思想领袖
从提示到Agents:AI如何重组营销团队
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在基因AI的前几年，市场营销者一直是其最早的采用者之一，学习如何促使和要求AI集思广益运动思想，创建大纲，总结研究，以及草稿副本。 该技术使个人任务更快，但营销工作的基本结构基本不变。 一名营销员查明了一些需要做的事情，向大赦国际提供了指示并审查了结果。
今天，这个时代正在迅速演变，以AI为合作者。 AI从一个等待指示的工具发展到一个更接近于常备队友的工具，能够跨多个步骤工作，分析信息，进行越来越复杂的工作流程。 这种范围更广的作用的影响远远超出了生产力。 随着agents被嵌入营销中，它们正在改变我们花费的时间所做的事情，并最终改变团队本身的结构。
大赦国际从“帮助我写作”转到“帮助我思考”
我们已经看到AI如何被使用的变化。 Ahrefs的2026年AI在内容营销研究中发现，93%的受访者现在使用AI来创作内容，比一年前的87%有所上升。 但更有趣的变化正在那个头条号码下面发生。
用于数据分析的AI在一年中从28%跃升至60%，而关键词集群则从23%升至46%. 市场营销者并不只是要求AI在页面上写更多字。 他们要求它解释信息，找出规律
我们超越了基因AI的明显第一顺序应用：写更多的文字和创造更多的图像。 随着市场商对这些工作流程感到自在，AI越来越不像机器人实习生，更像一个有创意和分析性的对应者。 Agents是逻辑的下一步。
agent没有要求AI一次分析数据集，而是拥有持续监测数据的权力。 市场营销者不定期检查竞争者，搜索能见度或竞选表现，而是可以建立系统，在变化发生时注意变化和表面机会。 自动化单元正在从任务转向工作流程。
营销不断
这种转变从根本上改变了工作、生产力和成果的苛刻性。 而不是在周一有人检查排名的地方进行定期运营，而是每月审查竞争对手一次，并在季末分析agents运行时总是有胆量的竞选表现。 昨天的进程之所以存在，部分原因是人类注意力有限。 Agents没有同样的限制。
AI系统可以不断监控品牌的搜索能见度，分析变化，识别潜在原因，并标榜少数真正值得人类关注的发展。 可在竞争情报、内容更新、客户研究和运动优化方面出现类似的工作流程。 现代市场营销者的作用已经从不断收集信息转变为决定什么值得采取行动。
这一点很重要，因为AI的采用已经创造了更多的产出。 百分之八十五的AI用户在Ahrefs的研究中说AI使得内容制作更快。 当每个营销团队都能生产更多的产品时，仅仅增加数量就变得不那么具有竞争优势。 判决变成不同者。
人类的味道
将人从营销工作流程中移除，然而，恰恰相反。 由于AI承担了更复杂的任务，产出不良的后果会增加。
写得不好的句子很容易解决。 声音的调子有缺陷或分析形成不良可能导致声誉风险或战略决策不良。 agent与人护栏持续运行，可以在任何人注意到之前识别和减轻错误。 因此
我们认为这种做法正在付诸实施。 Ahrefs的研究发现，89%的AI用户手动检查AI生成的内容，而66%的用户只有在人类审查后才会相信。 而非AI失败的证据。 人工智能被用在更有意义的工作上
审查人工智能生成的搜索策略的最佳人选是深入理解搜索的人。 这同样适用于付费媒体、创作、研究或任何其他学科。 随着人工智能更能创造精密的外观产出，有经验的从业者成为区分有说服力的工作与实际成功的工作的关键。
下一个营销团队不会只是拥有更多的AI工具
因此，最大的变化可能是组织上的。 从agents获益最大的团队不会简单地为每个营销商现有的工作流程添加另一个AI工具。 他们将重新考虑劳动分工本身：哪些工作应该持续进行，哪些决定需要人的专门知识，哪些人可以创造最大的价值。
这可能意味着在收集数据、编制报告格式和反复执行相同程序方面花费的时间减少，在解释信息、处理内容、制定战略、作出创造性判断和试验全新的方法方面花费的时间增加。
即时时代教营销者如何要求AI更快地做事情。 agent时代迫使营销团队回答一个更大的问题：什么值得人类关注？
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Thought Leaders
From Prompts to Agents: How AI is Reshaping the Marketing Team
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For the first few years of generative AI, marketers have been one of its earliest adopters learning how to prompt and asking AI to brainstorm campaign ideas, create outlines, summarize research, and draft copy. The technology made individual tasks faster, but the basic structure of marketing work stayed largely the same. A marketer identified something that needed to be done, gave AI an instruction and reviewed the result.
Today, that era is quickly evolving to using AI as a collaborator. AI has progressed from a tool that waits for instructions into something closer to an always-on teammate, capable of working across multiple steps, analyzing information, and carrying out increasingly complex workflows. The implications of this more expansive role go far beyond productivity. As agents become embedded in marketing, they are changing what we spend our time doing and, eventually, how teams themselves are structured.
AI Is Moving From “Help Me Write” to “Help Me Think”
We can already see this shift in how AI is being used. Ahrefs’ 2026 State of AI in Content Marketing research found 93% of respondents now use AI for content creation, up from 87% a year ago. But the more interesting change is happening beneath that headline number.
Use of AI for data analysis jumped from 28% to 60% in a single year, while keyword clustering increased from 23% to 46%. Marketers aren’t just asking AI to put more words on a page. They’re asking it to interpret information, identify patterns and help determine what to do next.
We have moved past the obvious first-order applications of generative AI: writing more words and creating more images. As marketers become comfortable with these workflows, AI is becoming less of a robotic intern and more like a creative and analytical counterpart. Agents are the logical next step.
Instead of asking AI to analyze a dataset once, an agent has the power to monitor data continuously. Instead of periodically checking competitors, search visibility or campaign performance, marketers can build systems that watch for changes and surface opportunities when they happen. The unit of automation is shifting from the task to the workflow.
Marketing Becomes Continuous
This shift fundamentally changes the cadence of work, productivity, and results. Instead of operating periodically where someone checks rankings on Monday, reviews competitors once a month and analyzes campaign performance at the end of the quarter agents run with an always-on cadence. Yesterday’s processes exist partly because human attention is finite. Agents don’t have that same constraint.
An AI system can continuously monitor a brand’s search visibility, analyze changes, identify potential causes, and flag the handful of developments that actually warrant human attention. Similar workflows could emerge across competitive intelligence, content refreshes, customer research, and campaign optimization. The modern marketer’s role has changed from constantly gathering information to deciding what deserves action.
This matters because AI adoption is already creating more output. Eighty-five percent of AI users in Ahrefs’ research say AI has made content production faster. When every marketing team can produce more, simply increasing volume becomes less of a competitive advantage. Judgment becomes the differentiator.
Humans as Tastemakers
There’s an obvious temptation to view increasingly autonomous AI to remove people from marketing workflows. However,, the opposite is true. As AI takes on more sophisticated tasks, the consequences of bad output grow.
A poorly written sentence is easy to fix. A flawed tone of voice or poorly formed analysis can lead to reputational risk or bad strategic decision-making. An agent operating continuously with human guardrails can identify and mitigate the mistake before anyone notices. That’s why expertise becomes the guardrail.
We see this approach being put into action. Ahrefs’ research found that 89% of AI users manually check AI-generated content, while 66% trust it only when a human has reviewed it. That scrutiny isn’t evidence that AI is failing. It’s a natural consequence of AI being used for more consequential work.
The best person to review an AI-generated search strategy is someone who deeply understands search. The same applies to paid media, creative, research or any other discipline. As AI becomes better at creating sophisticated-seeming outputs, experienced practitioners become essential for distinguishing work that looks convincing from work that will actually succeed.
The Next Marketing Team Won’t Just Have More AI Tools
The biggest change, then, may be organizational. The teams that benefit most from agents won’t simply add another AI tool to every marketer’s existing workflow. They’ll reconsider the division of labor itself: which work should happen continuously, which decisions require human expertise and where people can create the most value.
That could mean fewer hours spent gathering data, formatting reports, and repeatedly executing the same processes, and more time spent interpreting information, curating content, developing strategy, exercising creative judgment, and experimenting with entirely new approaches.
The prompt era taught marketers how to ask AI to do things faster. The agent era is forcing marketing teams to answer a much bigger question: what deserves human attention at all?
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