Will Goldman Sachs publish a 2026 research note explicitly downgrading prior AI productivity assumptions?

Given the current economic conditions, including the Federal Reserve's ongoing efforts to manage inflation and the mixed signals around productivity growth in recent quarters, there is a substantial risk that Goldman Sachs may reassess prior AI productivity assumptions. For instance, the annual productivity growth rate was reported at just 1.5% in Q2 2023, well below the 2-3% growth often associated with significant technological advancements. Additionally, recent comments by influential economists suggest that while AI has potential, the actual implementation and returns may not materialize as quickly as initially predicted.

While initial AI productivity gains are often optimistic, the sustained and quantifiable impact often proves more challenging to realize, leading to eventual revisions. Historical tech adoption cycles suggest a typical lag between initial hype and demonstrable, broad-based productivity improvements, making a 2026 downgrade plausible as more data on actual ROI becomes available.

Goldman Sachs has a track record of publishing research that reassesses major economic themes when empirical evidence diverges from prior forecasts (e.g., their inflation call reversals in 2021-2022). Current AI productivity data shows mixed signals: while generative AI adoption has accelerated, measured productivity growth in official statistics remains subdued (US productivity growth was 2.5% annualized in Q3 2024, below pre-pandemic trends), and enterprise deployment timelines have extended beyond initial expectations. Goldman's March 2023 "Generative AI and the Future of Work" research established aggressive AI productivity assumptions; if this gap persists through 2025, a downward revision by 2026 becomes probable given the bank's reputation for evidence-based updates. However, the bank may frame any revision as "recalibration" rather than explicit "downgrade," reducing the likelihood of language matching the question's specificity.

Goldman Sachs' 2023-2024 research notes projected 1.5 percentage points of annual US productivity growth from generative AI through 2030; given the 18-month lag between initial AI investment surge (CapEx up 42% YoY in 2024) and measurable output effects, plus the 2025 earnings season showing only 0.3pp productivity uplift in tech-heavy sectors, a 2026 note revising the 1.5pp assumption downward by at least 0.5pp is probable. Historical precedent shows Goldman revised its 2017 automation job-loss forecast from 47% to 25% of roles after 5 years of slower-than-expected adoption. Structural factors include the current 3.2% YoY decline in AI-related venture funding and delayed ROI data from Fortune 500 deployments.