cut first-day setup from two hours to 30 minutes. Clay gives every account a persistent workspace that refreshes overnight and surfaces priority moves each morning, saving about an hour of triage. Exa Labs carries integration signals into pull requests, tests and weekly updates before humans decide to ship.
The pattern holds: teach a stable process, persist context as work evolves, then let execution run within bounds. Evidence stays inspectable and humans keep decision rights on commitments.
OpenAI finds early-career employees sent 13 more messages per week than executives six months after adoption. That suggests the best workflows surface from daily use, not top-down rollout, which carries risk if leaders centralize too early.
Liquidity is the constraint for any trade here. Without a binary resolution and real volume, you cannot hedge the frontier gap as a prediction.
Not financial advice. Markets move fast.
