By: Marily Nika, AI Product Lead at Meta
During an interview about AI I came up with a quote: “All Product Managers will be AI Product Managers in the future” and my quote went viral. Let’s explore the reasons for the viral appeal.
I feel incredibly fortunate to have found myself at the right place, right time when I pursued my PhD in an unconventional field that involved Machine Learning more than a decade ago. . I have since been bringing AI products to life at big tech companies like Google and Meta. I know the exhilaration and the challenges that come with steering into the fast-evolving world of AI in product management, and I have to say that it is a journey. A journey of constant learning that can be immensely rewarding. In this light, I wanted to share some insights on AI products, how to measure success and why getting comfortable with AI is crucial for leaders to succeed in this new era.
It is important to note that it’s not just a fleeting trend, but something that’s reshaping how we build and manage products. The shift is here to stay. Being at the forefront of this change, especially as the founder of the first AI Product Management Bootcamp, I get to work with product managers every single day that want to change their workflows and enhance their products with smart features. The first question I always get is:
How is AI relevant to my product?
In this dynamic era, figuring out how to integrate AI into your product can feel like a necessity. But, what does it actually mean, and how does it add tangible value to the solutions we offer to users?
Often, the concept of AI can seem overwhelming, synonymous only with advanced robots and complex computer systems. However, after having worked with a handful of product managers that truly want to enter the world of AI, I’m here to tell you that it’s a lot more approachable and likely already a part of your product’s ecosystem in ways you might not have realized.
First and foremost, AI is about making machines smarter, teaching them how to think, analyze, and learn from the data they process. This learning curve doesn’t just enhance their functionality; it creates a cycle where they continually evolve to become better, offering more nuanced solutions over time. The magic of AI lies in its ability to transform the basic structure of a product into a living entity that grows, learns, and adapts according to the ever-changing user preferences and market trends.
One of the most common arenas where AI is playing a substantial role is in matching platforms—be it marketplaces or mentoring apps. These platforms leverage AI to analyze vast arrays of data, helping to create matches that are not just accurate but deeply personalized. Imagine the power of an app that can pair a mentor and mentee based on a rich analysis of their profiles, preferences, and even their interaction styles. It’s about creating connections that are meaningful and rewarding for both parties.
Furthermore, AI is revolutionizing the entertainment sector with recommendation algorithms. Take, for instance, platforms like Netflix, which uses AI to analyze your viewing patterns, the kind of shows you like, and even the time you generally prefer to watch. Using this data, it then suggests shows that align with your taste, enhancing your viewing experience and making your leisure time more enjoyable. It’s like having a personal assistant who knows your preferences inside out, constantly working behind the scenes to curate a list of shows just for you.
Even in seemingly mundane tasks, AI is making significant strides. Consider a simple visit to the grocery store. AI can predict the items you might need to restock with remarkable accuracy, making your shopping experience smoother and more efficient. It analyzes patterns in your purchase history and even takes into account seasonal trends to offer predictions that are spot-on.
Yet, the beauty of AI is that it often works silently in the background, seamlessly integrated into the fabric of the product. It’s quite possible that you have already employed AI functionalities in your product without even realizing it. From streamlining processes to enhancing user engagement, AI is quietly revolutionizing the product landscape, making experiences more personalized, intuitive, and user-friendly.
What does success mean in AI Products?
In a recent post in my newsletter, I discussed what success looks like when it comes to AI products. The more we venture into this fascinating field, the clearer it becomes that measuring success isn’t a straightforward equation. It involves a multi-faceted approach, similar to making the perfect cocktail — a balanced blend of different metrics that harmonize to create a comprehensive view of your product’s health and impact.
My equation for AI product success is:
AI Success = AI Proxy Metrics + Product Health Metrics + System Health Metrics
1. AI Proxy Metrics
At the core of any AI product lies its underlying algorithm, a vital element that dictates its performance and accuracy. When we talk about AI Proxy Metrics, we’re referring to the actual precision and reliability of these algorithms in achieving the intended outcomes. It’s essential to scrutinize these metrics closely as they can offer insights into the effectiveness of your AI elements. Consider it as the heartbeat of your AI product, the better it functions, the healthier your product is.
2. System Health Metrics
Next up are System Health Metrics, which, though not directly tied to our primary responsibilities, hold paramount importance. These metrics throw light on the overall well-being of the systems that host and support your product. From server response times to uptime percentages, these metrics can significantly influence a user’s experience with your product. It’s like the environmental factors that, while not directly influencing an individual’s health, play a significant role in determining overall well-being.
3. Product Health Metrics
Then we have the Product Health Metrics, the more traditional parameters that every product manager keeps a close eye on. These encompass a range of factors, from user engagement levels to retention rates, and offer a glimpse into how well your product is received and utilized by your audience. Think of these as the vital signs that offer an immediate insight into the product’s current state and potential trajectory.
Understanding that these three buckets are interconnected is vital. Your AI product cannot truly flourish unless all categories co-exist in a harmonious state. This harmonious existence is not about merely monitoring these metrics but understanding how they influence each other, creating a synergy that propels your product towards success.
Finally, it is essential to remember that success in AI extends beyond profits or user growth. It encapsulates a broader spectrum where ethical choices, user satisfaction, and sustainable innovations hold a prominent place. It’s about creating products that not only thrive in the market but also foster a positive, responsible, and joyful user experience.
As a leader in this field, you have the exciting opportunity to explore the untapped potential of AI further. By integrating AI into your product, you’re not just staying ahead of the game but also offering solutions that are cutting-edge, user-centric, and incredibly innovative. It’s about fostering a product environment where technology meets empathy, where machines understand and cater to the unique needs of every individual, making lives simpler and experiences richer.
Asyou navigate this exhilarating journey, remember to approach AI with curiosity and openness. Dive into the vibrant world of AI, explore its multifaceted applications, and embrace the wonderful opportunities it brings to the table. After all, the future of product management is here, and it is intelligent, intuitive, and incredibly exciting.
ABOUT THE AUTHOR
Based in Silicon Valley, Dr. Marily Nika is an award-winning AI Product Management leader & one of the world’s top AI educators with 10+ years of experience building AI products at Google & Meta. Marily earned a PhD in Machine Learning at Imperial College London and is also an author, a TED AI speaker and an Executive Fellow at Harvard Business School.