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AI浪潮下,咨询顾问如何通过学习拥抱变革,保住工作
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在AI技术飞速发展的背景下,一位拥有10多年IT基础设施经验的Salesforce顾问Joey Monroe,深感职业危机,并主动学习AI,特别是Salesforce的Agentforce产品。他强调AI素养和提示工程(prompt engineering)对未来就业的重要性。通过深入研究、参与社区交流和内部认证,他成功转型并带领了首个大规模Agentforce生产环境的AI项目部署。 Monroe的经历表明,主动适应AI、掌握相关技能是应对职业变化的关键,并建议大家尽早开始学习,与AI建立对话能力,以在快速变化的职场中保持竞争力。

💡 主动学习AI以应对职业危机:Joey Monroe察觉到AI技术对IT行业的潜在冲击,意识到需要转型以保持竞争力。他选择深入学习AI,特别是Salesforce的Agentforce产品,将其作为个人和公司在市场上的差异化优势,并积极参与到AI解决方案的实际应用中。

🚀 提示工程与AI素养是未来关键:Monroe强调,掌握AI的基本知识和“提示工程”(prompt engineering)技能对于未来职业发展至关重要。他通过阅读官方指南、参与在线社区和实践操作,不断提升自己在AI领域的专业能力,能够自信地与客户讨论AI策略和应用。

🛠️ 理论结合实践,加速技能提升:通过参与实际的AI项目部署,Monroe的AI学习进入了更深层次。他发现从理论理解到实际应用的过程中,实际操作带来了更深刻的领悟,并能直观看到AI对客户业务成果的影响,这比纯粹的概念讨论更有价值。

📈 拥抱变化,保持前瞻性:Monroe的经历是职场人士应对技术变革的一个范例。他建议大家尽早开始学习AI,不必追求成为专家,但要保持信息畅通,建立与AI的对话能力。他认为,在每一次技术革命中,早期采用者总能获得先机,而落后者则会面临被淘汰的风险。

Joey Monroe.

This as-told-to essay is based on a conversation with Joey Monroe, a 34-year-old AI strategy advisor based in Oklahoma City. The following has been edited for length and clarity.

I'm a senior Salesforce consultant at BlueGator, specifically focused on Salesforce implementations in the nonprofit, arts, culture, and entertainment space. I've been here for almost six years, and before that, I spent about a decade working in IT infrastructure.

About a year ago, I felt like my job was at risk. AI systems started to pick up steam and be more widely implemented. It became glaringly obvious to me that tech would be the canary in the coal mine for what would happen in the broader markets, and I needed to adapt.

I decided to train myself in AI to create a market differentiator for my firm and myself. This opened up opportunities to help skill up others in the community and give back, which is something I really enjoy.

Now, I lead project implementations for nonprofit clients, helping them build out their systems and improve operations using Salesforce tools.

Until recently, I didn't have a formal AI plan

I started playing around with ChatGPT, Gemini, and other generative tools when they began making headlines.

When Salesforce rolled out its agentic AI product, Agentforce, in October 2024, everything changed. That tool started gaining attention not just from consultants like me but also from clients.

Clients would ask, "What do you think about this product? How should we use it? What would you suggest?" We didn't really have great answers yet because it was so brand new to everyone.

I realized we needed to get involved in a real way

Someone needed to take the lead on this at my firm. We needed to build the knowledge and expertise to answer client questions, have meaningful conversations about whether AI or Agentforce was right for them, and decide what business drivers to consider when taking the plunge. I decided that someone was going to be me.

I fully immersed myself in learning everything I could, both about Agentforce and about AI more broadly. I started reading prompt engineering guides from Google and OpenAI and then went deep into Trailhead, our internal training and learning platform.

It was super impactful to connect with others who were learning the same things. I had many connections within the Salesforce and nonprofit space who were jumping in to learn more about Agentforce. There's also the Salesforce-sponsored Agentblazer Community via Slack, which brings together people from all over the world who are interested in the product.

Seeing other people's thoughts around use cases, technical implementation, and strategy really helped cement that knowledge and add additional perspectives to consider when discussing AI strategy with clients.

I went through an internal certification process and kept building on my expertise.

Eventually, we landed a client who wanted a large-scale AI implementation

That was a pivotal moment for me: my first time working on a real-world deployment of agentic AI in a production environment.

We closed on that in May, and we're still actively building more agents for them. What I've learned is that once you move from theoretical understanding to actual implementation, the real learning begins.

It's one thing to talk about AI conceptually — it's another to see it influencing a client's real-world outcomes.

If I had to go back and structure my learning differently, I'd start with the fundamentals

This includes prompt engineering, basic AI literacy, and really digging into what generative AI is and how it works.

Time and impact were the biggest factors in determining my learning priorities. We had specific and relevant use cases that needed immediate attention, so a crash course was necessary to prepare us to move forward effectively with those use cases.

The products were also constantly evolving, on a weekly and sometimes daily basis. The biggest challenges were staying up to date.

I've heard a lot of people say, "There's so much content, I don't know where to start." That's very real, but once you build a strong foundation, the rest starts to make more sense.

When people ask me what's next for AI, I always say: nobody knows for sure

Everything's moving at lightning speed, but one thing is certain: being able to communicate the concepts and terminology of AI is going to be critical in just about every role.

I don't think we're quite at the stage of full-on replacement, but roles are going to change. There will be augmentation, and in some cases, displacement.

If that happens, you need to know how to shift and use AI to become more efficient, offload repetitive tasks, and focus more of your energy on high-impact activities that require a human touch.

People love to say "AI won't replace you — but someone who knows how to use AI will." I think that phrase is a little reductive, but its spirit is mostly true. The bigger question is: How are you preparing for that future?

One of the biggest surprises was how much of an art prompt engineering can be

I think for anyone super technical, that could be a bit jarring, but once it clicks, it clicks. For people who are great creative writers, it might come far more naturally than they might think.

I believe people should make an honest assessment of their roles, where the gaps are, and what might be able to be automated by AI now or in the near future.

Using this, they can roughly predict how at risk their role might be and where their strengths lie.

Now, I feel like my role is very secure

I've developed very practical and in-demand skills to build on, and I've gone through an actual implementation with the learnings to show for it. I can speak from a position of expertise and some level of authority without it being hyperbole or theory.

My biggest piece of advice is to start now, start early, and build conversational fluency with AI. You don't need to be an expert, but you need to be informed.

In every technological revolution, we've seen the same pattern: those at the bleeding-edge, early adopters, the mainstream, and the laggards. Trust me: no one wants to be a laggard.

Read the original article on Business Insider

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