Fortune | FORTUNE 16小时前
UBS took a sweeping look at the AI revolution and concluded the ‘visible’ impact is at least 3 years away for consumer firms
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人工智能正从后台效率工具跃升为消费行业的战略核心,尤其在需求预测、供应链自动化和个性化推荐方面展现出巨大潜力。尽管目前AI对企业盈利的直接量化影响尚不显著,但预计未来3-5年将变得更加明显。大型企业凭借雄厚的资本和数据优势,在AI应用上已取得初步成效,如沃尔玛通过AI优化供应链实现成本降低,欧莱雅利用AI提升营销效率。未来,AI将是区分行业胜负的关键,大型企业有望加速整合,而中小企业则面临挑战。AI的广泛应用将重塑客户体验,推动行业增长,但其对利润和劳动力的深远影响,仍需时间显现。

💡 AI已成为消费行业的战略焦点和竞争优势来源,其应用范围广泛,涵盖需求预测、供应链自动化、产品推荐等,旨在提升客户体验和运营效率。文章强调,AI将是未来区分行业领导者和落后者的关键因素。

📉 尽管AI备受关注且应用案例众多,但目前其对企业损益表的直接、可量化财务影响仍有限,尚未达到“实质性”水平。UBS报告预计,AI的财务效益将在未来3年内逐步显现,并在3-5年内变得更加明显,主要体现在利润增长和劳动力生产率提升方面。

🏢 AI正从后台运营工具升级为企业战略的核心组成部分。领先的消费品公司,如沃尔玛,已开始任命专门负责AI转型的执行官,并在营销、供应链和客户体验等领域积极部署AI技术。例如,沃尔玛利用AI驱动的推荐系统优化客户体验和履行效率,其供应链自动化已实现高达30%的单位成本降低。

📊 大型、资本雄厚的企业,如沃尔玛、欧莱雅和宝洁等,在AI投资和数据积累方面更具优势,能更好地利用AI技术获得竞争优势。例如,欧莱雅通过其BETiq工具在广告任务中实现了10%-15%的生产力提升,宝洁则通过智能卡车调度预计可节省2亿至3亿美元。然而,规模较小、技术不发达的公司可能在AI竞赛中处于劣势,可能加速行业整合。

🌍 AI在不同地区和行业的应用模式和影响存在差异。美国零售商和餐饮连锁店侧重于运营效率和客户互动,而欧洲奢侈品行业受AI影响相对较小。亚洲市场领导者则利用AI推动产品差异化和成本优势。总体而言,尽管AI应用广泛,但能明确报告AI带来的利润或收入增长的公司仍是少数,多数企业,尤其是小型企业,尚未看到显著的财务改善。

“It’s becoming an essential strategic focus and a competitive differentiator across the entire value chain, not just a tool for efficiency,” the authors write. They see wide-reaching use cases, from demand forecasting to supply-chain automation to product recommendations, and believe it should provide a “more pleasant customer experience” on top of improving operations. The use of AI will be a critical factor going forward that separates winners and losers in the consumer space, they add. It’s just so early.

Despite prominent case studies and a surge in executive attention, UBS finds the direct, quantifiable financial impact of AI remains limited, stating simply about profits and loss statements, or P&L: “AI’s impact on P&L is not material, but we expect it to be visible in the next 3 years.” Meanwhile, despite many headlines about AI-related layoffs, UBS finds little evidence of reductions in headcount: “We have heard some anecdotal evidence but not within our coverage.” Such reductions in force are likely to come, though, UBS added.

Drawing on in-depth interviews with analysts and company disclosures across more than 20 global sectors, the report details how AI is reshaping everything from supply chains and marketing to customer experience, while underscoring the most significant changes—and competitive divides—are yet to fully appear. “Most consumer companies expect the impact of generative AI to be more visible in 3 to 5 years,” the note adds.

AI moves from back office to boardroom

A central theme: AI has moved beyond being a back-office efficiency tool to a core part of business strategy. Large retail and consumer-oriented firms, notably Walmart, are appointing executives dedicated to AI transformation, underscoring its rising importance. The number of AI mentions on consumer-sector conference calls has doubled since 2022, and major investments are being made not only to streamline operations, but also to power growth through personalized recommendations, smarter inventory management, and targeted marketing.

Leading companies are finding a wide range of AI applications, the UBS Evidence Lab found.

    Walmart uses AI-driven recommendations and assistants to personalize the shopping experience and optimize fulfillment. Automation in its supply chain is credited with up to 30% reductions in unit costs at fulfillment centers.L’Oréal leans on AI for marketing optimization and product innovation, reporting 10%-15% productivity gains in advertising tasks due to its bespoke BETiq tool, which it expects to cover 60% of its marketing spend by 2024.P&G utilizes AI for logistics, and it has quantified a potential $200 million-$300 million in savings from smarter truck scheduling.

Globally, consumer-facing companies are also deploying AI for tasks ranging from product design (e.g., Robam’s proprietary LLM called “AI Gourmet” in China), to dynamic pricing, to smarter labor scheduling. In Australia, travel firms and retailers have cited cost savings and improved margins from AI-enabled automation.

Bigness will matter

A recurring takeaway is that large, well-capitalized incumbents are set to benefit most in the near to medium term. These players, such as Walmart, Home Depot, Coca-Cola, L’Oréal, and China’s Midea and Haier, can better afford the investments and have the customer data troves needed to maximize AI’s benefits. In contrast, smaller and less technologically advanced companies may struggle to compete, potentially accelerating industry consolidation or leaving followers at a disadvantage.

While patterns of AI adoption are broadly similar worldwide, impacts vary by region and sector. U.S. retailers and restaurant chains have focused on operational efficiency and customer engagement. The European luxury sector, more dependent on craftsmanship and brand, should see less near-term impact from AI. In Asian markets, market leaders are leveraging AI to drive product differentiation and cost advantages, but there is little evidence of broad profit impact yet.

Only a handful of companies, usually industry giants with deep pockets and rich data sets, are reporting clear improvements in margins or revenue directly attributable to AI adoption. Most firms, especially smaller ones, have yet to see material P&L enhancements. In many cases, AI’s efficiency gains are being reinvested to spur growth, rather than dropping to the bottom line.

Outlook: gains to materialize over 3–5 years

Most analysts expect the true financial benefits—higher margins, revenue growth, and labor productivity—to become “visible” within three to five years, as AI applications mature and become more deeply integrated into core business processes. In the meantime, a wave of experimentation—particularly in marketing, logistics, and customer experience—is laying the foundation for a potentially transformative decade for consumer industries.

For now, UBS concludes that for all the excitement, the AI revolution’s effects on consumer-sector profits and workforce structure are only just beginning to be felt.

For this story, Fortune used generative AI to help with an initial draft. An editor verified the accuracy of the information before publishing. 

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人工智能 消费行业 战略转型 供应链优化 客户体验
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