Strategies for Upskilling in an AI Environment

Having better coding copilots doesn’t mean we need fewer engineers, fewer data scientists, or that the skillset required today is any less demanding. Infact, it’s quite the opposite. If you’re a data scientist in 2024, here’s how you should be thinking about upskilling and using AI to elevate your career: 1️⃣ Use AI tools for your win: AI isn’t here to replace you; it’s here to make your life easier. Learn to leverage tools like Copilot to automate the boring stuff—so you can focus on the fun, challenging parts of the job. Think of it like having a really smart assistant that gives you a head start, not a crutch. 2️⃣Stay Curious About the “Why” Behind the Models: Just because AI can help you code faster doesn’t mean it can make the key decisions for you. It’s your job to understand why a model works the way it does, why certain data behaves a certain way, and what the implications are. The deeper you understand the tech, the more valuable you become. Most importantly, it is for you to understand how and when you will built AI applications that has an ROI. 3️⃣ Be the Voice of Responsible AI: AI is powerful, but it can also introduce bias or unintended consequences. In 2024, being the person who understands both the technology and the ethical side of AI is crucial. AI regulations are catching up quickly, and it’s important to stay informed. Whether you’re working with personal data or building models that impact people’s lives, understanding the legal landscape will ensure you’re on the right side of innovation. 4️⃣ Be the implementer: Data Scientst role is slowly evolving to be more engineering inorder to do from ML to MLOps (some LLMOps), so you should think about scalability, distributed computing, cloud architecture, and more. 5️⃣ Never Stop Learning: AI and data science are evolving at lightning speed. The only way to stay ahead is to keep learning. Models will keep changing, open-source will keep growing, toolkits will evolve- even though you don't need to everything, knowing what exists and what capabilities are supported is still very valuable.

AI writing is eating the world, and it illustrates how we're doing AI strategy wrong. Authenticity is everything. I help companies with AI strategy- it’s not about chasing better tech, it's enhancing what makes your product unique through the people who understand it. Talent Folks: Train your entire organization to use AI effectively, or watch your competitive advantage disappear. HR and Talent leads - this post is for you. I was alerted to this study by the great Ethan Mollick, one of the best AI thought leaders out there. Follow him. ++++++++++++++++++++ WHAT THE RESEARCH SHOWS: This Stanford study shows that AI-assisted writing has infiltrated business and society. - 18% of financial consumer complaint text is now LLM-assisted - 24% of corporate press release content is attributable to LLMs - 10% of job posting content in small firms is AI-generated (15% in younger firms) - 14% of UN press release content is modified by LLMs The study analyzed over 1.5 million documents and found a consistent pattern: minimal usage before ChatGPT (Nov 2022), explosive growth through mid-2023, then plateauing by late 2023. ++++++++++++++++++++ WHAT THIS MEANS FOR YOUR AI STRATEGY HR and Talent leads: You need to be leading this AI upskilling, and it doesn't start with recruiting. It starts with upskilling the best brains in your organization - those folks who don't love digital but are absolutely brilliant at what they do. These people are at risk because they may not jump on the GenAI train fast enough. But they are GOLD because AI has to augment brains, and you want it to augment the BEST brains in your org. They don't need to be techy!! They need to be able to communicate. That's it. ++++++++++++++++++++ WHAT TO DO NOW - 3 CRITICAL STEPS: 1. Upskill Your Domain Experts Your organization's domain experts are GOLD. AI must amplify their expertise, not replace it. When different people use genAI differently, you end up rewarding someone just because they're better at using AI, not because they're better at their job. 2. Require Leaders to Set New Performance Benchmarks Team leaders need to understand that genAI fundamentally changes how people work. Line managers across departments must grasp what productivity means when it's augmented by AI, because THEY define expectations and shape how teams use these tools. 3. Train Everyone - No Exceptions When you train your entire organization in AI, you capture the full value of your people's expertise. This is about amplifying what everyone already does well, creating a strategic advantage that's hard to match. ++++++++++++++++++++ WE CAN HELP. When your company is ready, we are ready to upskill your workforce at scale. Our Generative AI for Professionals course is tailored to enterprise and highly effective in driving AI adoption through a unique, proven behavioral transformation. It's pretty awesome. Check out our website or shoot me a DM.

🚫 STOP saying: “AI won’t replace you. A person using AI will.” It sounds more like a threat than a strategy. It shuts down the conversation instead of opening it. Because when employees express fear about AI, they don’t need clichés. They need a plan. Show you’re investing in them, not replacing them. Upskilling isn’t just about training. It’s about trust. So don’t just quote the internet. Show them where they fit in and how to grow. Here are 7 ways leaders can actually do that: 1. Start with listening ↳ Let them voice fears and skepticism ↳ Don’t respond with a TED Talk 2. Audit current roles ↳ Identify tasks that could be enhanced (not replaced) ↳ Talk openly about what AI can actually do 3. Invest in AI literacy ↳ Offer bite-sized, low-pressure workshops ↳ Demystify AI without overwhelming your team 4. Create low-stakes practice zones ↳ Let employees test tools with no deadlines ↳ Make it okay to play, learn, and even mess up 5. Celebrate progress, not perfection ↳ Highlight effort, experimentation, and curiosity ↳ Focus less on mastery, more on momentum 6. Pair learning with real work ↳ Show how AI can solve actual small problems ↳ Build skills while building solutions 7. Repeat the message ↳ “You’re part of the future.” ↳ “And we’re building it together.” No trust, no transformation. AI adoption isn’t just strategy, it’s a trust fall. 💬 What’s one step you’ll try with your team? ♻️ Repost if you’re investing in people, not just tech. 👣 Follow Janet Perez for more like this.