内容来源：https://aibusiness.com/agentic-ai/in-catch-up-google-intros-ai-agents-financial-legal-services

内容总结：

谷歌云发布面向金融与法律行业的Gemini Enterprise新方案，追赶行业垂直化AI趋势。

谷歌于本周二推出了面向金融服务的Gemini Enterprise，以及相应的法律行业版本。这一举措标志着谷歌在AI竞争格局中，正效仿其主要竞争对手Anthropic和OpenAI，向垂直领域和特定行业的AI代理方向迈进。早在一年多前，Anthropic就已发布面向金融服务的Claude解决方案，其Cowork产品也配备了金融和法律领域的专用插件；OpenAI同样在其Codex平台上为包括金融在内的多个行业提供了插件服务。

此次发布的金融版Gemini Enterprise基于通用平台构建，包含谷歌托管的金融研究代理、50多项针对金融岗位和工作流程的专属技能，以及企业数据连接器。法律版本则配备了面向律师的专业技能和专用法律系统连接器。

有分析人士指出，谷歌在垂直领域布局上略显迟缓，目前处于追赶状态。Futurum Group分析师David Nicholson表示，谷歌正试图通过强调开放性和兼容现有业务流程的理念来吸引企业客户。例如，谷歌云CEO Thomas Kurian在声明中强调，金融专业人士需要的是不被单一模型或生态锁定、且具备高度安全性和合规性的平台。

然而，Nicholson认为，企业客户对“锁定”问题的关注度可能并不高。他们更关心的是AI代理能否在企业信任的框架和护栏内运行。对于已身处谷歌生态内的企业，他们了解其中的规范约束，因此相比独立的AI公司，他们可能更倾向于信任谷歌。但他也补充道，谷歌以“中立平台”作为卖点存在矛盾——作为AI竞赛的主要参与者，谷歌有动力超越OpenAI和Anthropic，因此难以真正保持中立。相比之下，与AI竞赛关联较少的厂商或许更能吸引那些希望避免绑定单一供应商的企业。

谷歌的优势或许更多体现在为金融服务业提供辅助流程的应用上。Tekonyx创始人兼首席研究官Sid Nag指出，这些应用通常基于CoinDesk Data & Indices、Daloopa、Dun & Bradstreet和FactSet等系统构建。他认为，谷歌的战略资产并非Gemini模型本身，而是通过其企业连接器将Gemini Enterprise与金融行业授权的数据源相连接的能力，并凭借强大的“企业控制平面”形成优势。

Nag表示，此次金融和法律版Gemini Enterprise的发布表明，谷歌正正确地将企业AI的讨论焦点从模型能力转向行业落地执行。

中文翻译：

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新平台展示了该供应商如何朝着AI代理的更多垂直应用方向迈进，同时也暴露了其落后程度。

谷歌周二推出了面向金融服务的Gemini Enterprise，以及面向法律行业的类似版本。

这些发布标志着谷歌姗姗来迟地朝着垂直和行业专属AI代理方向迈进，效仿了其主要的两大AI竞争对手Anthropic和OpenAI的做法。

Gemini Enterprise for Financial Services和Legal版本均基于Gemini Enterprise平台构建。金融套件包含一个由谷歌管理的金融研究代理、50多项针对金融岗位和工作流程的专用代理指令新技能，以及企业数据连接器。同样，Gemini Enterprise for Legal包含面向律师的专用技能，以及连接专业法律系统的连接器。

谷歌正在追随Anthropic和OpenAI等前沿模型创造者一年多前开启的趋势，当时Anthropic发布了面向金融服务的Claude。Anthropic Claude Cowork也拥有针对金融和法律领域的专用插件。OpenAI同样在其Codex平台上提供跨行业使用的插件，包括金融行业。

鉴于其他供应商已纷纷转向行业专属产品，谷歌推出Gemini Enterprise for Financial Services似乎有些迟了。

“目前谷歌在很多方面都在追赶，”Futurum Group分析师David Nicholson表示。“不过，他们正试图通过专注于开放性和‘你不会抛弃所有现有流程’这一理念来弥补这一点。”

他表示，谷歌试图通过将自己定位为一个中立的平台层来吸引企业客户，帮助他们优化现有流程。例如，谷歌云CEO Thomas Kurian在一份声明中强调，金融专业人士希望平台不会将他们锁定在单一模型或生态系统中，同时要具备高度安全性和合规性。

然而，Nicholson表示，企业可能并不那么在意“锁定”问题。

“企业寻求的是信任——相信AI代理能在一个他们信赖的框架和防护栏内运作，”Nicholson说。他表示，已经身处谷歌生态内的企业知道存在明确的防护栏可供其操作。

“在这一方面，他们更可能信任谷歌，而不是将Anthropic或OpenAI视为独立公司来信任，”Nicholson补充道。

劣势与优势

然而，谷歌面临的挑战在于它已经在一定程度上落后于OpenAI和Anthropic等竞争对手。虽然Gemini在性能上曾一度领先于ChatGPT和Claude，但此后该模型已被超越。因此，谷歌要追赶的地方还有很多。

此外，Nicholson补充道，谷歌“中立平台”的定位难以成立，因为作为AI竞赛的主要参与者，它有动力保持对OpenAI和Anthropic的领先，这意味着它不可能保持中立。

“谷歌能从‘我们保持中立’这一论点中获得多少收益尚不明确，”他说，并补充道，那些与AI竞赛关联不那么深的供应商，可能更能吸引那些希望不被绑定在单一供应商身上的企业。

Tekonyx创始人兼首席研究官Sid Nag表示，谷歌的优势可能更多在于其为金融服务业提供辅助业务流程的应用访问能力，这些应用通常构建在CoinDesk Data & Indices、Daloopa、Dun & Bradstreet和FactSet的系统之上。

“战略资产并非Gemini本身，而是谷歌通过所提及的连接器，将Gemini Enterprise连接到金融行业特许数据存储库的能力，”Nag说。

他补充说，该供应商可以通过拥有“强大的企业控制平面”而占据优势。

尽管如此，Nag表示，新的Gemini Enterprise金融和法律系统表明，“谷歌正在正确地将企业AI对话从模型能力转向行业执行落地。”

英文来源：

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The new platforms show how the vendor is moving toward more vertical use of AI agents, but also how far behind it is.
Google on Tuesday launched Gemini Enterprise for Financial Services and a similar legal industry version.
The releases signify Google’s belated move toward vertical and domain-specific AI agents, following the example of Anthropic and OpenAI, the tech giant’s two main AI rivals.
Both Gemini Enterprise for Financial Services and Legal are built on the Gemini Enterprise platform. The financial suite includes a Google-managed financial research agent, more than 50 new skills with specialized agentic instructions for financial roles and workflows, and enterprise data connectors. Similarly, Gemini Enterprise for Legal includes specialized skills for lawyers and connectors to specialized legal systems.
Google is following a trend that frontier model creators such as Anthropic and OpenAI started more than a year ago, when Anthropic released Claude for Financial Services. Anthropic Claude Cowork also has specific plugins for the financial and legal sectors. OpenAI also offers plugins on its Codex platform used across industries, including finance.
With other vendors already shifting toward domain-specific offerings, it appears that Google is launching Gemini Enterprise for Financial Services a little late.
“Right now, Google is playing catch-up in a lot of ways,” said David Nicholson, an analyst at Futurum Group. “However, they are trying to make up for that by focusing on openness and the idea that you’re not going to ditch all of your existing processes.”
He said that Google is trying to appeal to enterprises by pitching itself as a neutral platform layer that helps them with their existing processes. For instance, in a statement, Google Cloud CEO Thomas Kurian highlighted that financial professionals want a platform that does not lock them into a single model or ecosystem and that is highly secure and compliant.
However, enterprises might not care so much about lock-in, Nicholson said.
“[Enterprises] are seeking to trust that agents work within frameworks and guardrails that a company trusts,” Nicholson said. He said that enterprises already within Google’s sphere know there are defined guardrails they can operate within.
“They are more likely to trust Google on this than they are Anthropic or OpenAI as an individual standalone company,” Nicholson continued.
Weaknesses and Strength
However, Google’s challenge is that it has fallen somewhat behind competitors such as OpenAI and Anthropic. While Gemini was at times ahead of ChatGPT and Claude in performance, the model has since been overtaken. Therefore, Google has much to do to catch up.
Moreover, Google’s pitch as a neutral platform falls flat because, as a major player in the AI race, it has a motivation to stay ahead of OpenAI and Anthropic, which means it can’t be neutral, Nicholson added.
“It’s unclear how much Google is going to gain from this argument that they’re neutral,” he said, adding that other vendors that are not so intertwined in the AI race could
appeal more to enterprises for the ability not to be tied to any one vendor.
Google’s strength might lie more in its ability to provide the financial services industry with access to applications that aid their processes, often built on systems from CoinDesk Data & Indices, Daloopa, Dun & Bradstreet and FactSet, according to Sid Nag, founder and chief research officer of Tekonyx.
“The strategic asset is not Gemini by itself, but Google’s ability to connect Gemini Enterprise through the connectors that are talked about to licensed data repositories in the area of financial industries,” Nag said.
He added that the vendor could be superior by having a “strong enterprise control plane.”
Nevertheless, the new Gemini Enterprise financial and legal systems show “Google is correctly shifting enterprise AI conversation from model capability to industry work for execution,” Nag said.