Take a look at your LinkedIn feed – it’s probably flooded with AI courses, the latest tech breakthroughs, product launches, and updates on who’s winning the AI battle. Yup, we’re definitely deep in the AI era, and it’s transforming our daily lives in a big way.

Remember the good old days when everyone wanted to build websites, and then came mobile phones and apps. Well, now it’s the era of AI and chatbots. Like all trends, this one will eventually stabilize. But as this AI trend keeps on rolling, you might be wondering, “How can I keep up? Will I become irrelevant if I don’t grasp generative AI and chatbots? What would change in my profession as a Product Manager? And how on earth can I dive into this AI world?”

We’re gonna have to live through this era to see how the PM role evolves and how AI affects our daily lives. No crystal ball here, but I can drop a few tips from my journey breaking into AI as a PM.

Sure, there are plenty of courses on what AI is, its use cases, algorithms, tools, and even the ethical challenges. But there’s not much out there about the mindset a Product Manager should have in the AI world. It’s a complex topic, so let’s dive into how to get started with AI as a PM.

To cultivate an AI PM mindset, I recommend following a five-step framework:

1. Learn AI Concepts to Solve Real-World Problems:

Don’t get lost in an endless stream of AI videos and research papers. Instead, focus on real user problems where AI can make a difference. Dive into the tech behind it, understand basics like classification, prediction, summarization, Q&A, language generation, personalization, image and video processing. And don’t forget to jot down what you learn!

2. Speak the AI Language of Different Stakeholders

You’ll need to develop a vocabulary that allows you to communicate effectively with partners like Data Science, Analytics, Engineering, Marketing, and your product sponsor. You don’t have to be an expert in everything, but understanding their pain points and aspirations will go a long way. Get comfy with the AI life cycle, from gathering data, to model training, deployment and inference. The best way? One-on-ones. Ask them about their roles, challenges, and what gets them excited.

3. Find the Right Business Model support AI Costs

Don’t forget, AI-powered features come with computational costs. Especially if you’re dealing with a product serving 1Billion+ users. You must establish a suitable business model to justify the investment in AI.

4. Embrace Imperfection in AI

AI isn’t perfect, and it only gets better with time and more data. If you’re a perfectionist, AI will teach you some humility. It’s all about setting the right expectations with your users and stakeholders.

5. Build a Product with Active Feedback Loops

Personalization is the key to success for AI-powered features. Make sure you’ve got feedback loops in the most-used user journeys and use that data to train and fine-tune your AI model.

One of the biggest lessons I’ve learned as an AI PM is to be selfless. Sometimes, you’ll be tinkering with UI and product areas that aren’t directly in your wheelhouse. In those moments, you’re basically co-parenting someone else’s project.

So, stay calm and keep innovating with AI!

I was lucky enough to learn the ropes from the best in the AI biz – grateful to Fatima Kardar, Jaime Teevan, Luis Vargas, Saurabh Tiwary, Mat Velloso, Christian Liensberger, and Jeffrey Snover for believing in me and guiding me as an AI PM. It was a true honor to be part of the team on its epic mission! 🚀