AI Stock Volatility Amid Declining ChatGPT Usage: Behavioral Finance vs. Fundamentals

The AI stock market in 2025 has become a battleground between behavioral finance dynamics and traditional fundamental analysis, as declining ChatGPT usage intersects with heightened volatility. While ChatGPT's weekly active users dipped slightly to 792 million in October 2025 from 800 million in June, according to ChatGPT usage statistics, its influence on investor behavior remains profound. This tension between sentiment-driven trading and hard metrics underscores a critical question: Can AI tools like ChatGPT reliably bridge the gap between market psychology and corporate fundamentals?

Behavioral Finance and the ChatGPT Effect

Generative AI has become a double-edged sword for investors. On one hand, platforms like ChatGPT and Grok are democratizing access to real-time sentiment analysis, enabling retail and institutional investors to decode market narratives at unprecedented speed, as shown in Decoding market sentiment. For example, prompts analyzing "XRP sentiment" or "Bitcoin's 200-day moving average" now yield actionable insights within seconds, a point the Emerald study also documents. On the other hand, the June 2025 34-hour ChatGPT outage revealed the fragility of this reliance. During the outage, trading volume for firms with recent corporate news or high transient institutional ownership dropped sharply, suggesting a significant portion of investors had outsourced decision-making to AI, according to a Trading with ChatGPT analysis.

This behavioral shift aligns with classic finance theory: investors increasingly treat AI as an "amplifier" of sentiment rather than a neutral tool. Studies show ChatGPT exhibits optimism bias in stock return forecasts, mirroring human cognitive flaws, as reported in a Purdue Business post. For instance, firms referencing ChatGPT in SEC filings saw abnormal returns, with technology stocks benefiting disproportionately compared to energy and financials, as documented in a SpringerOpen paper. Such patterns highlight how AI-driven sentiment can distort price discovery, particularly in sectors where transparency is low, according to a ScienceDirect study.

Fundamentals: The Bedrock of Long-Term Value

Yet, fundamental metrics remain the cornerstone of sustainable AI company valuations. The Q2 2025 AI Public Comp Sheet reveals that firms with proprietary technology, scalable compute infrastructure, and positive EBITDA margins-such as Palantir (PLTR) and Tesla (TSLA)-outperformed peers despite market jitters, as shown in the PitchBook guide. Palantir's 458% performance gain, for example, was underpinned by real-world traction in defense and enterprise AI applications, a point the PitchBook guide highlights. Similarly, AI semiconductor stocks rallied 37% on average, reflecting demand for hardware underpinning large language models, another finding in the PitchBook guide.

The divergence between sentiment and fundamentals became stark in October 2025 when Reddit's stock fell 12% amid a 95% drop in ChatGPT citations of its content, according to a Yahoo Finance report. While short-term traders panicked over reduced AI reliance, analysts noted Reddit's long-term value through data licensing deals with Google and OpenAI in that Yahoo report. This episode underscores a key risk: overreliance on AI sentiment analysis can obscure durable business models, leading to mispricings that fundamentals eventually correct.

Navigating the Sentiment-Fundamentals Divide

For investors, the challenge lies in synthesizing AI-driven sentiment with rigorous fundamental analysis. ChatGPT excels at contextualizing market narratives-such as regulatory shifts or ecosystem growth-but struggles with nuanced risk assessments, as described in an IEEE paper. For example, during the June 2025 outage, firms with poor AI disclosure faced amplified volatility, as sentiment-driven liquidity dried up, a dynamic highlighted in the SpringerOpen paper. Conversely, companies with strong fundamentals, like those in the AI semiconductor space, demonstrated resilience despite broader market jitters, which the PitchBook guide also noted.

A balanced approach is emerging. Advanced users now pair ChatGPT with traditional metrics, using AI to identify "why" markets move while relying on revenue growth, EBITDA, and R&D spend to validate long-term potential, as the IEEE paper discusses. This hybrid model mitigates the risks of overfitting to sentiment-driven noise, particularly in volatile sectors like crypto and AI applications.

Conclusion

The AI stock market of 2025 is defined by a tug-of-war between behavioral finance and fundamentals. While declining ChatGPT usage has introduced volatility, it has also exposed the limitations of sentiment-driven trading. Investors who integrate AI tools with disciplined fundamental analysis are better positioned to navigate this landscape. As the market matures, the winners will likely be those who treat AI not as a crutch but as a complementary lens-one that sharpens, rather than replaces, human judgment.