Upskilling and reskilling
技能升级与再培训

A New Framework for AI Upskilling Across Your Organization
构建适用于您组织的人工智能技能提升新框架

Dan Brodnitz
Authored byDan Brodnitz 丹·布罗德尼茨

Head of Global Content, LinkedIn Learning (he/him)
LinkedIn Learning 全球内容主管（他/他）

May 8, 2024  2024 年 5 月 8 号

Illustration of a woman holding a tablet and developing her AI skills.

Overwhelmed by the pace and complexity of helping your organization gain AI skills? You’re not alone. 
在帮助组织提升 AI 技能的过程中，是否因速度和复杂性而感到力不从心？你并非独自一人面对这种挑战。

The 2024 Annual Work Trend Index from Microsoft and LinkedIn, released today, surveyed 31,000 people in 31 countries and revealed that AI is already changing the world of work. Fully 75% of knowledge workers now use AI at work, citing benefits like saving time, becoming more creative, and enjoying their work more. The report also found that while 79% of leaders agree AI adoption is critical to remain competitive, 60% of leaders worry their organization’s leadership lacks a plan and vision to implement AI. 
微软与领英今日发布的《2024 年度工作趋势报告》指出，人工智能正改变职场格局。该报告针对 31 个国家的 31,000 人进行调查，发现高达 75%的知识型员工在工作中应用 AI，他们认为 AI 有助于节省时间、激发创造力并提升工作满意度。同时，报告揭示，虽然 79%的领导者认同采用 AI 是保持竞争力的关键，但有 60%的领导者对其组织领导层在 AI 实施方面缺乏明确计划和愿景表示担忧。

“The urgency every company is feeling to build AI skills gives talent development pros a new seat at the table,” says Aneesh Raman, workforce expert at LinkedIn. “The biggest thing that will set any organization up for success is building a culture of continuous learning.”
“每家公司都迫切需要构建 AI 技能，这使得人才发展专家在决策中占据了一席之地，”LinkedIn 的劳动力专家 Aneesh Raman 指出。“任何组织要想成功，最关键的是培养一种持续学习的文化。”

This moment requires both thinking differently and a new plan for upskilling your employees. Talent development teams must help their organizations take a strategic, personalized approach to learning AI skills across levels.
当前形势要求我们不仅要有创新思维，还要为员工制定新的技能提升方案。人才发展部门应引导组织采取策略性、定制化的方式，在不同层级普及 AI 技能学习。

We’re here to help with a framework to upskill employees across a wide range of roles and levels of proficiency, from project managers, marketers, and administrative assistants requiring introductory AI knowledge to engineers who require highly technical skills to build and deploy company-specific AI systems. To jump-start your organization’s upskilling efforts, we’ve unlocked learning paths featuring more than 50 LinkedIn Learning courses, including a brand new course released today that walks you through this framework and offers practical guidance on how to lead your AI upskilling efforts. These courses are unlocked and free to access through July 8, 2024.
我们提供了一个框架，旨在帮助提升员工在各种职位和技能水平上的能力，无论是需要初步人工智能知识的项目经理、营销人员和行政助理，还是需要高阶技术技能以构建和部署公司特有 AI 系统的工程师。为推动您组织内的技能提升，我们已开放了包含 50 多门 LinkedIn 学习课程的学习路径，其中包括今天新发布的课程，该课程将详细介绍这一框架，并提供领导 AI 技能提升的实用指南。这些课程现已开放，免费访问期限至 2024 年 7 月 8 日。

A new framework for AI upskilling 
提升人工智能技能的新框架

In this new era of work, AI skills will be critical for nearly every role. But the level of AI readiness will vary: An entry-level sales representative, seasoned marketing professional, data analyst, and engineer will all need different skills to incorporate AI into their day-to-day work.
在这个工作的新时代，AI 技能对几乎所有职位都至关重要。然而，AI 的准备程度因人而异：无论是初级销售代表、资深营销专家、数据分析师还是工程师，都需要根据自身职责掌握不同的 AI 技能，以便将其有效融入日常工作。

It can be complex to navigate these different use cases; that’s why the LinkedIn Learning team crafted a five-level framework with a structured learning model to upskill your organization on AI. We built the framework utilizing insights from LinkedIn’s 1 billion members across 200 regions and countries; consulted LinkedIn Learning instructors who are some of the top AI experts in their field; and validated the model with LinkedIn’s top AI engineering experts across R&D and IT.
应对这些多样的应用场景可能颇具挑战；因此，LinkedIn Learning 团队精心打造了一个五级框架，采用系统化的学习模式，旨在提升您组织在人工智能领域的技能。我们基于 LinkedIn 遍布 200 个地区和国家的 10 亿会员的洞见构建了此框架；并咨询了 LinkedIn Learning 中在 AI 领域颇具权威的专家讲师；最后，通过 LinkedIn 顶尖的 AI 研发和 IT 工程师对模型进行了验证。

AI Upskilling Framework: Build business-critical AI skills at every level of your organization.

The framework is organized into five levels of AI expertise. The first two levels contain foundational AI knowledge that all employees will need, while the top three levels require deep technical skills and specialized expertise: level 3 is designed for business power users, developers, and data engineers; level 4, for machine learning engineers; and level 5, for cloud specialists, cybersecurity professionals, data scientists, researchers, and those preparing for tech certifications.
该框架将人工智能技能分为五个等级。前两级涵盖所有员工必备的基础 AI 知识，而高阶三级则要求具备深厚的技术能力和专业知识：第三级面向业务高级用户、开发者和数据工程师；第四级针对机器学习工程师；第五级则面向云计算专家、网络安全专家、数据科学家、研究人员以及备考技术认证的人士。

Check out how to upskill employees on AI at each of these levels:
了解如何在各个层面上提升员工的人工智能技能：

  1. Understanding: Building an AI foundation for all employees
    理解：为全体员工打造人工智能基石     
  2. Applying: Helping all employees apply AI to everyday work
    应用实践：助力全体员工在日常工作中融入人工智能技术
  3. Building: Creating with AI for business power users and developers
    构建：运用人工智能为商业领域的专业用户和开发者打造创新方案
  4. Training and Maintaining Models: Leveling up skills for engineers who are training and maintaining AI models
    模型训练与维护：提高工程师在人工智能模型训练和维护中的专业技能
  5. Deeply Specializing: Empowering technical and R&D specialists with AI tools
    深度专精化：借助 AI 工具增强技术与研发专业人员的能力

Some of the levels of upskilling should happen concurrently — for example, you may introduce general AI learning to your whole organization while you launch hands-on skill building to certain functional roles and deep specialization to highly technical engineers in parallel. While rolling out AI upskilling can feel overwhelming, your IT and tech teams, internal AI experts, and LinkedIn’s courses and insights will all help your organization thrive in this new era of work.
技能提升的某些阶段宜同步开展——例如，您可以在全组织范围内推广通用 AI 知识的同时，针对特定职能角色开展实践技能培训，并为技术精湛的工程师提供深度专业化的课程。尽管 AI 技能提升的实施可能颇具挑战，但您的 IT 和技术团队、内部 AI 专家以及 LinkedIn 提供的课程和洞察，都将助力您的组织在新时代的工作环境中茁壮成长。

Let’s take a deeper dive into what upskilling looks like at each level of employee AI expertise — along with steps you can take and unlocked courses to start making immediate progress.
让我们深入了解在员工 AI 专业知识的各个层级上，技能提升的具体表现——并探讨您可以采取的措施以及可解锁的课程，助您即刻迈出提升的步伐。

Level 1 / Understanding: Building an AI foundation for all employees 
第一阶段 / 理解：打造全体员工的人工智能基础

To begin your organization’s AI journey, every employee — from business leaders to creatives to tech professionals — will need to understand AI basics.
开启您组织的 AI 之旅，每位员工，无论是企业领导、创意人员还是技术专家，都需掌握 AI 的基本概念。

Help your employees understand what AI can help with (first drafts of emails, finding patterns in data) and what it can’t help with (human-to-human connection, relationship building). From there, it’s important to share a consistent message around how AI should be used based on your own organization’s goals and guardrails, including guidelines for responsible AI use. 
协助员工认识 AI 在哪些领域能提供帮助（例如撰写邮件初稿、识别数据中的模式），以及它无法涉足的领域（如人际沟通、建立关系）。随后，根据组织的目标和界限，传达一致的 AI 应用信息至关重要，同时包含负责任使用 AI 的相关指南。

“Over the next few years, we’ll see people who have the same job title, but doing entirely different work,” says Doug Rose, AI strategist, trainer, organizational change consultant, and LinkedIn Learning instructor whose course Introduction to Artificial Intelligence is featured in this level. “It won’t just be about learning how to interact with AI systems but also about getting better at tasks where humans still have a distinct advantage.”
“未来几年内，我们会发现尽管职位名称相同，人们的工作内容却大相径庭，”AI 战略家、培训师、组织变革顾问兼 LinkedIn Learning 讲师 Doug Rose 指出，他的课程《人工智能导论》在本级别中备受推崇。“这不仅仅是学习如何与 AI 系统协作，更在于提升人类在特定任务上的独特优势。”

But if your organization is just getting started with AI, you’re in good company. 
如果您的组织正开始涉足人工智能领域，那么您是众多探索者中的一员。

“We’re still figuring a lot out in the AI space, like I’m sure many organizations are,” says Terence Morley, VP of global talent development at NBCUniversal. “We’re excited about AI’s potential to fast-track learning, help leaders in the moment, and improve performance.”
“我们仍在人工智能领域探索许多未知，正如我相信众多机构所经历的那样，”NBC 环球全球人才发展副总裁 Terence Morley 说道，“我们对人工智能加速学习、实时支持领导者以及提高绩效的潜力感到振奋。”

Expert example: When Kraft Heinz was planning its 2023 Ownerversity Day, an annual 24-hour global learning event to accommodate employees across time zones, they decided on the theme “Revolutionizing Creativity and Collaboration Through the Power of AI.” 
专家案例：卡夫亨氏在筹备 2023 年的 Ownerversity 日时，这一年度 24 小时全球学习盛事旨在覆盖不同时区的员工，他们选定的主题是“借助 AI 之力，重塑创造力与合作”。

They focused learning on three topics to craft a foundational knowledge of AI:
他们聚焦于三个主题，旨在打造人工智能的基础知识体系：

  • “The first was What is Generative AI,” says Pamay Bassey, Kraft Heinz’s chief learning and diversity officer. “To kick off the conversation, we first explored what AI is, how it’s intended to be used, its power, and the challenges that are faced when considering and leveraging AI. We explored traditional and generative AI so people had a strong foundation.”
    “首问便是‘何为生成式 AI’，”卡夫亨氏首席学习与多元官帕梅·巴希表示。“我们首先探究了 AI 的本质、应用意图、其强大之处以及在考量与运用 AI 时所遇挑战。通过涉猎传统与生成式 AI，为大家奠定了坚实基础。”
  • The second topic was How is AI Used at Kraft Heinz, an exploration of the AI projects and pilots that were already underway in the company. 
    第二个议题聚焦于“卡夫亨氏的人工智能应用”，深入分析了公司内部已启动的 AI 项目和试验。
  • The third was What Does AI Mean for Each of Us? “As we considered this question,” Pamay says, “we discussed the ways that AI can be leveraged both in our personal and professional lives.”
    第三个议题是“AI 对我们每个人意味着什么？”Pamay 提到：“在探讨这个问题时，我们讨论了 AI 在个人生活及职场中如何被应用。”

Read more: How to Host an AI Learning Day
深入了解：怎样组织一场人工智能学习日活动

Take the first step: Identify what teams (for example, compliance, IT, and legal) are charged with establishing policies and guidelines around the use of AI. Align early and often as they will be your go-to partners throughout the journey on everything from privacy and security considerations to details like what data can and cannot be inputted into AI. 
迈出第一步：明确负责制定 AI 使用政策和指导方针的团队（如合规、IT、法务），并与之保持早期且频繁的沟通。他们将成为你从隐私和安全考虑，到具体细节（如 AI 可输入哪些数据，不可输入哪些）全程依赖的合作伙伴。

Learning path for employees: Building AI Literacy
员工 AI 素养培养路径

Level 2 / Applying: Helping all employees apply AI to everyday work
二级/实践：助力全体员工在日常工作中运用人工智能

The second level is for employees who have gained basic AI fluency and are ready to get hands-on with AI. Core skills include chatbot prompting and collaborating with AI assistants, as well as how to think critically when using AI. Level 2 moves beyond education (how and why AI can help you with parts of your job) to practice, so people can learn firsthand how to harness AI for specific tasks and roles.
第二级针对的是那些已经掌握基础 AI 技能的员工，他们准备深入实践 AI 应用。核心技能涉及聊天机器人的提示设计、与 AI 助手的协同工作，以及在运用 AI 时如何进行批判性思维。这一级别不仅停留在理论教育上（即 AI 如何及为何能辅助工作），更侧重于实践，让员工能够亲身体验并掌握如何将 AI 应用于具体任务和岗位中。

This level is appropriate for all professionals, including leaders and managers. Every employee can benefit from topics such as building a generative AI strategy or using AI to foster a collaborative team culture.
此级别适用于所有专业人士，涵盖领导者和管理者。每位员工均可从诸如制定生成式 AI 策略或借助 AI 培育团队协作文化等议题中获益。

Expert example: PwC, which was recently honored by LinkedIn as a 2024 Top Company for career growth in the U.S., pledged to invest $1 billion over the next three years toward expanding and scaling its AI offerings across every level of the organization. To do so, they had to lay the groundwork for their 75,000 employees in the United States and Mexico.
专家案例：普华永道最近被领英评为 2024 年美国职业发展顶尖企业，宣布未来三年将投入 10 亿美元，旨在全面扩展和提升其人工智能解决方案，覆盖公司各个层级。为此，他们正为在美墨两国的 75000 名员工打下坚实基础。

“When it comes to learning and development at PwC, we know that a one-size-fits-all approach just doesn’t cut it,” says Leah Houde, chief learning officer at PwC. They first rolled out mandatory e-learning modules about how to use AI at PwC to all their employees. But they didn’t stop there: PwC paired those modules with in-person seminars, gamification, hands-on workshops, snackable video content, and access to generative AI tools to offer learning adaptable to different departments’ needs. 
“在 PwC，我们深知学习与发展不能一概而论，”首席学习官 Leah Houde 指出。最初，他们为全体员工强制推行了关于在 PwC 运用 AI 的电子学习模块。然而，PwC 并未止步于此，他们还辅以线下研讨会、游戏化体验、实践工作坊、精简视频内容及生成式 AI 工具的访问权限，以满足各部门不同的学习需求。

“We want our employees to feel empowered and engaged throughout their learning journey,” Leah says, “not intimidated or overwhelmed with emerging topics like gen AI.” 
“我们希望员工在学习的旅程中能感到充满力量和积极参与，”Leah 表示，“而不是对诸如生成式 AI 等新兴话题感到畏惧或不知所措。”

Take the first step: Reach out to team leaders (sales, marketing, your partners across HR) to assess how employees are using AI today so you can share examples company-wide and inspire people to get started. While you’re talking to those leaders, make sure you also know what their business goals are and you can speak to how AI aligns with them. Whether you allot some time at an all-hands, schedule a lunch-and-learn, or create a dedicated AI Learning Day, it’s important to build a culture of curiosity around AI and get people comfortable with digging in and learning. 
首先，联系团队负责人（包括销售、市场营销及人力资源等部门的合作伙伴），了解员工目前使用 AI 的情况，以便在全公司分享实例并激发大家的参与热情。同时，了解这些负责人的业务目标，并阐明 AI 如何与之契合。无论是通过全员大会、午餐学习会，还是设立专门的 AI 学习日，关键在于培养对 AI 的好奇文化，让员工乐于深入探索和学习。

Learning paths for employees: 
员工学习路径规划：

Learning path: Applying Generative AI as a Creative Professional
学习路径：作为创意专业人士应用生成式人工智能

Learning path: Applying Generative AI as a Business Professional
学习路径：商业专业人士如何应用生成式人工智能

Learning path: Applying AI as a Tech Leader
学习路径：技术领导者如何应用人工智能

Level 3 / Building: Creating with AI for business power users and developers
第三层级/建筑：助力商业高级用户及开发者利用 AI 创造价值

While the first two levels focus on using AI, the third is centered on creating with AI. For many L&D leaders, this is where collaborating with technical leaders on AI upskilling can drive the greatest business impact. 
前两级着重于 AI 的应用，而第三级则专注于利用 AI 进行创作。对众多学习与发展领域的领导者来说，这阶段与技术领导者联手提升 AI 技能，能带来最大的商业价值。

Level 3 includes business power users working with no- and low-code tools as well as seasoned developers. It covers skills like working with APIs (application programming interfaces) and getting hands-on practice with AI tools like Hugging Face and Semantic Kernel to do things like build custom GPTs for your organization. Employees at this level will benefit from hands-on practice, whether it’s building an AI application or using low-code methodologies to leverage large language models. 
第 3 级涉及的业务高级用户和资深开发者，他们运用无代码和低代码工具。此级别技能包括操作 API（应用程序编程接口），并通过 Hugging Face 和 Semantic Kernel 等 AI 工具进行实践，例如为组织定制 GPT。在这一级别的员工将通过实际操作获益，无论是开发 AI 应用还是采用低代码策略来运用大型语言模型。

Expert example: “We strongly believe that all of our people need a fundamental understanding of AI technology to advise clients through this transformation and to leverage it in their own work,” says Leah Houde, chief learning officer at PwC. “We also know that strategy needs to continue to evolve for all of our people — and for those in deeply technical roles.” Leah also explains that, for technical employees already fluent in AI basics, “intermediate training will help accelerate engineers’ skills development, making this corps of engineers some of the top talent in the field.”
专家案例：“我们坚信，所有员工都应掌握人工智能基础知识，以便指导客户度过这一转型期，并在自身工作中运用该技术，”普华永道首席学习官 Leah Houde 表示。“同时，我们也认识到，无论是全体员工还是技术岗位的专家，都需要持续更新战略。”Leah 进一步说明，对于已具备 AI 基础知识的员工，“进阶培训能促进工程师技能的快速提升，使他们成为该领域的佼佼者。”

After PwC rolled out beginner-level courses to all their employees as highlighted in level 2, they took concrete steps to link technical AI upskilling and talent development strategies:
正如第二级所述，PwC 向全体员工推出入门级课程后，便采取具体步骤，将 AI 技术技能提升与人才培养战略紧密结合：

  • Releasing intermediate courses to their 75,000 employees in the U.S. and Mexico 
    在美国和墨西哥，向 75,000 名员工推出中级课程
  • Starting to offer advanced courses and activities for their professional technologists and “gen AI super users” to further equip them with the knowledge and skills to drive innovation
    开始向专业技术人员及“生成式 AI 超级用户”提供高级课程与活动，以深化其知识与技能，助力创新推动
  • Actively recruiting talent from across business lines into an internal team of AI technologists
    从各业务线积极招募人才，打造一支内部的 AI 技术专家团队

Take the first step: As the 2024 Annual Work Trend Index from Microsoft and LinkedIn advises, it’s important that L&D pros prioritize rolling out AI to those functions that will see the most ROI first. Keep track of wins and learnings, and share learnings widely as you scale.
按照微软与领英的 2024 年度工作趋势指数建议，L&D 专家应首先将 AI 应用于投资回报率最高的领域。及时记录并广泛分享成功案例与学习心得，以便在推广过程中不断积累经验。

 According to a McKinsey analysis of 16 business functions, “just four — customer operations, marketing and sales, software engineering, and research and development — could account for approximately 75 percent of the total annual value from generative AI use cases.” So start a pilot program on AI upskilling with your developers and your organization will reap the benefits.
据麦肯锡针对 16 项业务职能的分析显示，“仅客户运营、市场营销与销售、软件工程及研发这四大领域，便可能占据生成式 AI 应用案例年度总价值的约 75%。”因此，开展面向开发团队的 AI 技能提升试点项目，将使您的组织收获显著效益。

Learning path for employees: Develop Your Skills with the OpenAI API
员工技能发展路径：借助 OpenAI API 精进自我

Level 4 / Training and Maintaining Models: Leveling up skills for engineers who are training and maintaining AI models
第 4 级/模型训练与维护：为参与 AI 模型训练与维护的工程师提供技能提升培训

While machine learning engineers have long used AI to build software and develop and train AI models, the momentum and speed of change to AI-driven software requires frequent upskilling and reskilling to help them stay on track. This pace of change only exacerbates an existing issue: Talent with deep technical expertise is both harder to find and more expensive to hire. IDC predicts a global shortfall of 4 million developers by 2025. This looming talent gap makes upskilling your technical talent mission critical.
长期以来，机器学习工程师借助 AI 构建软件、开发和训练模型。然而，AI 驱动软件的迅猛发展要求他们频繁地进行技能升级和再培训，以紧跟时代步伐。这种快速变化进一步凸显了一个问题：具备深厚技术专长的人才愈发稀缺且成本高昂。据 IDC 预测，到 2025 年全球将面临 400 万开发者的缺口。因此，提升技术人才的技能已成为当务之急。

Level 4 of the framework focuses on the skills needed by employees in engineering and coding-heavy roles who are building AI systems and products. Topics include deep learning and neural networks, as well as training, maintaining, and fine-tuning AI models.
框架的第四层级聚焦于从事 AI 系统和产品开发的工程及编码密集型岗位员工所需技能。涉及内容包括深度学习、神经网络，以及 AI 模型的训练、维护与精细调整。

L&D is well positioned to help these engineering leaders upskill their teams — both current employees and those new to the company — so they are better equipped to quickly and effectively deliver the AI-powered applications that the business needs. 
L&D 具备优势，可助力工程领导者提升团队能力，无论是老员工还是新成员，都能更高效地开发出企业所需的 AI 应用。

Take the first step: Meet with your senior engineering leaders and discuss two key questions: What AI skills do their teams currently have? What AI skills are they lacking? Set up a monthly time to sync so that reskilling can happen on an ongoing basis for your organization’s engineers. 
迈出第一步：与资深工程领导会面，探讨两个核心问题：团队现有的 AI 技能有哪些？还欠缺哪些 AI 技能？安排每月定期沟通，确保贵组织工程师的技能再培训得以持续进行。

Learning path for employees: Advance Your Skills in Deep Learning and Neural Networks
员工进阶学习路径：深化掌握深度学习与神经网络技术

Level 5 / Deeply Specializing: Empowering technical and R&D specialists with AI tools
深度专精第五级：为技术和研发专家提供人工智能工具，以增强其专业能力

Level 5 of the framework focuses on helping specialists roles — think DevOps, data scientists, and R&D teams — sharpen their skills in the cybersecurity applications of AI as well as AI cloud solutions like AWS Cloud, Azure, and Google Cloud Platform (GCP). 
框架第五级旨在助力专家角色，例如 DevOps、数据科学家及研发团队，提升他们在人工智能网络安全应用及 AWS 云、Azure、谷歌云平台（GCP）等 AI 云服务领域的技能。

This group of technical specialists has a particular challenge: The AI skills that they need change on a weekly basis, rather than a monthly basis. This rapid pace of change calls for continuous, in-depth skill-building to help specialists be more agile and productive. 
这群技术专家面临的特殊挑战是：他们所需的 AI 技能更新频率为每周，而非每月。如此迅速的变化节奏，要求他们不断深入地提升技能，以便更加灵活高效。

L&D pros can help this group by offering expert-taught courses that involve deep skill-building, hands-on practice, and certification prep, all of which is important to advancing both their individual careers and the business.
L&D 专家可通过提供专家授课的课程助力该群体，课程内容涵盖深度技能提升、实操练习及认证备考，这对促进个人职业成长和推动企业发展均至关重要。

Take the first step: For this super-specialized population that needs frequent upskilling, open and maintain regular, open lines of communication with your engineering and IT teams will be critical. One challenge technical talent often faces is making time for learning. So, L&D working alongside department leads to help technically skilled talent make time for regular upskilling will be critical — from working with managers to tie learning to career growth to rewarding top-learners.
对于这群高度专业化、需频繁提升技能的人员，首要任务是与工程及 IT 团队建立并保持定期、开放的沟通渠道。技术人才常遇到的难题是如何抽出时间学习。为此，学习与发展部门需与各部门领导携手，协助技术人才规划出固定的技能提升时间——无论是与管理者协作将学习与职业发展相结合，还是对学习表现突出者给予奖励。

Learning Path: Develop Your AI Skills as a Cybersecurity Professional 
学习路径：提升你作为网络安全专家的 AI 技能

Final thoughts: This is L&D’s moment
最终感想：L&D 正逢其时

Today’s Microsoft and LinkedIn report on the state of AI at work revealed that nearly half (45%) of U.S. executives are not currently investing in AI tools for employees and only a quarter (25%) of L&D teams globally plan to offer any generative AI training this year. 
微软与领英今日联合发布的职场人工智能状况报告显示，美国约半数（45%）高管尚未为员工投资 AI 工具，全球范围内，仅 25%的 L&D 团队计划本年度开展生成式 AI 培训。

So, employees are taking things into their own hands. The report showed that 78% of AI users are bringing their own tools to work, but without guidance or clearance from the top, organizations are missing out on the benefits that come from the strategic use of AI at scale. 
因此，员工们开始自行动手。报告显示，78%使用 AI 的员工将个人工具带入职场，然而缺乏上级的指导或批准，组织便无法充分利用 AI 战略性大规模应用所带来的优势。

And if you need to convince the C-suite to invest in AI learning, a recent study from IDC “The Business Opportunity of AI” showed that for every $1 a company invests in AI, it is realizing an average return of $3.50. 
若要促使高管层对 AI 学习进行投资，IDC 近期发布的《AI 的商业机遇》研究指出，企业每向 AI 领域投入 1 美元，平均能获得 3.50 美元的回报。

Companies that channel employee AI experimentation into an intentional strategy that drives bottom-line impact will pull ahead. Those that stand still will fall behind. And as an L&D pro, you’re in the driver’s seat to lead your organization to seize this opportunity. 
将员工的人工智能实验整合进一项有目的的策略，以此推动公司业绩的企业将占据优势。那些停滞不前的则会落后。作为学习与发展领域的专业人士，你正处在引领组织抓住这一机遇的关键位置。

This framework is intended to be a starting point to upskill every employee based on their specific level of AI readiness and technical proficiency. As you dig in and start to make it your own based on your company’s needs, stay on your toes — the AI landscape will continue to evolve and you’ll need to continue to be proactive, adapt, and refine your upskilling strategy. 
此框架旨在成为提升每位员工技能的基础，依据各自的 AI 准备状态和技术水平量身定制。随着你深入探索并根据公司需求进行个性化调整，请保持敏锐——AI 领域将持续演进，你需不断主动适应、调整并优化你的技能提升策略。

We at LinkedIn will be doing the same, continuing to bring you the latest expert insights and resources so you can lead your organization to AI literacy, one skill at a time. 
我们 LinkedIn 同样会持续努力，不断为您提供最新的专家洞见及资源，助您逐步引领组织迈向 AI 素养。

Want to learn more about enabling your own team? Our new LinkedIn Learning course A Practical Guide to Upskilling Your Organization on AI will help your L&D team understand how to use LinkedIn Learning’s AI upskilling content at each level of the framework. This course is unlocked through July 8, 2024.
想深入了解如何赋能您的团队吗？我们新推出的 LinkedIn 学习课程《AI 时代组织技能提升实用指南》将指导您的 L&D 团队掌握如何运用 LinkedIn 提供的 AI 技能提升资源，覆盖框架的各个层面。本课程至 2024 年 7 月 8 日免费开放。

The 2024 Workplace Learning Report: Explore now.

Topics: Artificial intelligence Top skills and courses Upskilling and reskilling
主题：人工智能 关键技能与课程 技能升级与重新培训

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