All Content from Business Insider 11月12日 13:55
企业AI应用落地缓慢,投资回报受质疑
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尽管消费者对人工智能(AI)的热情高涨,企业在AI应用落地方面却进展缓慢。高盛分析师指出,虽然ChatGPT等工具在消费者层面广受欢迎,但企业级应用和用户采纳率远低于预期。AI基础设施建设虽然强劲,但高昂的投资引发了对长期回报的质疑。麦肯锡的报告也显示,大多数公司虽然在部分业务中使用AI,但仅有少数能将其推广至整个企业,实现显著的财务效益仍是挑战。

📈 **消费者AI应用普及,企业落地滞后**:ChatGPT等AI工具已迅速吸引消费者,但在企业层面,AI的应用和用户采纳率远未达到预期。高盛分析师Kash Rangan表示,企业在AI采用方面“远低于”他之前的预期,尤其是在过去六到九个月的进展缓慢。

💡 **AI基础设施需求旺盛,投资回报存疑**:生成式AI(如ChatGPT、Google Gemini)推动了对计算能力的需求,AI基础设施的建设超出了预期。然而,高昂的投资额,例如高盛预计到2030年AI基础设施的累计支出将达3万至4万亿美元,引发了投资者对长期投资回报的担忧,他们难以证明如此巨大的投入能带来相应的回报。

📊 **企业AI应用现状:广泛使用但深度不足**:麦肯锡的《2025年AI现状报告》显示,近88%的公司报告在至少一项业务功能中使用AI,但只有约三分之一的公司将其推广至整个企业。尽管64%的公司认为AI促进了创新,但仅有39%的公司报告AI已对公司盈利产生影响,表明AI尚未被足够深入地嵌入工作流程以实现企业级效益。

🎓 **教育领域AI的协同潜力**:卡内基梅隆大学的一项研究表明,当人类教师与AI协同教学时,学生的学习效果最佳。这预示着AI在教育领域的应用应侧重于人机协作,以最大化学习效率和效果。

A Carnegie Mellon study finds students learn fastest when humans and AI teach together.

Artificial intelligence may be transforming how consumers use technology, but the revolution is still lagging when it comes to businesses, according to a pair of Goldman Sachs analysts.

"A lot of consumer applications, they're exemplifying the value of AI, whether it's ChatGPT or Claude application at the consumer level. But at the enterprise level and user level, there are some signs of life, but we're not where we expected," said Kash Rangan, a US software equity research analyst, on Goldman Sachs' "Exchanges" podcast published on Tuesday.

While tools like ChatGPT have rapidly captured consumer attention, corporate adoption has been slower.

Rangan said companies are "well below" where he thought they would be in AI adoption.

"It's not where we expected it to be a year ago, two years ago, but rather to where we were six months ago, nine months ago," he said.

Eric Sheridan, a US internet equity research analyst, said the AI infrastructure buildout has "surprised to the upside." That surge, he added, reflects how demand for computing power from generative models such as ChatGPT and Google Gemini has already outpaced available capacity.

High spending has left some investors questioning whether the returns will ever match the outlay. Sheridan said the rapid rise in AI infrastructure investment has created growing doubts about the long-term return on investment, even as spending keeps accelerating.

Sheridan pointed to Nvidia's forecast of $3 trillion to $4 trillion in cumulative AI infrastructure spending by the end of the decade.

"I think most investors we talk to would struggle to justify the return profile on 3 to 4 trillion of cumulative spend, unless AI is the main driving factor in an enormous amount of the economic output of society in some sort of end state," he said.

The Goldman analysts' comments come amid investor jitters over the scale of AI spending that has pushed the S&P 500 and Nasdaq to record highs in recent weeks. Stocks pulled back last week on concerns that markets may have run ahead of fundamentals.

That gap between excitement and execution echoes what consultants at McKinsey are seeing.

In its State of AI 2025 report, released last week, McKinsey found that while nearly 88% of companies report using AI in at least one business function, only about a third have scaled it across the entire enterprise.

In its survey of nearly 2,000 companies across industries, 64% said that AI is enabling their innovation. However, 39% reported AI's impact showing up in the bottom line.

"While AI tools are now commonplace, most organizations have not yet embedded them deeply enough into their workflows and processes to realize material enterprise-level benefits," wrote McKinsey's consultants.

Read the original article on Business Insider

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