What if an AI agent completes month-long business tasks unsupervised?
An agent completing month-long unsupervised business tasks reprices services-labor substitution — compute demand (NVDA/AVGO/memory) rises while the demand-drag and consumer-credit stress weigh on the S&P. Rhymes with the May-2023 Nvidia blowout that bid compute as the displacement thesis pressured labor-exposed sectors. Forward angle: long-horizon reliability is the gating factor — if the agent still needs heavy human oversight, the labor-substitution repricing is premature, so fade the displacement leg until autonomy is proven; roots (high ai_capex, high displacement) are apt.
Every number ships with its receipt — the odds, the range, the precedents, and a public grade at Reality Check. The statistical machinery that produces it is proprietary.
The butterfly cascade
How this trigger trickles across markets, left → right — the root shock, its first‑order moves, then the ripple effects. Drag any node; tap a market for its real price history.
Resolution timeline — how this probability is moving
Our model's odds (electric blue) over time vs the market's (Polymarket, amber), from the past toward the 1–3 years horizon. Each dot is a real macro event that nudged the probability — green pushed it up, red pushed it down. Tap a dot for the source. Loading the probability audit trail…
What it would mean
If this plays out, it is a risk-off shock. An agent completes month-long multi-step business tasks unsupervised, repricing labor-substitution exposure across services. The trigger decomposes into signed root‑shocks — AI capex ▲ · Job displacement ▲ — which propagate through our causal graph to the markets below.