Apple (NASDAQ: AAPL ) shares are surging following the company’s fiscal 2026 annual report , and artificial intelligence ( AI ) projects an optimistic Apple stock price target for November 30, 2026.
Namely, Finbold’s AI-powered prediction tool sees the iPhone maker rallying another 5.91% from the current price of $334.97 by the end of the month, eventually trading at $354.78, which would be a new all-time high.
AI predicts Apple stock price on November 30, 2026. Source: Finbold
The two models the tool leveraged were relatively aligned in their forecasts. ChatGPT -5.7 Luna delivered the most bullish projection, anticipating a 6.52% advance, while DeepSeek Chat provided a more conservative estimate, predicting a 5.31% increase.
While the models point to continued gains, the forecasts remain estimates rather than guaranteed price targets, even if shares have been on a generally upward trend this year.
Artificial intelligence predicts AAPL share price target on November 30, 2026. Source: Finbold
Human analysts also see Apple stock rallying
With the earnings report generating a lot of buzz, Wall Street analysts likewise revisited their Apple stock price targets. For example, Evercore ISI reaffirmed its “Outperform” rating and $380 forecast after reviewing Apple’s record-setting financial year.
The company generated $478.8 billion in full-year revenue, up 15% year-over-year (YoY), while earnings per share (EPS) climbed 20% to $8.98. Both figures marked all-time highs for the tech giant. Meanwhile, the company forecast December-quarter revenue growth of 7% to 10%.
For the same reasons, Baird raised its price target on Apple from $330 to $340 while maintaining an “Outperform” rating. In addition, the prediction was bolstered by new M6 hardware, including an updated 14-inch MacBook Pro.
The combination of renewed analyst confidence, fresh product announcements, and record fiscal 2026 results thus fueled Thursday’s rally, bringing Apple shares within striking distance of their 52-week high of $351.73 and the new all-time high projected by our machine learning algorithm.
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