Evercore ISI analyst Julian Emanuel laid out a bifurcated outlook for the S&P 500 in a client note on Monday, setting a base-case target of 7,750 for the index by year-end 2026 and assigning a 30% probability to an upside scenario that would lift the S&P 500 to 9,000.
Emanuel attributes the potential for such strong gains to AI-led appreciation concentrated in technology, communication services and consumer discretionary sectors. He described the current environment as the intersection of a structural, technology-driven bull market and broad geopolitical transformation, an alignment that he says expands the range of plausible outcomes beyond what conventional forecasting tools typically model.
In his note, Emanuel framed the present moment as a dramatic inflection, writing: "The Pandemic changed everything. Warlike stimulus, surging M2, and a productivity shock collide with an 'AI Revolution' - reminiscent of the 1920s and 1990s." He expects that dynamic could lift productivity growth to 3% by the end of the decade.
Given that possibility set, Evercore ISI recommends option strategies that express long-dated upside on stocks it labels the "AI Class of 2026," as well as on the QQQ ETF, which the firm views as positioned for potentially "seemingly unimaginable" gains under the bull case. At the same time, the firm advises using a collar strategy on SPY to protect against nearer-term headwinds arising from movements in oil prices and interest rates.
But Emanuel also injected caution about the limits of current AI systems. He noted that artificial intelligence remains probabilistic and constrained, and he warned against overestimating the general-purpose abilities of large language models. According to Evercore ISI, such models show a "Narrow Consensus" bias in which outputs cluster near consensus views and understate tail outcomes. From that perspective, Emanuel argued that sustained value will be earned by firms with deep domain expertise and by those that own end-to-end workflows, rather than by AI capability alone.
The note further observed that markets and prediction mechanisms reflect crowd beliefs but do not necessarily discover long-dated or tail-heavy futures. Emanuel cautioned that prediction markets reveal what participants currently believe, which may make them less reliable for continuous, long-dated, or extreme scenarios.
Strategy implications laid out by the firm are therefore twofold: take targeted, long-dated option exposure to concentrated AI winners and ETFs like QQQ to capture potential upside, while also employing protective collars on broad indexes such as SPY to guard against more immediate macro-driven volatility.
Overall, Emanuel's view emphasizes a wider distribution of possible market outcomes as a result of the interaction between technological acceleration and geopolitical shifts. That broader distribution raises the odds of both pronounced upside, represented by the 30% path to 9,000, and meaningful downside, which the suggested hedges aim to mitigate.