Product Manager - Artificial Intelligence
Impact: AI and machine learning innovation
Manages AI and machine learning products. Focuses on AI innovation, machine learning applications, and AI-powered solutions.
From people doing the work
It's a constant balancing act between new AI research and real-world business value. You're the bridge between data scientists, engineers, and the market, translating complex algorithms into tangible product features that users love and that drive impact. Expect a lot of stakeholder management and a need to stay updated on the latest AI trends.
Drawn from Product School, AI Product Managers LinkedIn Group, Towards Data Science
Attribution: Composite
Composite · Synthesised from Product School, AI Product Managers LinkedIn Group, Towards Data Science
A day in the life of a Product Manager - Artificial Intelligence
- People interaction
- Moderate
- Team vs solo
- 60% Team / 40% Solo
- Client facing
- Sometimes
- Impact visibility
- Very High
- Travel
- Moderate
- Schedule flexibility
- Flexible
- Remote work
- Hybrid
- Typical work hours
- 45-55 hours/week
- Stress level
- High
Product Manager - Artificial Intelligence salary, education and outlook at a glance
- Median salary
- $200,000
- Entry-level
- $125,000 - $160,000
- Senior
- $300,000
- Growth by 2033
- 31% (much faster than average)
- Demand
- Growing Fast
- Freelance potential
- Low
- Salary growth potential
- High (140% from entry to senior)
- Typical student debt
- Moderate
Skills you need as a Product Manager - Artificial Intelligence
Hard skills
- AI/ML Algorithms
- Machine Learning
- Neural Networks
Soft skills
- Technical Thinking
- Innovation
- Communication
Technical complexity: Very High
Tools of the trade
Core tools
- Jira (Software): Manages product backlogs, sprints, and issues for AI/ML product development.
- Confluence (Software): Documents product requirements, technical specifications, and AI model designs.
- Python (Language): Used for prototyping AI/ML models and understanding data science workflows.
Commonly used
- TensorFlow (Framework): Familiarity with this framework helps in understanding AI model development and deployment.
- AWS SageMaker (Platform): Manages the lifecycle of machine learning models from development to deployment.
- SQL (Language): Queries data for analysis, feature engineering, and understanding model performance.
Specialist tools
- Tableau (Software): Visualizes AI product performance metrics and user insights.
How to become a Product Manager - Artificial Intelligence
- Minimum education
- Bachelor's Degree in Computer Science or related field
- Licensing
- No
- Years to mid-career
- 5-7 years
- Years to senior
- 12-16 years
- Career switching
- Very Hard
Where this career leads
How people arrive here
- Data Scientist: Transitions from focusing on data analysis and model building to product strategy and market needs for AI solutions.
- Software Engineer (Machine Learning): Moves from implementing AI models to defining the product vision and roadmap for AI-powered features.
- Product Owner: Expands from managing a product backlog to leading the strategic direction of AI products.
Where you can go from here
- Head of AI Product: Advances to a leadership role overseeing multiple AI product lines and strategy.
- AI/ML Consultant: Applies expertise in AI product development to advise various clients on their AI strategies.
- Chief Product Officer: Progresses to a senior executive role, responsible for the overall product vision and strategy of a company.
Typical progression
- AI PM
- Senior PM
- AI Lead
- Product Manager
Product Manager - Artificial Intelligence job outlook and future demand
- Automation probability
- 4%, very low risk
- AI disruption risk
- Very Low
- Demand trend
- Growing Fast
Job satisfaction as a Product Manager - Artificial Intelligence
- Overall satisfaction
- 8.1/10
- Meaning
- 8.3/10
- Work-life balance
- 6.8/10
- Prestige
- 7.8/10
- Social perception
- High
Where practitioners gather
Podcasts and media
- Towards Data Science: A popular Medium publication covering data science, machine learning, and AI.
Online communities
- Product School: Offers courses and a community for product managers, including those in AI.
- AI Product Managers: A LinkedIn group for professionals focused on AI product management.
- Kaggle: A community for data scientists and machine learning engineers to compete and collaborate.