AI Product Manager Explained in 4 minutes (No Tech Background Needed)

Opera manager today will essentially become an AI program manager in the coming few years. Over 70% of companies today had admit that they have been using AI into daily operations and more

than half of the VC funding last quarter went to AI startup. Obviously AI is a future. However, most product management

future. However, most product management still have challenges and break into AI product management. In this video, I'm

product management. In this video, I'm going to break down what is a data product manager. What does data manager

product manager. What does data manager actually do? with the roles and

actually do? with the roles and responsibilities so you're able to get this clear blueprint to understand what it take for you to become an AI product manager. Make sure to stay until the end

manager. Make sure to stay until the end of this video where I share with you the all the free resources to help you get started on your AI product management career

[Music] journey. Hey guys, this is Dr. Nazi at

journey. Hey guys, this is Dr. Nazi at direct product vision in Forbes. I've

helped thousands people land the dream PM job offer in fan companies and unicorn startup and continue get promoted as a product leader in this channel at top tech trends and free point management training. Like and

subscribe to a new video every Tuesday.

I started my AI product management career over 10 years ago and I launched the very first AI smart cities product that received the mayor's best practice award and our team were invited to

present our product at NVIDIA GCP conference. Now I'm going to tell you my

conference. Now I'm going to tell you my personal experience in real life how to build AI product and what kind of roles and responsibility does AI product manager do. Now let's get started. First

manager do. Now let's get started. First

of all, what is an AI product manager?

It's very simple. An AI product manager oversees the development and implementation of artificial intelligent product. And AI program manager is

product. And AI program manager is mainly working on three things. Is a

perfect combination between business, data and technology. Now how is different from traditional per management is actually quite simple one word data as AI per manager we need to

go above beyond than traditional per manager is doing for example as AIPM we need to evaluate what kind of application is suitable for AI how to better the model quality and do you

build your model inhouse or you leverage existing large language model on the market right now we also need to validate AI hypothesis and design the data pipeline with engineering ing team

and then we are going to use the traditional product management methodology which is conduct with customer interviews building MVP with engineering team and design the go to

market strategy of our product at the same time AI product manager is also responsible for the scalability of the AI product as we all know AI has hallucination so there's a data drifting

concept shift lots of different things are happening so we need to manage the entire end to end experience of an AI I product. I made a separate video talk

product. I made a separate video talk about the five unknown differences between traditional product manager versus AI product manager. Make sure to check out this video right here. I'm

also going to link in the description of the show note. What does an AI product manager actually do dayto-day? Now, let

me lay out the daily roles of responsibility for an AI product manager. Number one, if you take a look

manager. Number one, if you take a look at all those AI product manager job responsibilities out there, you can find out there's a trend out there. All AI

product measures are responsible for creating the product strategy and the vision of developing and deploying AI product. The AI plus strategy is quite

product. The AI plus strategy is quite different than traditional product management strategy because in addition to pro strategy we need to understand the fast evolving space of AI and how to

outbeat the competition especially lots of technologist data are two weeks ago now there's a new model out there we need to be very fast in terms adjusting to the changing landscape and have a

long-term strategic vision for the AI initiatives second is manage the end to AI product management cycle end to end So as I mentioned earlier then AI part

measure starting with the entire AI hypothesis validating those model understand what kind of scenario is we must use AI or AI is just good to have.

So all those are part of initial phase of AI hypothesis and then they go to MEP phase eventually go to product launch phase. Now the third key

phase. Now the third key responsibilities for AI per measure is measure model product performance and making datadriven decision and sometimes

you build your model inhouse with a team of data scientists and sometimes you directly use the existing large language model by working with the AI engineers.

Number four AI manager needs to learn how to lead cross functional team including data scientists, AI engineers, AI designers and the legal compliance departments as well. Number five, which

define problem statements suitable for AI. There are three types of AI product.

AI. There are three types of AI product.

The product cannot function without AI such as self-driving car. You can create brand new experience leveraging AI such as AI chatbot or add on additional feature powered by AI to existing

product such as tax prediction for Gmail. When you validate what situation

Gmail. When you validate what situation you need to use AI, you must use AI hypothesis framework I've invented. I

have a deep dive 30 minutes free talk teaching you how to use AI hypothesis to validate different AI ideas on why 70% of today's AI product fail and how to

fix it. You should go to this website

fix it. You should go to this website and start to uh check out this free training. I'm also going to link in the

training. I'm also going to link in the description of the AI hypothesis what a lightning talk and then AR manager still need to write product requirement documentation prioritizing product

features on the Roma managing your backlogs and defining MVP and AI product manager also need to define the go-to market strategy of your AI product because at the end of the day if nobody

want to use your product you're not a successful AI product manager there's also something special AI partner should do which is and AI compliant science. If

you want to dive deeper regarding what a day in life as a AI product manager, you can check out this video right here. I'm

using my real life example showing you behind the scene stories. I'm also going to link it in the description of this video. Now, here comes the bonus tip.

video. Now, here comes the bonus tip.

How to get started on your AI product management journey. And number one, I

management journey. And number one, I have lots of free courses resources highly recommend everyone to learn to brush up your AI skills. For example,

this course, learn the fundamentals of generative AI for real world applications. Uh there's also lots of

applications. Uh there's also lots of free YouTube videos that I believe is so outstanding and you can start learning for free. For example, Gen AI in a

for free. For example, Gen AI in a nutshell in the age of AI only 17 minutes that give you overview geni right away. There's also free lecture by

right away. There's also free lecture by Andrew Wan about agendic workflow and how is a game changer for the entire AI era. I discovered 10 other free

era. I discovered 10 other free resources. I'm also going to the link in

resources. I'm also going to the link in the description of this video so you can watch all of these for free. After

learning all those free content, you should start to build your AI product portfolios to demonstrate your skill set and knowledge about AI. And third, I

highly gain hands-on experience using AI and building real world AI product with a team of developers and data scientists. This is the best way for you

scientists. This is the best way for you to really stand out in the competitive job market today. If you're interested getting matched with a team of AI developers to build real life AI product

with coachings and starting your own AI startup, you can check out our AIPM boot camp. I'm going to link in the

camp. I'm going to link in the description so that you can learn more.

Number four, you should get started with creating a clear AI primure resume to help you land your first AIPM interview.

You can download the free AIPM ré template with guaranteed interview opportunities after you implement the entire keywords on those template. Feel

free to go to this website and download those template for free today. Within AI

program management, their traditional ML AI, ML manager, there's also Gen AIPM.

And nowadays, the trend is all moving towards Gen AIPM. And I made a separate video breaking down in depths regarding the only three ways to become a Genai product manager this year. Make sure to

check out this video right here. If you

like any of the free tips today, make sure to like and comment. Subscribe to

channel. This is Darkness CD from PMxer.