AI is revolutionizing industries, and businesses are scrambling to keep up. The role of AI product managers is at the forefront of this shift, with more than 14,000 job openings globally as of October 2023, including nearly 6,900 in the U.S. alone. Salaries reflect this demand, with U.S. AI PMs earn an average of $133,600 annually, climbing to $200,000 for senior roles.
At Eleken, a UI/UX design agency, At Eleken, we collaborate with startups building AI SaaS solutions, giving us insight into how AI product management bridges technology and business goals.
Yet, despite the rapid growth of this field, many product managers find it challenging to transition into AI. A Reddit poll of aspiring AI PMs revealed that nearly half of the respondents were still searching for effective resources to learn the skills they need. The diversity in preferred learning methods—structured courses, YouTube tutorials, blogs, AI subreddits, and hands-on Kaggle projects—underscores how undefined the learning journey for AI product managers still is.
We’ve seen this struggle firsthand, and that’s why we’re here to help. In this guide, we’ll dive into the role of AI product managers, the skills they need, the challenges they face, and how to set yourself up for success in this exciting and rapidly evolving field.
What is an AI Product Manager?
An AI product manager is a unique blend of product management expertise and AI fluency. They act as the bridge between technical teams and business stakeholders, ensuring that AI-driven products align with organizational goals while delivering value to users.
AI product managers oversee every stage of an AI product’s lifecycle, including:
- Defining product vision and strategy: Translating business objectives into AI product development strategies and AI-powered solutions.
- Managing cross-functional teams: Collaborating with data scientists, engineers, and designers to develop and refine AI models and applications.
- Prioritizing features: Balancing AI capabilities with user needs and technical constraints.
- Ensuring ethical AI practices: Addressing concerns like data privacy, bias, and transparency.
AI product managers differ from traditional PMs by focusing on machine learning for product managers, data ethics, and ongoing model refinement.
AI vs. Traditional Product Management
AI product management goes beyond traditional product roles by focusing on the integration of rapidly evolving technologies into business solutions. While traditional product managers deal with structured workflows and defined feature sets, AI product managers must:
- Navigate data complexities: Ensuring datasets are clean, unbiased, and representative is a frequent bottleneck, as even minor data flaws can derail an AI project.
- Manage model lifecycles: Unlike static features, AI models require continuous training, refinement, and monitoring to remain effective.
- Balance ethics and innovation: AI PMs face the dual challenge of driving cutting-edge advancements while addressing critical issues like data bias, privacy, and model transparency.
A common struggle for AI PMs is communicating these intricate dynamics to non-technical stakeholders. Translating complex AI processes into accessible insights is a crucial skill, especially when managing expectations about what AI can—and cannot—achieve. Successfully aligning teams around these goals is what sets AI product managers apart.
Skills required to succeed as an AI product manager
To excel in artificial intelligence product management, you’ll need a mix of technical and non-technical skills:
Technical skills
AI product managers need to know their way around the basics of AI and machine learning. This includes knowing how models are trained, tested, and deployed, and being familiar with tools like TensorFlow or AWS SageMaker. You don’t have to be an expert, but knowing what they do will save you headaches when talking to your team.
And here’s a tip straight from the trenches: AI for product managers requires focus on data literacy over coding. Experienced AI PMs on Reddit say it’s more important to know how to work with data—spotting trends, identifying gaps, and understanding what the results mean—than it is to write the code yourself. Leave the heavy lifting to the engineers!
Non-technical skills
Soft skills are where AI PMs really shine. You’ll need to:
- Tell a great story: Explaining ML work to non-technical stakeholders is critical. As one PM puts it:
"It’s about translating complex data into something actionable for the business." Clear communication builds trust and aligns teams around a shared goal. - Think big picture: Use strategic thinking to align product management for AI initiatives with business goals.
- Stay ethical: AI comes with tricky issues like bias and privacy, and not everyone will prioritize them. As another PM shares:
"Ethical considerations, like bias in AI, often aren’t top of mind for everyone on the team. A great PM makes these a priority while balancing the push for delivery."
At the end of the day, the best AI PMs are the ones who can juggle the technical and the human sides of the job without dropping the ball.
Transferable skills from other roles
One of the great things about AI product management is how well skills from other professions translate into the role:
- UX designers bring a deep understanding of user needs and often work closely with PMs, making it easier to transition. You can start small with using ChatGPT for AI research and go down the AI rabbit hole from there.
- Marketers bring user research expertise and a clear focus on aligning product decisions with business goals.
- Engineers contribute technical know-how and the ability to navigate complex systems, even if they don’t have formal PM experience.
These diverse backgrounds not only offer unique perspectives but also highlight that product management isn’t a one-size-fits-all career. If you’ve honed any of these skills in your current role, you already have a head start.
How to become an AI product manager
Getting into AI product management might feel overwhelming, but breaking it down into clear steps makes the journey a lot easier. Here’s a roadmap to get started:
#1. Start with the basics
Begin by building a foundation in product management and AI concepts. Learn how product roadmaps work, get comfortable with user research, and dive into the fundamentals of AI and machine learning. Online resources like Coursera, which offers the IBM AI Product Manager Certificate, and Udacity, with its dedicated AI Product Manager Nanodegree, are goldmines for building foundational knowledge and practical skills.
For additional insights, platforms like ProductSchool provide valuable guides that blend theoretical knowledge with real-world applications, while hands-on learning through Kaggle projects helps you work with datasets to tackle real-world AI challenges. Communities like r/ProductManagement and r/learnmachinelearning on Reddit are also great places to learn from experienced AI PMs, ask questions, and stay updated on industry trends.
As you dive deeper, reading widely recognized product management books can provide essential context and inspiration. Titles like:
- Inspired by Marty Cagan, which explains the spirit of modern product management,
- Lean Product Playbook by Dan Olsen, a practical guide for creating products customers love, and
- Escaping the Build Trap by Melissa Perri, which focuses on aligning product work with business outcomes, are must-reads for aspiring product managers. To tailor your learning to AI-specific challenges, combine these with resources like Designing Machine Learning Systems by Chip Huyen, which explores how to build effective AI products.
#2. Get hands-on experience
Theory is great, but nothing beats real-world practice. Look for internships, shadow experienced PMs, or take on adjacent roles in AI-driven projects. Even contributing to small-scale AI projects can give you a solid edge when applying for jobs.
While getting your first AI-related experience might feel like chasing the next big thing, seasoned professionals caution against falling for AI hype. As one experienced PM on Reddit explains:
"Be wary of AI hype positions right now. Many AI PM jobs exist just to 'add AI,' but the real skill lies in knowing when AI is genuinely the solution and when it's not worth the investment."
Instead of chasing flashy roles, focus on positions where you can make a tangible impact. As another practitioner advises:
"Being an AI PM isn’t just about cool tech; it’s about creating impact. Opt for unsexy roles where you can make tangible business contributions, rather than chasing cutting-edge research teams."
#3. Network like a pro
AI product management is a growing field, and connecting with people in the industry can open doors. Join AI-focused communities on LinkedIn, Reddit, or Slack groups. Attend webinars and conferences to meet seasoned AI PMs and learn from their experiences.
#4. Build an AI-centric portfolio
Employers want to see what you can do. If you’ve worked on projects with AI integrations, highlight them in your portfolio. Don’t worry if they’re not groundbreaking—showing you’ve tackled real problems with AI solutions makes a big impression.
And if you don’t have direct experience yet, don’t sweat it. Pet projects can be just as powerful. Build a small AI-driven tool, analyze a dataset, or create a simple prototype that demonstrates your understanding of AI concepts. It’s a great way to showcase initiative and prove your skills.
#5. Land your first AI PM job
Breaking in can be the toughest part, but persistence pays off. Tailor your applications to highlight how your skills align with the unique needs of AI product management. And don’t forget to mention any networking connections who might vouch for you—it’s a small world in tech!
If you’re just starting out, consider tech companies’ Associate Product Manager (APM) programs. Companies like Google, Facebook, and Uber offer these programs to train young professionals straight out of college, providing hands-on experience and a clear pathway to product management roles. While AI-specific APM programs aren’t yet widespread, gaining entry through general APM roles can set you up for a future in AI PM.
Another effective strategy is to aim for internal promotions within startups or departments where AI-driven projects are being developed. Startups, especially those working on AI, often operate in a fast-paced, cross-functional environment that encourages employees to take on broader responsibilities. Proactively taking on PM-related tasks can help you gradually transition into the role.
For those already in related roles, consider shadowing and collaboration. Working alongside AI teams in positions like data analysis, UX design, or even marketing gives you firsthand experience with AI projects. This not only boosts your skill set but also helps you build relationships with team members who can advocate for your transition to an AI PM position.
Breaking into this field isn’t easy, but it’s absolutely doable if you take it step by step. As many experienced AI PMs say, start small, stay curious, and keep learning along the way. If you’re considering a transition from a design position, start with learning more about AI in UX design.
Career growth in AI product management
Once you’ve broken into AI product management, there are plenty of ways to grow your career. AI product manager job descriptions often emphasize roles that combine strategy with execution. Senior roles in machine learning product management typically involve greater cross-functional leadership and innovation oversight. Pathways include transitioning into specialized roles like AI product owner or ML product manager.
You could move into:
- Senior AI product manager roles: Lead high-impact projects and mentor junior PMs.
- AI strategy or leadership positions: Shape the direction of AI initiatives for an entire organization.
- Starting your own AI-focused company: Use your experience to solve market gaps with innovative AI products.
Seasoned AI PMs often emphasize the importance of adaptability. As one experienced PM puts it on Reddit:
"In the early stages of your ML project, aim for speed. Choose the solution that validates/rejects your hypotheses the fastest."
The field is evolving rapidly, so staying ahead means embracing iterative learning and being open to new methodologies. Another professional highlights this dual challenge:
"Bridge the tech/business gap in your organization: Business professionals don’t know enough about the intricacies of machine learning, and ML professionals don’t know about the practical needs of businesses."
Staying curious, flexible, and engaged with emerging tools and trends is key to climbing the ladder in this fast-changing industry.
AI product management across industries
AI is no longer just a buzzword in Silicon Valley—it’s making waves across industries you might not expect. From healthcare to e-commerce, automotive to finance, businesses everywhere are investing in AI to solve problems and unlock new possibilities. This trend means big opportunities for AI product managers (PMs) to step outside traditional tech hubs and work on exciting, real-world applications. As one experienced PM notes:
"AI roles are expanding into industries like healthcare and finance. Knowing the use cases—like patient care systems or fraud detection tools—can open new opportunities outside tech hubs."
Let’s dive into how these roles look in different industries:
Healthcare AI product manager
Imagine helping doctors save lives with smarter tools. Healthcare AI PMs work on:
- Patient care solutions: Creating AI tools that suggest personalized treatments or help with early diagnoses.
- Clinical decision-making: Building systems that provide doctors with data-driven recommendations.
- Medical imaging analysis: Using AI to detect issues in X-rays or MRIs faster and more accurately than ever before.
In healthcare, you’re not just creating cool tech—you’re making a real difference while ensuring strict privacy and safety standards.
E-commerce AI product manager
Online shopping wouldn’t be the same without AI working behind the scenes. As an e-commerce AI PM, you might:
- Build recommendation engines: Design AI that suggests the perfect product based on someone’s tastes and shopping habits.
- Personalize the shopping experience: Create tools that make every visit feel tailor-made for each customer.
- Streamline operations: Use AI to predict inventory needs or provide super-fast customer support.
This role combines creativity and data to keep customers engaged and businesses thriving.
Automotive AI product manager
Cars are getting smarter, and AI PMs are driving (pun intended) that change. In this role, you could:
- Develop connected car features: Build AI systems for smarter navigation, entertainment, and driver safety.
- Work on self-driving tech: Create the brains behind autonomous vehicles, from recognizing obstacles to making safe driving decisions.
- Enable predictive maintenance: Use AI to tell drivers when their car needs servicing before it’s a problem.
If you’re fascinated by futuristic tech, this role lets you create innovations that redefine how people travel.
Finance AI product manager
AI is shaking up the finance world by making services smarter and more secure. Finance AI PMs focus on:
- Fraud detection: Designing systems that catch suspicious transactions before they cause trouble.
- Risk assessment: Building tools that evaluate credit or investment risks with pinpoint accuracy.
- Algorithmic trading: Using AI to make faster, smarter trades by analyzing market trends in real time.
In finance, you’ll work at the intersection of tech and trust, ensuring AI delivers powerful results while keeping data safe.
These roles show just how much AI is transforming industries far beyond traditional tech. Whether you’re improving patient care, personalizing shopping, or building self-driving cars, AI PMs have the chance to solve exciting challenges and make a real impact. The opportunities are endless—where will you take them?
AI product manager salaries and job market
AI product management isn’t just exciting—it’s well-paid too. And with demand for AI expertise exploding, the job market is packed with opportunities.
In the United States, AI product managers earn an average of $133,600 per year, with entry-level roles starting at $100,000 to $120,000. Mid-level PMs can expect $120,000 to $150,000, while senior roles often command salaries between $150,000 and $200,000 or more. Outside the U.S., salaries are also competitive. In India, for example, the average salary for an AI PM is approximately ₹26,78,330 annually, reflecting the global demand for this expertise.
And that demand is growing fast. As of late 2023, there are over 14,000 job openings for AI product managers on LinkedIn, including nearly 6,900 in the U.S. and 1,300 in India. This surge isn’t just limited to tech companies—industries like healthcare, finance, and retail are all jumping on the AI bandwagon, creating a diverse and rapidly expanding job market.
AI product management is clearly a field on the rise, offering not just strong compensation but also a dynamic range of opportunities across industries.
Practical tips to kickstart your AI product management journey
Breaking into AI product management can feel daunting, but the right approach makes all the difference. As we’ve explored throughout this guide, the role of an AI product manager is unique, challenging, and full of opportunities. Whether you’re just starting out or looking to grow your career, here are a few final, actionable steps to help you get there:
Get involved in AI communities
Communities are your gateway to insights, mentorship, and new opportunities. Platforms like r/ProductManagement and r/learnmachinelearning on Reddit are packed with discussions, resources, and advice from seasoned AI PMs. Slack groups, local meetups, and webinars offer great ways to connect with others in the field, expand your network, and stay informed about the latest trends. Finding a mentor who has successfully transitioned into AI product management can provide personalized guidance and help you avoid common pitfalls.
Leverage online resources
The journey to becoming an AI PM is still evolving, which means there’s no single roadmap—but there are plenty of tools to guide you. Platforms like Coursera and Udacity provide structured courses to build your foundation, while hands-on practice through Kaggle projects helps you tackle real-world challenges. Add to that insights from blogs, YouTube tutorials, and books like Designing Machine Learning Systems by Chip Huyen to round out your knowledge.
Seek continuous learning
AI isn’t static—it’s an ever-evolving field, and staying relevant means keeping up with the latest advancements. Follow technical blogs like the Netflix Tech Blog and LinkedIn Engineering Blog to learn how industry leaders are solving problems. Explore cutting-edge tools, attend industry events, and continuously expand your expertise.
Focus on the journey, not just the role
Your path to becoming an AI PM won’t look like anyone else’s—and that’s okay. Adaptability, curiosity, and a commitment to lifelong learning are what will set you apart. Draw inspiration from the diverse career stories of successful PMs, many of whom transitioned from roles like marketing, design, or even teaching. These case studies remind us that breaking into AI product management is achievable, no matter where you’re starting from.
Final thoughts
With determination, the right resources, and support from mentors and communities, you can chart your own path to success in this exciting and rapidly evolving field.
If you need an experienced designer partner to help you tailor your new AI product, drop us a word and see what Eleken brings to the table!
