Taking Control of your AI Learning

Taking Control of your AI Learning

Last week, I shared that when it comes to AI adoption and empowering your people to harness AI tools, training is just the beginning. The next step is just as important: taking those lessons and continuing to learn. 

I see this disconnect everywhere: Companies invest heavily in training programs. Employees attend dutifully. Everyone feels good about checking that professional development box. And then... nothing changes.

The most successful leaders I know don't wait for their next training session to learn something new. They take radical ownership of their ongoing education.They understand that in our rapidly changing world, your ability to learn continuously and efficiently is what separates thriving from surviving.

This is particularly essential with AI, with tools constantly changing and evolving. 

So how do you actually do this? How do you take responsibility for your own learning without drowning in information overload?

The Art of Strategic Subscription

With countless newsletters, YouTube channels, podcasts, and classes to sign up for, it can be hard to know which resources are worth your time. 

Here's my counterintuitive advice: subscribe to more than you think you'll read.

I know it sounds crazy, but hear me out.

When someone tells me about a great newsletter or podcast, I immediately subscribe. Then I scan through everything for a month or two. If I find myself consistently skipping something, I unsubscribe without guilt.

This approach helps me discover what actually serves my learning style and current needs, instead of what just sounds good in theory.

What's valuable to me may not be as valuable to you. The only way to figure out your optimal learning diet is to experiment.

Right now, I'm loving Practical AI podcast, which shares 10 to 15 minutes of focused content, two or three episodes daily. I don't listen to all of them, but I scan through weekly and listen to the episodes that align with my learning interests.

Create Learning Systems That Work for You

The key is creating systems that help you learn efficiently. 

I set aside dedicated learning time and use filters to organize everything in one place. When it's learning time, I know exactly where to go and what to consume.

For podcasts, I use Overcast to create custom playlists. I have a daily playlist for regular listening, plus different queues for specific topics. When someone recommends a podcast, it goes into the appropriate queue until I'm ready to dive deep into that subject.

For newsletters, I have an inbox folder for AI content. Everything gets filtered there automatically, so I can process it all during my designated learning sessions.

I learned to code using YouTube videos, not formal courses. Why? Because I don't have the patience to sit through sequential lessons when I need to solve a specific problem right now.

Some people thrive with structured A-to-Z courses. Others (like me) prefer just-in-time learning that addresses immediate needs.

Know your learning style and lean into it, rather than forcing yourself through methods that don't work for you.

Use AI to Learn About AI (and Everything Else)

Here's where it gets meta: I use AI to accelerate my learning about AI.

When I wanted to learn about vibe coding, I went straight to Gemini (which I'd heard was particularly good at planning and coding guidance) and said:

"Hey Gemini, I heard you're really good at planning vibe coding. I want you to teach me. Walk me through the process step by step. Here's what I don't know...and here's what I do know..."

It created a personalized tutorial just for me.

You can take this even further:

👉🏽 "I only have 15 minutes a day to learn about [topic]. Create a schedule for me."

👉🏻 "Give me a playlist of relevant podcast episodes from five different experts, in the right order."

👉🏾 "I need some accountability. How should I structure my learning goals?"

AI becomes your personalized learning coach, adapting to your schedule, style, and current knowledge level.

The Future Belongs to Self-Directed Learners

The half-life of skills keeps shrinking. What you learned five years ago might be completely irrelevant today.

Organizations that invest in learning are taking an important first step. But your competitive advantage comes from what you do between formal training sessions.

The future belongs to those who can learn faster than the world changes around them. Taking responsibility for your learning means:

🔬 Being intentionally curious. Don't just consume content passively. Ask yourself: "How does this apply to my work? What would I do differently based on this insight?"

🚧 Setting boundaries. You can't learn everything. Focus on what serves your goals and let go of what doesn't.

📋 Creating accountability. Whether it's through AI, learning partners, or personal tracking systems, build in mechanisms that keep you consistent.

🚀 Applying immediately. Knowledge without application is just trivia. For every new concept, ask: "How can I use this within 48 hours?"

Your Turn

How are you taking ownership of your learning? What systems have you created to stay ahead of the curve?

Whether you prefer sequenced, classroom-style learning or independent learning based on immediate problem-solving, I’m curious to know how you’re approaching continuing education in AI. 


What I Can’t Stop Talking About

  • The weak link in your AI strategy might be communication. If your stakeholders don’t know that you’re creating value with AI, you might need to rethink how you talk about it.
  • You don’t have to build your AI strategy alone. Work with other senior leaders to level up the plans you have for the future. My Samudra AI Innovation Exchange group starts soon – learn more and apply!

My Upcoming Appearances/Travel

Shahdad moradi

Anesthesiology Resident (PGY-2) | Founder @ Medora™ — HealthTech & Clinical Systems | Patient Safety • Supply-Chain Transparency • AI for Trustworthy Care

1mo

Charlene, I couldn’t agree more on the importance of taking ownership in AI learning. What resonates with me is how this mindset goes beyond personal growth it’s the same principle we apply when building resilient systems in healthcare. In projects like Medora, we use AI not only to personalize knowledge but also to anticipate risks in drug supply chains. Just as individuals shouldn’t wait for the next training session, healthcare systems shouldn’t wait for the next crisis. Proactive learning and proactive systems share the same DNA: responsibility, adaptability, and foresight.

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Michael Loboyko

Building AI solutions, custom GPT agents, software development, and human-centered interfaces | Co-founder@Empha Studio | Co-founder@Meetia.io

2mo

Continuous learning is less about big trainings and more about building systems that make growth part of your daily flow.

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Denise Gosnell, Ph.D.

Graph Theorist | Decision Architect | Brilliant Misfit

2mo

The skill is definitely lifelong, continuous learning. You nailed it here.

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Dylan Gambardella

Founder of Different Health & Next Gen HQ

2mo

So much opportunity here — great push to use ai to meet us where we are!

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Ryan Mullins

Global AI Implementation | Enterprise Automation & GenAI Systems in Regulated Environments | Founder, Renew | Building Scalable AI Frameworks for Global Brands

2mo

Most people wait for the company to hand them a course. By then it’s too late. With AI especially, the only way is to test it in your own flow. See where it sticks, see where it breaks. I’ve learned more from running messy pilots in real work than from any structured programme. Responsibility isn’t about hoarding content. It’s about trying one thing today and proving it works. That’s how trust builds.

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