内容来源：https://www.technologyreview.com/2026/07/02/1140045/achieving-operational-excellence-with-ai/

内容总结：

AI赋能运营卓越：技术与流程融合成企业决胜关键

随着人工智能重塑工作方式，拥有强流程框架的企业在规模化运营中占据先机。精益六西格玛和业务流程管理等框架曾为混乱的运营带来秩序，如今正随着AI的嵌入而演进。数据显示，AI驱动的流程优化市场预计在未来十年内突破1130亿美元，88%的企业高管计划在未来12至18个月内加大AI流程智能投资。

然而，缺乏坚实基础的投资可能难以兑现预期。那些已具备规范化运营的企业更具优势，能将AI工具融入成熟系统，而非仓促附加于薄弱基础。成熟的流程管理文化使组织更易将AI愿景转化为实际成果，因为它们已适应数据驱动决策和流程纪律——这正是AI系统创造价值所需的文化土壤。

简言之：AI能加速流程优化，但现有流程卓越性才是发挥AI效用的关键。技术与流程不再是独立杠杆，只有将二者协同推进的企业，才能实现两者的全部价值。

（注：以上内容整合了领导段落与后续分析，遵循新闻报道的客观陈述风格，同时保留原文核心论点。）

中文翻译：

赞助内容

借助AI实现卓越运营

随着人工智能重塑工作方式，拥有强大流程框架的组织最能在规模化运营中保持严谨与领先地位。

与Teleperformance联合呈现

精益六西格玛和业务流程管理（BPM）等框架最初之所以受到追捧，是因为它们承诺在混乱中带来清晰——一种将杂乱、庞大的运营过程理顺的结构化方法。精益六西格玛强调统计严谨性和质量控制；BPM则绘制出跨部门工作流的全流程蓝图。两者都提供了一种可重复的方式，将衡量、分析和问责的习惯植入日常公司文化。

但如今，随着企业寻求将AI融入成熟的卓越运营方法论，这些经过时间考验的经典法则正在演变。据估计，AI驱动的流程优化市场在未来十年内预计将超过1130亿美元。在一项研究中，高达88%的商业领袖预计在未来12至18个月内将增加对AI赋能的流程智能的投资。

然而，若缺乏正确的基础，许多此类投资可能无法充分发挥其潜力。那些已经以严谨方式运营的公司具有优势。它们能将新工具引入经过验证的系统中，而不是将其硬塞到不稳固的基础上。拥有成熟流程规范的组织也更能将AI的雄心转化为实际成果，因为它们早已习惯于数据驱动的决策和流程纪律——这正是AI系统发挥价值所需的文化基础。

简而言之：AI可以加速卓越运营，但现有的卓越运营才能使AI真正产生影响。技术与流程不再是可以独立运作的杠杆，只有将两者结合起来的组织，才能真正实现双方的全部价值。

本内容由MIT Technology Review的定制内容部门Insights制作。并非由MIT Technology Review编辑团队撰写。内容由人类作者、编辑、分析师和插画师进行研究、设计和撰写，包括调查的编写及调查数据的收集。可能使用的AI工具仅限于经过人工严格审核的辅助生产流程。

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英文来源：

Sponsored
Achieving operational excellence with AI
As AI reshapes how work gets done, organizations with strong process frameworks are best positioned to lead and maintain operational rigor at scale.
In association withTeleperformance
Frameworks like Lean Six Sigma and business process management (BPM) first gained traction because they promised clarity in the chaos—a structured way to bring order to messy, sprawling operations. Lean Six Sigma emphasized statistical rigor and quality control; BPM created end-to-end maps of how work should flow across departments. Both offered a repeatable way to embed habits of measurement, analysis, and accountability into day-to-day company culture.
But today, those time-tested playbooks are evolving as companies seek to embed AI into established process excellence methodologies. By some estimates, the market for AI-powered process optimization is projected to exceed $113 billion within the next decade. In one study, a full 88% of business leaders anticipated increasing investments into AI-infused process intelligence in the next 12 to 18 months.
Yet without the right foundations, many of those investments may not fully deliver on their potential. Companies that already operate with discipline have an edge. They can channel new tools into proven systems rather than bolting them onto shaky foundations. Organizations with mature process disciplines are also better positioned to translate AI ambition into real outcomes, as they are already accustomed to data-driven decision-making and process discipline—precisely the cultural foundation AI systems need to deliver value.
Simply put: AI can accelerate process excellence, but existing process excellence is what makes AI truly impactful. Technology and process are no longer separate levers, and only organizations that pull them together stand to realize the full value of both.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.
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