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璞砺营销咨询:2026年“下一步”指南:开拓可能 决胜未来(中译版)(82页).pdf

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1、1Guide to Next.2026Fight forwhatspossible20262Guide to Next.2026Table of contentsOverview0304050711172224314050575964697681Industry provocationsMacro TrendsEditors Note Guide to Next 2026:At a GlanceIllustration:Words that Define 2026Financial Services Client Experience Gap is Blocking a$124 Trillio

2、n Wealth TransferRetail Depends on AI That Encodes Identity,Not Just EfficiencyWhen Bots Shop,How Will Consumer Product Brands Win?Transportation and Mobility Are Finally in Their Platform EraDear PS:How Do I Navigate the Tariff Situation?The Next Breakthrough in Healthcare is AccessEnergys Real Pow

3、er Shift Comes from Decision Making,Not SupplyFractured Audiences Push Telecommunications and Media to Redefine ReachThe Attention Wars Are Coming for Travel and HospitalityThe Next Tech Debt Crisis is AgenticThe Boldest Move in AI?Data Governance That Actually Works AI Ate the Entry Level.Now What?

4、Illustration:The Digital HangoverWhy 2026 feels differentBold takes on every major sectorForces reshaping business as we know itResearch Methodology3Guide to Next.2026Every year,“Guide to Next”is our chance to take a clear-eyed look at whats coming.But this year,the stakes feel higherthe decisions h

5、eavier,the bets bigger.Leaders told us theyre walking into 2026 with equal parts optimism and unease.The phrase that stuck with us was this:optimistic uncertainty.That tension is real.Across Publicis Sapients own industry surveys,the majority of executives say their AI technology and programs are sc

6、aled or enterprise ready.Yet our data,and the experts we spoke with,reveal a different story:most organizations are still in pilot mode.Confidence is outpacing capability,and that gap has become the new fault line in enterprise AI.Its what our research calls decision debt:when optimism moves faster

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根据《Guide to Next 2026》的内容,以下是全文关键点的概括: 1. **企业AI的挑战**:多数企业AI技术发展迅速,但实际应用能力不足,存在“决策债务”问题,即乐观情绪超越实际证据,导致假设先行于系统建设。 2. **行业趋势**: - **金融服务**:财富转移高达124万亿美元,金融机构需从产品转向以生活为中心的旅程。 - **零售**:AI将影响零售的每个角落,成功取决于编码品牌身份而非仅效率。 - **消费品**:购买决策转向机器,无法使数据可读的品牌将消失。 - **交通与移动性**:汽车成为连接商业平台,赢家将满足真实驾驶需求。 - **医疗保健**:AI的最大影响来自改善可及性而非诊断。 - **能源与商品**:赢家是那些决策最快、最佳的公司。 - **电信、科技与媒体**:受众碎片化,增长取决于个性化、信任和更智能的数据使用。 - **旅游与酒店业**:分销正在被AI、影响者和数字身份重新定义。 3. **技术债务危机**:自主代理的快速扩散导致“代理债务”,企业需标准化数据、协调自动化并跟踪每个代理决策。 4. **数据治理**:AI项目失败往往不是模型问题,而是数据不一致和碎片化。企业应建立数据治理习惯,如数据 stewardship、共享定义和可追溯来源。 5. **人才短缺**:自动化正在消除早期职业角色,导致未来领导者人才短缺。企业应通过导师制、培养可持续技能和利用AI节省的时间来投资人才。 6. **财富管理**:金融服务机构需适应年轻投资者,提供个性化、前瞻性的指导,以应对124万亿美元的财富转移。 7. **零售**:AI将影响零售的每个角落,成功的关键在于将品牌价值观和客户承诺直接编码到AI系统中。 8. **消费品**:品牌需确保其AI代理代表公司真实价值观,以在自动化商业中脱颖而出。
"AI时代,品牌如何脱颖而出?" "财富转移,金融如何拥抱变革?" "零售未来,AI如何助力品牌?
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