MIT Technology Review » Artificial Intelligence 10月28日 17:47
AI 投入未因负面消息而缩减
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尽管近期有关于AI技术进展缓慢、试点项目失败率高以及公司裁员等负面消息,但媒体在调查中发现,并未有企业公开承认因这些因素而缩减对AI的投入。一种解释是,AI领域的热度并未受到显著影响,企业仍在持续投入。另一种观点认为,AI技术的实际进展和广泛应用速度,使得许多行业尚未达到对其产生重大负面影响的程度。此外,即使AI试点失败,许多公司也将其归因于数据不足或战略执行不力,而非技术本身的缺陷。一些曾经尝试缩减AI投入的公司,如Klarna和部分餐饮连锁企业,也已重新开始招聘或恢复相关项目,表明AI的战略价值仍在被重新评估和利用。

🤖 **AI 投资的持续性:** 尽管面临关于GPT-5发布不尽人意、95%的生成式AI试点项目失败等负面报道,但记者在深入调查后,并未发现有公司公开承认因此而减少AI方面的支出。这表明,即使有令人担忧的消息,企业对AI的投入似乎并未因此放缓。

💡 **对AI泡沫的解读:** 一种观点认为,企业在负面消息面前仍持续投入,恰恰印证了“AI泡沫论”的观点。然而,另一种解读是,当前关于AI的负面新闻,尚不足以让企业认为有必要大幅调整其AI战略。AI的快速发展和应用速度,可能使得经济和行业对其变化的敏感度比预期的要低。

📉 **失败原因的多样性:** 当AI试点项目失败时,企业(尤其是咨询行业)倾向于将其归因于多种战略性原因,如试点进展缓慢、缺乏足够的数据支持AI模型优化,而非AI技术本身的根本性缺陷。例如,Klarna在暂停招聘并声称用AI替代员工后,又重新开始招聘,并强调“AI提供速度,人才提供同理心”。

🛒 **具体案例的调整:** 一些企业在AI投入上进行了调整。例如,McDonald's和Taco Bell等连锁餐厅结束了语音助手AI的试点项目。此外,尽管可口可乐曾承诺投入巨资,但大部分广告内容并非由生成式AI制作。这些案例表明,企业正在根据实际情况,审慎评估和调整其AI应用策略。

A few weeks ago, I set out on what I thought would be a straightforward reporting journey. 

After years of momentum for AI—even if you didn’t think it would be good for the world, you probably thought it was powerful enough to take seriously—hype for the technology had been slightly punctured. First there was the underwhelming release of GPT-5 in August. Then a report released two weeks later found that 95% of generative AI pilots were failing, which caused a brief stock market panic. I wanted to know: Which companies are spooked enough to scale back their AI spending?

I searched and searched for them. As I did, more news fueled the idea of an AI bubble that, if popped, would spell doom economy-wide. Stories spread about the circular nature of AI spending, layoffs, the inability of companies to articulate what exactly AI will do for them. Even the smartest people building modern AI systems were saying the tech has not progressed as much as its evangelists promised. 

But after all my searching, companies that took these developments as a sign to perhaps not go all in on AI were nowhere to be found. Or, at least, none that were willing to admit it. What gives? 

There are several interpretations of this one reporter’s quest (which, for the record, I’m presenting as an anecdote and not a representation of the economy), but let’s start with the easy ones. First is that this is a huge score for the “AI is a bubble” believers. What is a bubble if not a situation where companies continue to spend relentlessly even in the face of worrying news? The other is that underneath the bad headlines, there’s not enough genuinely troubling news about AI to convince companies they should pivot.

But it could also be that the unbelievable speed of AI progress and adoption has made me think industries are more sensitive to news than they perhaps should be. I spoke with Martha Gimbel, who leads the Yale Budget Lab and coauthored a report finding that AI has not yet changed anyone’s jobs. What I gathered is that Gimbel, like many economists, thinks on a longer time scale than anyone in the AI world is used to. 

“It would be historically shocking if a technology had had an impact as quickly as people thought that this one was going to,” she says. In other words, perhaps most of the economy is still figuring out what the hell AI even does, not deciding whether to abandon it. 

The other reaction I heard—particularly from the consultant crowd—is that when executives hear that so many AI pilots are failing, they indeed take it very seriously. They’re just not reading it as a failure of the technology itself. They instead point to pilots not moving quickly enough, companies lacking the right data to build better AI, or a host of other strategic reasons.

Even if there is incredible pressure, especially on public companies, to invest heavily in AI, a few have taken big swings on the technology only to pull back. The buy now, pay later company Klarna laid off staff and paused hiring in 2024, claiming it could use AI instead. Less than a year later it was hiring again, explaining that “AI gives us speed. Talent gives us empathy.” 

Drive-throughs, from McDonald’s to Taco Bell, ended pilots testing the use of AI voice assistants. The vast majority of Coca-Cola advertisements, according to experts I spoke with, are not made with generative AI, despite the company’s $1 billion promise. 

So for now, the question remains unanswered: Are there companies out there rethinking how much their bets on AI will pay off, or when? And if there are, what’s keeping them from talking out loud about it? (If you’re out there, email me!)

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AI 人工智能 AI投资 AI泡沫 技术应用 企业战略 AI adoption Artificial Intelligence AI investment AI bubble technology adoption business strategy
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