Reasoning
Goldman Sachs has a documented history of publishing major research revisions on transformative technologies—they downgraded AI productivity estimates in early 2024 after initially bullish 2023 forecasts, and revised energy demand assumptions following similar boom-bust cycles. The current trajectory shows AI adoption is proceeding slower than 2023 peak enthusiasm (enterprise deployment rates ~15-20% vs. 40%+ predicted), capital expenditure scaling is facing ROI scrutiny, and analyst consensus on near-term productivity gains has already moderated substantially. By 2026, if current capex-to-productivity conversion rates persist below historical precedent, a major research house like Goldman publishing explicit downward revisions becomes highly probable as they seek to maintain credibility after prior optimism.Key uncertainty
Whether major AI productivity improvements materialize in 2025-2026 (particularly in enterprise workflows and code generation) which could validate prior assumptions and eliminate need for explicit downgrade—conversely, if productivity gains accelerate unexpectedly, Goldman would maintain or upgrade rather than downgrade.