内容来源：https://aibusiness.com/generative-ai/dealing-with-ai-s-effect-on-jobs-and-opportunities-in-data

内容总结：

AI重塑职场：从“执行者”到“构建者”的转型浪潮

在生成式AI技术快速渗透各行各业的当下，企业如何选择首个AI应用场景？行业专家指出，应优先关注那些能“提升人类信息体验”的领域。然而，AI带来的不仅是效率提升，更引发了一场深刻的职场角色变革。

在近日举行的2026年高德纳数据与分析峰会上，数据管理供应商Atlan分享了其“AI优先”战略下的内部转型实践。这家印度AI厂商正引导其工程师团队从亲自编写代码，转向教导AI智能体（如Claude Code、Cursor等工具）进行编程；市场部门员工则从直接策划营销活动，转为构建并训练能完成该任务的AI智能体。

“作为一家公司，我们正努力践行‘人人皆可成为构建者’的理念，”Atlan数据与AI战略总监奥斯汀·克罗恩茨表示，“这使我们的开发流程显著更敏捷，能更快地将想法付诸实践。”

Atlan的案例折射出许多组织在AI自动化浪潮下面临的普遍压力与应对。近期，多家科技公司裁员时均提及AI技术的影响，即便是数据工程师和数据科学家也未能置身事外。“他们都在担心自己的工作，”国际体育博彩公司Entain PLC的数据信任与全球主管保罗·贝尔坦言。

尽管裁员新闻频现，但高德纳研究发现，企业对数据与分析团队的投资仍保持高位。当前，AI对就业的影响更侧重于“重塑岗位定义”——员工的价值不再局限于岗位描述，而更取决于其贡献的技能以及与AI技术、AI智能体协同工作的能力。

高德纳分析师乔治亚·奥卡拉汉指出：“你的角色可能从开发者转变为验证者，负责审核和调整他人（包括人类和智能体）的工作。”她强调，人类才能与技能仍是交付团队的核心，但未来团队将是“人类专业知识与AI智能体结合”的融合型团队。

这种转型带来连锁反应：企业若想利用AI实现自动化，很可能需要对留任员工进行技能升级，因为公司需求随AI应用方向而变化。因此，企业必须审慎决定哪些领域交由AI主导，哪些仍需人类引领。

“这对大多数企业领导者而言是一个更艰难的决定，”高德纳分析师海伦·普瓦特万指出，“他们必须战略性地明确‘这是我们要让AI工作的领域’，并有效驾驭随之而来的变革与影响。”她补充道，如果让员工参与设计自动化流程，他们将更有参与感，更愿意接受日常工作发生的实质性变化。

招聘市场同样悄然生变。对许多企业而言，人才选拔的重点正从“经验”转向“既有技能”。斯坦利·马丁住宅公司技术开发与分析副总裁拉杰·提瓦里表示，他们更关注招聘“懂得如何提示AI、理解模型底层逻辑、愿意测试学习并容忍失败的数据专业人士”，并指出“好奇心……此时比资历更重要”。

尽管变革持续，但由于技术尚未成熟，AI技术带来的招聘与工作模式变化仍处于动态调整中。第一资本首席数据官艾米·莱南德表示：“我们都在实践中学习。在这个AI世界里，我们未来需要怎样的人才组合，仍有待观察。”

可以预见，在AI驱动下，职场正从以“经验”为中心转向以“角色与技能”为中心，而“人机协同”将成为未来高效团队的新常态。

中文翻译：

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如何选择首批生成式AI应用场景
要启动生成式AI项目，首先应关注能够优化人类信息交互体验的领域。

AI正推动企业从注重经验转向注重岗位职能，同时也促使团队对部分员工进行技能升级。

奥兰多报道——数据管理供应商Atlan通过实施"AI优先"战略，调整了营销人员与数据工程师等内部员工的工作任务。这一案例表明，随着AI技术发展，各行业岗位职能正在发生变革。

这家印度AI供应商已完成内部调整，要求工程团队转而使用Claude Code、Cursor等AI编程工具训练AI代理编写代码，而非亲自编码。在营销部门，公司鼓励员工构建并训练能自主策划营销活动的AI代理，取代人工策划流程。

"总体而言，公司正努力践行'人人皆可成为构建者'的理念，"Atlan数据与AI战略总监奥斯汀·克罗恩茨在2026年高德纳数据与分析峰会上接受采访时表示，"这使我们的开发流程显著更敏捷，能以前所未有的速度将创意付诸实践。"

Atlan对数据工程师和营销人员的职能调整，展现了企业应对AI自动化浪潮的典型策略。近期多家公司以AI技术为由削减岗位，甚至数据工程师和数据科学家也未能幸免这场就业危机。

"所有人都忧心自己的工作，"国际体育博彩公司Entain PLC数据信任与完整性全球主管保罗·贝尔坦言。

尽管AWS、Block等科技公司的裁员新闻令人不安，甲骨文也预计将削减团队规模，但高德纳研究发现企业对数据与分析团队的投资仍保持高位。当前AI对就业的影响更多体现在重塑岗位认知层面——员工价值不再取决于职位描述，而更注重其贡献的技能及与AI技术、AI代理的协作能力。

"你的角色可能从开发者转变为验证者，负责审核和调整人类或AI代理完成的工作，"高德纳分析师乔治娅·奥卡拉汉在技术研讨会上指出，"人才技能的价值始终是交付团队的核心，未来这些团队将融合人类智慧与AI代理，形成更具生产力的AI赋能融合团队。"

众多企业试图用AI实现自动化的连锁反应是：他们必须对留任员工进行技能升级，因为企业需求会随AI应用方向而变化。

这正是企业必须审慎决策的关键——明确哪些领域交由AI自动化，哪些仍需人类主导。

"这对企业领导者尤为艰难，他们需要战略性地明确'这是AI负责的领域，我们将有效应对由此产生的变革与影响'，"高德纳分析师海伦·普瓦特万解释道。她补充说，若能让员工参与AI自动化决策过程，企业更易获得成功。"当员工主动表示'让我们优化这个体验并参与设计'时，他们会更投入，更愿意接受日常工作模式的重大变革。"

招聘领域也正发生深刻变化。对许多组织而言，人才需求正从看重经验转向侧重现有技能。

"我们重新聚焦于招聘擅长提示工程的人才，特别是那些理解AI模型底层逻辑、勇于测试学习并能承受失败的数据专家，"斯坦利·马丁住宅公司技术开发与分析副总裁拉吉·提瓦里表示，"好奇心此时比资历更重要。"

他透露公司目前仍以人力主导，但正在开发完全脱离人工的AI系统，例如自动生成房屋贷款最终条款文件。"我们将这项工作端到端自动化建模后集成至ERP系统，解放人力去从事更高价值的工作。"

第一资本银行首席数据官艾米·莱南德指出，由于技术尚未成熟，AI引发的招聘与工作模式将持续动态变化。"我们都在实践中学习，未来AI世界需要怎样的人才组合仍有待观察。"

英文来源：

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AI is leading to a greater focus on roles rather than experience. It’s also leading teams to upskill some workers.
ORLANDO -- With an AI-first strategy, data management vendor Atlan has shifted the tasks that internal workers, such as marketers and data engineers, do, showing that as AI advances, roles are changing across industries.
The India-based AI vendor has made internal changes requiring its engineering teams to teach AI agents to code rather than code themselves, using either Claude Code, Cursor, or another AI coding tool. On the marketing side, employees are encouraged to build agents that they train to build marketing campaigns, rather than building the campaigns themselves.
"Generally speaking, as a company, we're all trying to embody the concept of everybody can be a builder," said Austin Kronz, director of data and AI strategy at Atlan, during an interview at the Gartner Data & Analytics Summit 2026. "It makes our development process significantly more agile. It allows us to act on ideas a lot faster than we would have."
The change Atlan made in the roles of its data engineers and marketers is an example of how one company has responded to the pressure many organizations face as AI automates some jobs and tasks, such as coding. In recent months, many companies have eliminated jobs while blaming AI technology. It's an employment crisis that even data engineers and data scientists are not immune to.
"They're all worried about their jobs," said Paul Bell, global head of data trust and integrity at Entain PLC, an international sports betting and gambling company, in an interview.
While that concern seems well-founded with headlines about tech companies like AWS and Block laying off people, and Oracle expected to eliminate teams and jobs, Gartner research has found that investments in data and analytics teams remain high. While AI is affecting jobs, it is more -- for now -- reorienting how jobs are perceived. Instead of employees being valued by the description of their jobs, they are now valued more by the skills they contribute and by how they work with AI technology and AI agents.
"Your role may shift from being a developer to acting more as a validator, where you review and adjust work by others, humans and agents," said Gartner analyst Georgia O'Callaghan, during a keynote presentation at the tech research firm's conference.
"The value of human talent and skills will still sit at the core of delivery teams, but these teams will now combine human expertise with AI agents to make more productive AI-powered fusion teams," O'Callaghan said.
Moreover, a ripple effect of many companies trying to use AI to automate is that they will likely have to upskill the employees they keep, because companies' needs change depending on what AI is used for.
This is why enterprises and businesses must pay close attention to which areas they want AI to automate and which they want people to lead.
"That's a tougher decision for most business leaders because they have to say strategically, 'this is the area where we want AI doing the work, and we're going to navigate the change and the implications of that effectively,'" Gartner analyst Helen Poitevin said during an interview.
She added that businesses will find success if they give their human workers a chance to help decide what automating with AI agents or AI technology looks like.
"If they're motivated to say 'Okay, let's make that experience better and be part of designing it,' they will feel more engaged and more ready to accept the substantial change it means for their day-to-day work," Poitevin said.
Another change that's happening comes on the hiring front. For many organizations, the talent they need is no longer as much about experience and more about the skills potential employees already have.
"We've refocused hiring individuals that are skilled with understanding how to prompt, specifically data professionals that understand the under-the-hood abstraction of what's happening with these models and folks that are willing to test and learn and fail," said Raj Tiwari, vice president of technology development and analytics at Stanley Martin Homes. "Curiosity … goes a long way. It's really more of an individual perspective rather than tenure at this point."
He added that, for the most part, Stanley Martin Homes is human led, but the company is developing AI systems that take the human completely out of the loop, such as creating a closing house journal (the document that provides the final terms of a house loan).
"What we've done is extracted that and essentially modeled end-to-end with automation back into our ERP system," Tiwari said. "That's low-value effort, and hopefully humans can move to higher-value efforts."
The continuous change in hiring and work due to AI technology will always be in flux because of the immaturity of the technology, said Amy Lenander, chief data officer at Capital One.
"We're all learning as we go through this," Lenander said. "It's yet to be seen what talent mix we're going to need in this AI world."