Raising the quality of insights in agentic analytics
Raising the quality of insights in agentic analytics
提升代理分析中洞察的质量
Sponsored In partnership with Snowflake In just a few years, generative AI has changed the face of enterprise analytics, notably by making analytics accessible to users across the organization. Agentic AI promises to do even more, by automating entire workflows and taking actions based on agent insights. But there is a problem: The quality of insights that agents currently generate leaves much to be desired. Fewer than half of agent-generated insights at the organizations surveyed for this report lead to business improvement. And while most respondents praise the quality of their agents’ descriptive insights, reviews of their prescriptive insights—those on which actions are based—are decidedly mixed.
由 Snowflake 赞助。在短短几年内，生成式人工智能改变了企业分析的面貌，特别是让组织内的用户都能使用分析工具。代理式人工智能（Agentic AI）承诺做得更多，通过自动化整个工作流程并根据代理的洞察采取行动。但存在一个问题：代理目前生成的洞察质量远未达到理想水平。在本报告调查的组织中，不到一半的代理生成洞察能带来业务改善。虽然大多数受访者称赞其代理在描述性洞察方面的质量，但对其规范性洞察（即采取行动所依据的洞察）的评价却褒贬不一。
DOWNLOAD THE REPORT Failure to produce insights that improve the business deprives organizations of their desired return on investment in agentic analytics. Worse, flawed insights that trigger incorrect actions can cause reputational or financial damage. This report gauges how companies view the quality of the outputs produced by their analytics agents and explores how organizations are seeking to boost insight quality and get their agents working harder for the business.
下载报告。未能产生改善业务的洞察，使组织无法获得其在代理分析中预期的投资回报。更糟糕的是，触发错误行动的缺陷洞察可能会导致声誉或财务损失。本报告评估了公司如何看待其分析代理所产生输出的质量，并探讨了组织如何寻求提高洞察质量，以及如何让代理更有效地为业务服务。
Some key findings from the report include the following: Agentic analytics is only just starting to deliver. On average, 48% of insights generated by analytics agents at the surveyed companies lead to actions that improve the business. That is a marked advance from the 37% average the respondents say generated such actions one year ago. But it means that more than half of the insights generated by analytics agents today are still failing to help businesses.
报告的一些关键发现包括：代理分析才刚刚开始发挥作用。在受访公司中，平均有 48% 的分析代理生成的洞察能引导出改善业务的行动。这比受访者一年前所称的 37% 的平均水平有了显著进步。但这同时也意味着，今天由分析代理生成的洞察中，仍有超过一半未能帮助到企业。
Better quality of insights leads to clear business advantage. At a small cohort of organizations, which we term “insight leaders,” AI agents perform much better than the average. In this group, more than 70% of agent insights lead to actions that improve the business. The insight leaders also give the quality of their agents’ insights higher marks than do the total respondents overall. The quality gap is particularly wide when it comes to prescriptive insights.
更高质量的洞察带来明显的商业优势。在一小部分我们称之为“洞察领导者”的组织中，人工智能代理的表现远好于平均水平。在这一群体中，超过 70% 的代理洞察能引导出改善业务的行动。与总体受访者相比，这些“洞察领导者”对其代理洞察质量的评分也更高。在规范性洞察方面，这种质量差距尤为明显。
Insufficient context reduces insight quality. When analytics agents deliver insights of substandard quality, the main reason is a lack of business context, as cited by 55% of surveyed executives. Fragmented or inaccessible data is the other major factor, according to 45%. Fewer insight leaders say their agents struggle with access to context.
背景信息不足会降低洞察质量。当分析代理提供的洞察质量不达标时，主要原因是缺乏业务背景，55% 的受访高管提到了这一点。据 45% 的受访者称，数据碎片化或无法访问是另一个主要因素。较少的“洞察领导者”表示其代理在获取背景信息方面存在困难。
Insight overload further inhibits agent effectiveness. At a majority (52%) of surveyed organizations, analytics agents generate too many insights to be properly evaluated and therefore acted upon. Less than one-quarter (24%) are able to evaluate all agent insights; most do so on a case-by-case basis, and that process is currently human-intensive.
洞察过载进一步抑制了代理的有效性。在大多数（52%）受访组织中，分析代理生成的洞察过多，无法得到妥善评估，从而无法采取行动。不到四分之一（24%）的组织能够评估所有代理洞察；大多数组织采取逐案评估的方式，而这一过程目前非常依赖人力。
Governance and semantics are areas of focus for improving insights. The surveyed companies are prioritizing initiatives that enable better agent insights by strengthening AI and data governance (cited by 60%). They are also adding a semantic layer to their data architecture (45%). The experts we interviewed agree that the semantic layer is crucial to ensure high-performing agents.
治理和语义是提高洞察质量的重点领域。受访公司正在优先采取措施，通过加强人工智能和数据治理（60% 的受访者提到）来促进更好的代理洞察。他们还在其数据架构中添加了语义层（45%）。我们采访的专家一致认为，语义层对于确保代理的高性能至关重要。