Hyperliquid News Today: The AI Hype Dilemma—How Targeted Approaches Outperform Generalized Efforts in Creating Value

Many companies are pushing too aggressively into artificial intelligence, yet most executives are struggling to realize real benefits from their AI spending, according to a recent study by MIT and comments from industry experts. A July report from the Massachusetts Institute of Technology found that 95% of businesses are failing to see clear, measurable gains from their investments in generative AI, highlighting a significant gap between expectations and actual results. This has led to calls for a more targeted strategy, with NTT Data CEO Abhijit Dubey recommending that leaders "focus on one or two areas that can deliver outsized economic impact for the business and execute thoroughly," instead of spreading AI efforts too thin, as reported by a

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The MIT report reflects a widespread challenge in expanding AI beyond initial pilot programs. For example,

has chosen to direct its AI initiatives toward three specific priorities: streamlining internal processes, improving customer interactions, and creating new value for clients, such as better demand prediction and minimizing product returns. Kami Viswanathan, who leads FedEx in the Middle East, Indian Subcontinent, and Africa, pointed out that organizations with a well-defined AI plan "achieve far greater success" than those lacking clear priorities, according to the Fortune article. Likewise, Vortexa, a company specializing in cargo tracking and energy analytics, has embedded AI into its chatbot-powered data tools but emphasizes the necessity of human oversight to avoid issues like AI hallucinations. CEO Fabio Kuhn remarked that "explainability" is becoming increasingly vital to ensure AI-driven decisions are both understandable and actionable.

Yet, not every AI-focused business is navigating this shift smoothly. C3.ai, which pivoted from energy management to AI solutions in 2019, experienced a 50% drop in its stock price in 2025 after founder Thomas Siebel unexpectedly retired. Siebel’s exit, who played a key role in securing major contracts, happened alongside a steep revenue decline in the latest quarter. Although the company now provides over 130 AI applications to help businesses adopt the technology, analysts remain cautious about its short-term prospects, with consensus price targets reflecting a wary outlook, as noted in a

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The gap between AI expectations and actual performance is also apparent in BigBear.ai’s recent 160% stock surge, despite worsening business fundamentals. Even after lowering its full-year revenue forecast by 22% for Q2 2025 and reporting an 18% year-over-year revenue decline, the company’s valuation has soared, raising questions about its growth and operational progress. Analysts have previously advised caution on investing in the stock, citing ongoing structural issues and missed opportunities in its early AI analytics niche, according to a

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Healthcare is another sector facing challenges in scaling AI. January AI’s Mirror platform, which processes patient data, keeps its hallucination rate below 1% by requiring human review of outputs. CEO Noosheen Hashemi stressed that while the tools to fight chronic diseases are available, progress is slowed by fragmented data and regulatory barriers in the U.S. "We have the technology today to eradicate lifestyle-based chronic diseases," Hashemi stated, but questioned "how willing we are to actually implement these solutions," as the Fortune article reported.

As organizations weigh the opportunities and risks of AI, the experiences of C3.ai, BigBear.ai, and other industry leaders highlight the importance of strategic focus. Dubey’s recommendation to concentrate on high-value areas rather than broad experimentation is echoed by companies like FedEx, which have found success by narrowing their AI scope. For investors, the contrasting paths of C3.ai and BigBear.ai serve as a reminder of the dangers of overhyping AI while overlooking the operational discipline needed to turn innovation into financial returns.