🌟 亲自体验AI：领导者应首先在个人层面使用AI，如分析会议记录、总结文章、测试新工具等，以此获得实际经验和信誉，并理解AI的基本原理，从而能够提出智能问题并识别智能答案。
🗣️ 将AI融入领导对话：在高管会议中讨论AI，询问团队如何使用AI，并强调实际案例，通过持续、一致的沟通减少AI的神秘感，推动文化变革。
📚 全面培训：AI并非IT部门专属，而是影响所有部门和员工。应建立面向全公司的学习旅程，从基础AI素养开始，逐步提供更深入的课程，包括内部培训、LinkedIn学习、供应商课程、开放式对话、AI午餐学习、实验展示、办公时间和AI黑客马拉松等。
🧪 鼓励实验：为团队提供尝试新事物的空间，允许低风险、低成本的试验，即使失败也要分享经验和教训，促进跨部门的交叉学习，为创新提供土壤。
🏆 奖励好奇心：认可和表扬团队在AI方面的创新尝试，如财务团队构建AI模型预测趋势，人力资源团队使用AI起草职位描述等，使好奇心具有传染性。
🛡️ 建立治理框架：在AI发展初期就成立跨部门的工作组，制定可接受的政策，平衡AI的边界、道德和风险控制，使合规成为合作伙伴而非障碍。
👀 展示示范：领导者应展示自己如何使用AI，如准备演讲、制定战略或创建个人头像，以此鼓励团队成员探索AI的可能性，因为如果高层不示范，其他人就不会行动。
🛠️ 投资可扩展工具：从免费工具开始可以，但最终需要投资企业级系统，以保护数据并跨业务扩展，确保工具易于使用和集成，避免因工具复杂或孤立而阻碍进展。
🗣️ 引入外部声音：与AI思想领袖和其他CEO定期交流，获取新鲜见解，避免孤立地构建AI未来，因为创新的想法往往来自公司外部。
🎯 将AI与使命相结合：所有AI相关的讨论都应回到公司的使命和价值观上，确保AI发展与用户、社区和公司的目标一致，避免AI沦为花哨或混乱的工具。
The future of leadership includes knowing how to build AI knowledge and culture into your company. You can’t delegate this. Not anymore. As AI reshapes industries, senior leaders must do more than observe. You need to engage. Not just with the technology, but with the people, the process, and the purpose behind it.
This is not about becoming a data scientist. It’s about building a leadership mindset that sees AI as a powerful tool for innovation, efficiency, and growth.
Here’s what I’ve learned from leading AI transformation in its early stages.
If you’re not curious, don’t expect anyone else to be. I started by using AI in small, personal ways. I would use it to analyze meeting notes, summarize articles, test new tools. Whether it is generating a document, creating a presentation, or writing a song, I used every app available. That hands-on experience gave me credibility and context.
You don’t have to master machine learning. But you do need to understand enough to ask smart questions and recognize smart answers.
Talk about AI in your exec meetings. Ask your team how they’re using it. Highlight real examples. The more it’s discussed, the less intimidating it becomes. Culture changes through repeated, consistent signals.
I often ask: “How could AI make this faster or better?” That one question reframes the conversation.
Big learning: AI is not an IT initiative. It touches marketing, legal, operations, sales, finance. It touches everyone in every department. We built a learning journey for our entire company, starting with basic AI literacy and then offering deeper tracks.
We used internal sessions, LinkedIn Learning, vendor-led classes, and open dialogue. AI lunch and learns. Experiment showcases. Office hours. AI hackathons.
If you punish people for trying new things, they’ll stop. Give teams permission to experiment. Low-risk, low-cost trials. Some failed. Some led to breakthroughs. We shared successes and lessons learned across departments. That cross-pollination made all the difference.
Someone on your finance team builds a new AI model to forecast trends. Recognize it. Someone in HR tests AI to draft job descriptions. Applaud it. Curiosity is contagious (if it’s noticed).
Leaders shape culture by what they praise, question, and invest in.
AI needs boundaries…ethics…guardrails. But it also needs momentum. We formed an AI working group early on with voices from legal, compliance, IT, and business units. They helped shape policies we could live with—not just write down.
Don’t let compliance be a blocker. Make it a partner.
Your team is watching. When I shared how I use AI to prep for speeches, develop strategy, or even to create headshots, it gave others permission to try. A CEO using it signals it’s safe to explore.
Free tools are fine to start. But at some point, you need enterprise-grade systems that protect your data and scale across the business. We invested in platforms that integrated with our systems and made adoption easier.
Don’t expect momentum if the tools are clunky or siloed.
I am regularly talking to AI thought leaders and other CEOs. One conversation with a startup founder sparked an idea. You never know where it will come from, but here’s what I have learned: don’t build your AI future in isolation.
Every AI conversation comes back to this: What are we trying to do for our users? Our communities? Our purpose? If AI doesn’t connect to your mission, it will drift into gimmicks or confusion.
Tie every experiment, every investment, every story back to your values.
This is not a one-off campaign. Building AI literacy and culture is an ongoing effort. Keep talking about it. Keep learning. Keep experimenting. We’re not close to being done – we are just starting.
I am a student of AI and am learning every single day.
Eventually, AI will stop being a topic and just become part of how you work.
And that’s when you know the culture has changed.
Image Credit: mayukh karmakar and badea iowana
The post Building AI Leadership and Knowledge in Your Organization first appeared on Skip Prichard | Leadership Insights.
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