The Rise of the AI Product Manager

In the 1980s, AT&T commissioned McKinsey to estimate the size of the cellular telephone market. Their report estimated that at the peak there would be 900,000 cellphone subscribers. That is a far cry from reality, today it is estimated that 85-90% of the world owns a phone. People love to bring up this example to poke fun at McKinsey and at humans' general inability to estimate. But if you look a little deeper this miss makes more sense. At the time they did the study, phones were expensive, unreliable, clunky, and just plain ugly. It is hard to feel like that is a product that will take off. Until recently, AI has been in somewhat of a similar boat. It can be expensive, requires technical expertise, and things can get ugly if it is used incorrectly. But things are changing.

Kaggle released their state of AI report for 2023. You probably don’t need a report to tell you that AI’s moment has arrived. It’s a huge buzzword and everyone is rushing to cram AI into their products. But despite the trendiness of AI, I found the report to be valuable, you can find a summary here. The big takeaway of the report is that while LLMs and GPT are the hot topics of today, there is so much more to AI. Many areas are ripe with opportunity. As I read through it, I started thinking about what this means for PMs. There have been AI waves before. Many companies have been using AI/ML/predictive analytics to power their products for a long time. But this time feels different. It feels like the entire tech industry will be caught by this wave. To be seen is if they ride that wave or drown. For product managers, there is an opportunity to carve a new niche and a new specialization. AI represents a chance for PMs to help shape the future of the industry.

It is time for the AI Product Manager. This concept was inspired by swyx.  He contends that there is the need and the capacity for a new type of engineer to arise during this AI craze. He's talked about it in depth on his podcast and later in a post. There will always be a need for traditional engineers. They build the frontends and backends of the apps we all use every day. And we also need ML engineers who spend their time refining existing models and building new ones. But between them, there is now the opportunity for engineers who build things based off of AI APIs. They get all the benefits of using models without ever having to train a model. With the speed of AI development, there will be more and more tools to build on top of.

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I see product laying out on a similar spectrum. PMs are often divided into customer-focused Software PMs and developer /platform-focused Technical PMs. (This is a generalization for simplicity, there are many other PM types out there.) PMs working on ML models and analytics would be more on the Technical end of the spectrum. They work with their engineering counterparts to build models that can be used by their software counterparts. It is a tough and never-ending job, it doesn’t look much like what people think of as traditional product management. It’s lots of testing hypotheses and finding out that a model can’t be built. Or one can be built but it isn’t accurate. Or that it is accurate for some customers, but not all customers. Or it was working when it went to production, but now it is regressing and needs more fine-tuning. You build a lot of things that never make it to production and the ones that do can be a beast to maintain.

With the prevalence of easy-to-access and easy-to-understand models (think GPT), there is an opportunity for PMs to cut a new path. PMs can dive in and become experts in these ready-built and ready-to-use models. And then use their unique customer perspective to innovate on ways to use these models. These PMs should spend their time researching and understanding the latest models. They should understand how others are using them. Then they can test these models for themselves by building proofs of concept. Finally they work with their engineering counterparts to get these models into products.


Who is An AI PM?

This sounds like a lot, but the good news is that anyone can be an AI PM. Here are a few example profiles of PMs who have gotten into the AI space:

None of these people were "qualified" but they all dove in and figured it out. Anyone can be an AI PM if they are willing to learn and passionate about problem-solving. And frankly, we need people from all kinds of backgrounds who are willing to lead in AI. Some people will start with an advantage, technical PMs will grok the tech and how it works faster. And software PMs are more likely to understand how to apply it to customers' needs. That is why we need everyone to bring their strengths to AI. And the good news is that you can bring what you already love to do and apply it to AI work. And eventually, everyone will likely be an AI PM. You can choose to be one now and be ahead of the pack or forced to be one later on.

What Does an AI PM Do?

If Software PMs build great customer-facing products. And Technical/Platform PMs build the tools that power those products. What is the charge of AI PMs? Their first and most important job is to know when a problem or opportunity will benefit from the use of AI. Let’s be frank, AI is sexy right now, everyone wants AI everywhere, or at least they think they do. But the reality is that AI is not always the answer. There are many places where AI will just make things more complicated. Or there may be an existing solution that is more simple and does the job as well. This means AI PMs need to be knowledgeable in two ways. They need to flex to the right on the spectrum so that they can deeply understand the customer and their wants and needs. They need to have all the empathy and user vision of a software PM. And then they need to be able to flex to the left on the spectrum and be an expert in the technology. They need to dive into white papers, listen to podcasts, and go hands-on with the tools. They need to understand what models are out there and the types of problems that each is best suited to solve.

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Once you’ve done all that (should be light work) it’s time to put things into action. When looking at how an AI PM solves problems, I look at it in 3 approaches. The first is they use models to answer customer’s questions before they ask them. There are things that customers do every single day that are not their actual work. It is pre-work to doing their actual work. This could be things like generating sales emails or compiling forecasts in spreadsheets. AI can do all that for them. It can do the prep work for the customer so they can start at the decision point.

Once you have got that nailed down it is time for the second approach. This one is like the first but goes deeper into the customer's business and data. You should use models to answer the questions that customers didn’t know they should be asking. Using their data and the unique ability of AI you should reveal trends and opportunities that they may not otherwise see. This approach goes beyond helping your customers do better in their existing work which we did above. Instead, this unlocks new opportunities for their businesses.

The third approach is to make it so that customers don’t worry about whether AI is involved in a product. This may seem counterintuitive for an AI PM but part of the job is knowing when to use AI. Ultimately, customers want answers they can trust, when they need them, and where they need them. As an AI PM, you should care about where the answer comes from, that is why you did all that research and testing of models. You should know which models it does or does not make sense to use for a certain problem. You should determine how to best integrate these models into your product. You should create a delightful and easy-to-understand solution for customers. You should care about how things work under the hood, but customers shouldn’t have to worry about any of that. They should be able to get the answers they need and act on them. They should get all the value without any of the cognitive work.

Where Are the AI Opportunities?

We’ve talked about what AI PMs do and how they should help customers. But where should they be doing this? Where are the areas that make the most sense to be applying AI? There isn’t one right answer. Rather it is on you as a PM to figure out what customer problems are worth solving and if AI is the right way to solve them. But to get you thinking here are some areas that are AI-based or are ripe for AI disruption:

These are just a start, there are even more areas out there to explore. Other areas to explore include computer vision, recommender systems, anomaly detection, robotic process automation, and edge AI.

Tools of the Trade

So we know what an AI PM is and the spaces they should be exploring. But how do they explore? What are the tools they should have in their belt? The great thing about being an AI PM is the tools and models are so accessible. You can go far and do high-fidelity discovery without needing to distract your engineering peers. There are so many tools out there, with seemingly 100’s more released each week. And if a tool doesn’t exist, it will soon. Places like Product Hunt and Reddit are great for learning about what is available. To get you started here are a few of the things every AI PM should be using:

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These tools play many roles in the life of a PM. We should be using them to make ourselves better and more capable. We should be using them to create PoCs for our products. And they should be inspirations for how to better integrate AI into our products.

Stick to the Basics

There is a lot to explore, it is easy to get excited, to want to dive in and solve everything. But before you get started let’s review the basics. The things AI PMs should be doing to set themselves, their products, and their customers up for success:

Looking to the Future

There have been hype cycles before (RIP to all the NFT PMs out there 🪦) but AI feels like it is here to stay. It feels like AI’s time to go mainstream is here. Things that seem novel today, will soon be table stakes in all products. The models and tools are easy to understand, accessible, scalable, and affordable. By getting started now, you are setting your products and customers to be ahead of the curve. And you are also setting yourself up to be a leader in tech’s newest breakthrough. PMs with passion and drive in this area will be able to carve their career path. There’s lots to be excited about with AI and like most things, the best way to start is to get out there and get building!