How to Become an AI Product Manager: Skills, Requirements, and Career Guide
Chances are, if you've found your way to this page, you're already familiar with the general roles and responsibilities of a general product manager. If not, go take a look at that career guide to get caught up. AI Product lives at the intersection of general product development and the ever-changing and fast growing field of Artificial Intelligence. This role is exploding in popularity as companies work to catch up with the industry.
AI Product Managers focus on ways to develop and integrate AI into their company's relevant features and applications. These PMs collaborate with cross-functional teams to define product strategy around AI, design features and user experiences, and general business cases from concept to launch.
If you're interested in becoming an AI product manager, this guide is for you. We'll walk you through the essential skills and requirements for the role, as well as the various career paths and opportunities available to product managers in this field. We'll also provide tips on how to break into the product management industry and how to advance your career over time.
We must admit, this is a type of role (mid-to-senior-ish-level) that we don't usually make guides for-- but the requests have been overwhelming! So here it goes...
What is an AI Product Manager?
An AI (Artificial Intelligence) Product Manager is a tech professional responsible for guiding the development, launch, and continuous improvement of AI-powered products or features. These PMs specifically combine their expertise in product development, artificial intelligence, machine learning, and data science to create valuable and effective solutions that meet user needs and drive business impacts.
At a high level, AI Product Managers work closely with several cross-functional teams, including data science, engineering, design, and marketing, to define product requirements, prioritize features, and ensure successful product execution. Their role also involves making data-driven decisions, setting key performance indicators (KPIs), and monitoring the performance and impact of AI-enabled products in the market.
As AI technology continues to advance and integrate into various industries, AI Product Managers play a crucial role in translating complex AI capabilities into user-friendly and valuable solutions for both businesses and consumers.
Curious what we mean when we say "product?" Read This.
Responsibilities of an AI Product Manager
AI Product Management Business Cases
Until recent years, AI and ML (machine learning) have seemed like tools of the far future. That's actually not the case at all. Here are some practical use cases and product examples that would fall under the umbrella of an AI product manager.
- Personalization: AI can be used to personalize the user experience by providing personalized recommendation algorithms and advertising based on individual user touchpoint data (in fact, this is what I do in my full-time job!). An example of this would be product recommendations in a "You May Also Like" modal on an ecommerce website.
- Predictive Maintenance: AI can be used to analyze equipment data and predict when upkeep is needed, which can drastically reduce maintenance costs. An example of this could be a product that predicts when rental vehicles need service to reduce costs.
- Customer Service: AI-powered chatbots and virtual assistants can handle customer inquiries and provide personalized support, improving customer satisfaction and reducing support costs. You're probably familiar with these examples from bank chatbots, but these bots are very prevalent in many industries. I'm predicting that the Chat GPT model will become a white-labeled customer service helpline within the next few years.
- Supply Chain Optimization: AI can analyze supply chain data to optimize delivery routes, improve inventory management, and reduce waste. An example of this could be running models to determine the best places to create physical products that minimize shipping and manufacturing costs.
- Data-Democratization: If you haven't heard, AI is competent at writing and optimizing queries to pull data from multiple sources and databases. This is the future of analytics. While this tech is still in early stages, we predict a new field will emerge to create products that enables non-analytical teams to pull and connect multiple data sources from a simple, plain-worded question!
So what exactly does an AI Product Manager do?
We talk about this more in our general product management guide, but two days are rarely the same for any type of product manager. Product Managers collaborate with each of the technical jobs to make sure everyone is equipped with the resources and guidance to do their best work.
However, as an AI product manager you can expect to be responsible for several things, including:
- Defining the AI product vision and strategy: Develop a clear understanding of the market, customer needs, and business goals to create a product vision and strategy aligned with your company's objectives.
- Defining product requirements: Work closely with stakeholders, data scientists, and engineers to translate business goals into actionable product requirements, ensuring AI solutions meet customer needs and provide value.
- Prioritizing features and potential releases: Create and maintain a product roadmap, prioritizing features and enhancements based on factors like customer needs, business value, and technical feasibility.
- Cross-functional collaboration: Collaborate with various teams such as engineering, design, data science, and marketing to ensure seamless development and execution of AI-powered products or features.
- Overseeing development and launch: Manage the product development process, working closely with development teams to ensure timely delivery of features while maintaining high-quality standards.
- Monitoring performance: Establish key performance indicators (KPIs) and monitor the performance of AI products in the market, using data-driven insights to make informed decisions and adjustments.
- Continuous improvement: Iterate on AI products based on user feedback, market trends, and new technological advancements to ensure continuous improvement and stay competitive in the market.
- Stakeholder management: Communicate product updates, progress, and challenges to stakeholders, while managing their expectations and addressing any concerns.
- Ethical considerations: Ensure AI products adhere to ethical guidelines, taking into account fairness, transparency, and privacy concerns.
- Staying informed: Keep up-to-date with advancements in AI, machine learning, and related technologies, as well as industry trends and best practices, to make informed decisions and drive innovation.
AI Product Management Team Members
For general product management we'd recommend you check out the roles of Product Analyst, UX Designer, UX Researcher, Project Manager, and maybe some engineering roles. However, AI is a different industry and requires knowledge of machine learning and data science principles. You'll also regularly be interacting with those team members, so focus your time on getting chummy with your data scientists.
Education Requirements
Do I need a degree to be an AI Product Manager?
General Product Managers can come from all backgrounds. They're also a popular role for people with MBAs, though this is definitely not a requirement. Industry experience is actually much more relevant for a Product Manager, and it's popular as an inter-company movement. General Product Management job descriptions will sometimes mention a requirement of something STEM related, but this is becoming less and less common. This is also a popular bootcamp role.
If you're new here to bridged, we're glad to meet you! We are huge fans of alternate forms of education, and recommend specific certifications to target skills. While this job works great with degrees, you have other options.
However, AI is a hugely mathematical-driven field. If you do not have a degree in something STEM related, we recommend focusing on data science principles and working your way from there. This is also not an entry-level role, and likely will require previous product management experience.
Associate Product Manager Programs
A popular way to break into general product management right after college is to join an Associate Product Manager (APM) or Rotational Product Manager Program (RPM). Most major tech companies offer some sort of program spanning between 1-2 years, and often come with a full-time offer upon completion. Learn more about APMs here.
Our Favorite AI Product Management Certifications
Duke University's AI Product Management Specialization
This program comes with a certification from prestigious Duke University that is resume-worthy and verifiable on Linkedin. This is the primary reason we rank this course the highest-- showing employers you took the time to get certified does wonders in the job market.
University of Washington's Machine Learning Specialization
We won't lie: this course is challenging, but clustering is an incredibly practical concept in many industries. Professor Emily broke down the material into understandable chunks, and we loved the application case-studies for showcasing how businesses could use clustering to better understand their users. This is also a very popular concept for user analysis and personalization (which is our background!).
Udacity's NanoDegree Program: AI Product Management
This specialization comes with a sharable certification from Udacity. The best part of Udacity programs is the career-ready portfolio of completed projects upon completion of the cert. Portfolios are a great way to show potential companies what you're capable of, especially when starting out in a tech career. Though we won't lie, we're always updating our personal portfolio 10 years in!
Salary and Career Potential
What is an AI Product Manager's salary?
AI Product Managers are most certainly not entry-level positions, and are usually product managers with several years of experience and a knack for technicality. The salaries of these PMs definitely reflect this. We've aggregated thousands of salaries across glassdoor and linkedin, and AI product managers can make anywhere between 135k-185k, depending on their location and skillsets. We'd be kidding if we didn't mention it is rare to see this role not listed as a senior position.
Career Path of an AI Product Manager
We're going to start from step one here, so maybe you can work your way into it. Product management career paths can be super confusing. We've written a whole piece on the general career path here. But here's the AI-specific short version for you:
- Data Scientist. Spend 2-4 years here.
- Product Manager, or Associate Product Manager: Spend about 2-4 years at each level here.
- Senior Product Manager: Spend about 3-5 years here.
- Senior AI Product Manager: Spend about 3-5 years here. This is usually a lateral movement from Senior PM, but since AI is so much more technical we broke it out into its own line.
- Director of Product: This one is tricky, but most folks spend roughly 4-6 years here. We wouldn't be surprised if we start seeing Director of AI popping up as a role sometime soon. We warned you!
Job Requirements and Skills
Popular Job Description of an AI Product Manager
We've used AI (no pun intended?) to aggregate the top job descriptions used by hiring managers looking for AI/ML Product Managers. When putting your resume together, try to mimic these listings. To learn more about this process, check out our partner Jobscan for a comprehensive resume review.
- Develop and refine product vision, strategy, and roadmap for AI-powered products or features, aligned with company objectives and market trends.
- Collaborate with stakeholders, data scientists, engineers, and designers to define product requirements and ensure AI solutions address customer needs and business goals.
- Prioritize features and enhancements based on customer feedback, market research, technical feasibility, and business value.
- Manage the product development lifecycle, from ideation to launch, working closely with cross-functional teams to ensure timely delivery and high-quality standards.
- Monitor and analyze product performance using key performance indicators (KPIs), making data-driven decisions to optimize and improve AI products.
- Gather and incorporate user feedback, market trends, and technological advancements into the product development process to ensure continuous improvement and competitiveness.
- Communicate product updates, progress, and challenges to stakeholders, managing their expectations and addressing concerns.
- Ensure AI products adhere to ethical guidelines and consider fairness, transparency, and privacy concerns.
- Stay informed about advancements in AI, machine learning, and related technologies, as well as industry trends and best practices, to drive innovation and informed decision-making.
Top Technical Skills of an AI Product Manager
We've compiled thousands of job descriptions for AI Product Managers to record the most common requirements to save you time. While preparing for interviews, keep in mind specific times you've demonstrated these skills.
- Ability to connect and communicate with Data Scientists and Machine Learning engineers
- Understanding of explicit and implicit inputs to feed various learning models
- Requirements gathering across teams and verticals
- Deep knowledge of scrum processes in Agile like sprints, point systems, and refinements
Top Functional Skills of an AI Product Manager
We recommend getting familiar with different types of customer questions if you plan to pursue a career in AI/ML product management. If finding these answers seems interesting to you, read on!
- Excellent communication and leadership skills, with the ability to influence and collaborate with cross-functional teams
- Soft skills and team bonding
- Strong analytical, problem-solving, and strategic thinking skills
Top Tools of an AI Product Manager
These are more generic, because many AI product managers will come from engineering backgrounds. But we've also compiled the most common tools for general PMs that are listed in job descriptions. If you're serious about becoming a product manager, get familiar with these and be ready to talk about them.
For Data Models & Manipulation
- Databricks
- AWS Personalize
- TensorFlow
- PyTorch
- scikit-learn
- Keras
- CUDA
For Team Collaboration
- Notion
- Roadmunk
- Aha!
- Clickup
- Roadmunk
- Trello
For Coding
- Python
- SQL
- JavaScript
For Engineering Management
- Jira
- Confluence
- Roadmunk
- Notion
Key Traits of a Successful Product Manager
Comfort with Ambiguity- Product managers often work in fast-paced and dynamic environments, where priorities and requirements can change rapidly. To be successful, product managers must be comfortable with uncertainty and able to adapt quickly to changing circumstances. They must be self-motivated to solve ambiguous problems, and have the ability to manage their time and workload effectively.
Qualitative & Quantitative Research - Gathering data and insights is crucial to product management, as it helps inform product decisions and strategy. Qualitative research involves conducting user interviews, focus groups, and surveys to gain a deep understanding of user needs, preferences, and pain points. Quantitative research involves analyzing metrics and data to track user behavior, engagement, and other key performance indicators. Product managers need to be proficient in both types of research to make informed decisions.
Quick Decision Making - Product managers are often required to make fast, informed decisions to keep projects moving forward. They need to be able to weigh the pros and cons of different options quickly and decisively, while remaining calm under pressure.
Curiosity - Product managers need to have a natural curiosity and desire to explore and understand potential problems with their products. They need to be able to identify friction points and areas for improvement, and continuously look for ways to optimize and enhance their products.
Analytics Platforms - To be effective in quantitative research, product managers need to be proficient in using analytics platforms such as Google Analytics, Mixpanel, or Amplitude. They need to be able to extract insights from data, and use those insights to inform product decisions.
Collaboration - Product management is a collaborative role that involves working closely with cross-functional teams, including engineering, design, marketing, and sales. Product managers need to be able to bring out the best in their teammates and remove any blockers that may be hindering progress.
Empathy - User empathy is a huge part of building a helpful and cohesive product. You need to be able to understand where the users are coming from, and create solutions to address their problems. User empathy is essential for building products that truly meet user needs and solve their problems. Product managers need to be able to understand user perspectives and design solutions that are intuitive, user-friendly, and helpful. They also need to be able to communicate the value of their products in a way that resonates with users.
Get AI Product Management Experience
Learning on the job is one of the fastest ways to get familiar with new topics, and showing is much better than telling. Think about a net-new or existing product at one of your favorite companies. Think about different problems they might face, and think about how you might be able to solve those using artificial intelligence or machine learning models. What data would you need? Think about what pieces of data you could feed the model, and how that model could make your users' lives better. Maybe design a rough algorithm for a potential solution.
The most popular implementation of AI/ML as it stands in big companies is recommendation algorithms and assisted chat bots. To get personal, I interviewed for an AI product manager role recently (writing for Bridged is a fun side-project) at a large company well-known for it's stellar recommendations in the beauty industry. For one -- the hardest one, a dreaded whiteboard-- of my many rounds of interviews, I was asked to create a map of the inputs my model might take in and the outputs I'd create for a loyalty recommendation algorithm for makeup and hair care products. They then asked me to weight and prioritize the inputs and outputs in case the data was not readily available. Based on the prep I'd done, this is a very standard sort of interview question (and project!) for AI product managers.
Expert mode: if you're interested in the specifics, I answered the inputs recorded should be something like product names browsed, categories of products browsed, user-experience level for products browsed, size/lifespan of products, spread of product type, product views per visitor, product checkouts per visitor (frequency of purchase for sizing), and a few others. Outputs-- why do I always want to call these Exputs-- would be things like a very personalized feed based on what we know about the user's experience level with products, size of products most likely bought, and complementary products and categories to things the user may have a propensity to impulse buy. This sounds a lot more fun than actually building the pipelines to acquire and manipulate this data. But you get the idea.
Real talk: we'd recommend completing the Duke course or the Udacity Nanodegree before deciding if this role is for you because it is extremely technical compared to some other high-paying tech roles.
Relevant AI Product Management Experience
- STEM majors- anything math, science, or technology related
- MBA grads. The strategic thinking around problems and solutions lends nicely.
- Industry knowledge - did you get lucky and end up at a company that uses AI? How can you work closer to it?
- 1-2 years in another technical profession- data science, product analytics, ux research/design, or project management.
Some popular product management activities to get general experience:
- Research! Think about what features are needed for your product. How many users will they affect? How much money could it make?
- Analytics! Working on identifying "user friction," ie. where do users have issues with the product? What's the most common path to conversion for users?
- Presentation! Think about how you'd show off your proposed product improvements--even if it's a fake product. Make a deck. Write about company "problems" and your proposed solutions. Show off how you used quantitative and qualitative data to make conclusions. (This is actually part of the interview process for many big companies. Be ahead of the curve.
Other Types of Product Management for Your Radar
AI product managers are getting a lot of hype, but there are other, less-technical roles out there. Sometimes at a small company, one PM will run several aspects, but if you go to a larger company it'll be expected that you niche down. I started my career as a growth product manager, and then an ecommerce product manager, then now am a technical product manager. It's definitely fluid and company-dependent!
Technical Product Manager
A technical product manager is responsible for overseeing the development of complex and technical products. They work closely with engineering teams to define technical requirements and ensure that the product is built to meet the desired specifications.
Growth Product Manager
A growth product manager is focused on driving user acquisition, retention, and revenue growth in several types of markets. They use data analysis and experimentation to identify and implement strategies to improve key performance metrics.
Platform Product Manager
A platform product manager is responsible for building products that provide a foundation for other products or services to be built upon. They need to be able to design flexible and scalable platforms that can be customized for different use cases.
eCommerce Product Manager
An eCommerce product manager is focused on building products for online retail markets. They need to have a deep understanding of eCommerce platforms and technologies, and design products that provide a seamless and secure online shopping experience.
(you know this one already but) AI/ML Product Manager
An AI/ML product manager is responsible for building products that leverage artificial intelligence and machine learning technologies. They need to have a strong understanding of data science and analytics, and be able to design products that deliver accurate and relevant insights.
Get Experience as an AI Product Management Volunteer
While it's tough to get 0-1 experience, there are organizations out there to help. Bookmark these orgs to search for UX/UI work to add to your product portfolio.
- Volunteer organizations: Someone way smarter than us came up with the idea to connect newbie designers with non-profit organizations who could use the help. Some of our favorites include Catchafire and UX Rescue. This is also a plus because it's a tax writeoff... but we aren't qualified to be giving financial advice!
- Hackathon teams: If you live in a city, odds are there are tech hackathon groups you can find with a quick google search. Even better if you're a student and near a university. If you live somewhere without a lot of tech folks, peruse hackathon.io apply for jobs!
- Spec work (that turns to real work): A popular term in the freelance industry is "Spec work often turns into real work." This is true for lots of different areas, but especially in UX. Go to local businesses and ask if you can help them solve some digital problems on their website. This can be a win-win-- you can get meaty projects for your portfolio, and maybe even get paid for some of it. Good luck!
Craft a Memorable Product Management Portfolio
We loved these tips here at Linkedin for getting familiar with the process of making a product management portfolio. While it's not required to have a portfolio (like it is in ux design/research), product managers who put in the work usually come out ahead because it shows hiring managers they have the ability to execute.
Get Started with a Bridged Recommendation
Review: AI Product Management Specialization by Duke University
Conclusion
In conclusion, AI Product Managers play a pivotal role in driving the development and success of AI-powered products and features in today's rapidly evolving technological landscape. By combining their expertise in product management, artificial intelligence, and data science, they help create innovative solutions that meet customer needs and deliver business value. As the demand for AI integration across various industries continues to grow, AI Product Managers will be instrumental in bridging the gap between complex AI capabilities and user-friendly, valuable offerings.
If you are considering a career in AI Product Management, now is the perfect time to develop the necessary skills and knowledge, and embark on an exciting journey that will shape the future of technology and business. Here at Bridged we are huge fans of stacking micro-certifications to achieve desired career results. We're building a product to make your career planning fun and affordable, and we'd love to talk to YOU! Was this article helpful? Did you land an interview for a product management role?
Let us know at hello@getbridged.co
Check out our sources!
Glassdoor Team. “Salary: AI Product Manager (April, 2023) | Glassdoor.” Glassdoor, 1 Feb. 2023.
