Product Manager vs. AI Scientist: Which Career Path Should You Choose in 2025?
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Dear PBW Community,
We’ve been hearing a lot of questions within the community:
Should I pivot to AI?
Is product management still a strong long-term play?
Which path offers more opportunity in 2025 and beyond?
This article is for those of you navigating these choices. Whether you're looking to pivot, level up, or simply stay informed, here’s a clear, unbiased look at two of the most talked-about roles right now: Product Manager and AI Scientist.
Understanding the Roles
Product Managers are responsible for identifying user needs, aligning them with business goals, and working cross-functionally to bring products to life. They lead product strategy, manage roadmaps, define success metrics, and coordinate teams across design, engineering, and marketing.
AI Scientists focus on designing algorithms, training machine learning models, publishing research, and solving complex technical problems. They work in deep tech environments, often collaborating with researchers, engineers, and ethics teams to develop next-generation AI systems.
Career Growth Paths
A typical Product Manager path moves from Associate PM to PM, Senior PM, Director, VP, and eventually Chief Product Officer. The focus shifts from tactical execution to strategy and cross-functional leadership.
An AI Scientist typically starts as an intern or junior ML engineer, then advances to AI Scientist, Senior Scientist, AI/ML Manager or Architect, and eventually Head of AI or Chief AI Officer. Progress here means deepening technical knowledge and leading innovation.
Job Market in 2025
Product Management is highly competitive right now. As of May 2025, there is roughly one job opening for every 37 experienced applicants. Entry and mid-level roles are the most saturated, but leadership roles like Director and VP are still in demand. Remote roles are growing while hybrid and in-office roles are declining.
AI Science is experiencing rapid growth. In Q1 2025 alone, AI-related jobs grew over 25 percent year-over-year. The fastest-growing titles include AI/Machine Learning Engineer, Data Scientist, and Big Data Engineer. AI is expanding across all industries—not just tech—and roles are becoming more strategic and well-compensated.
Compensation Comparison
Entry-level Product Managers earn approximately 86,000 to 126,000 dollars per year. Mid to senior PMs earn around 126,000 to 195,000. Top PMs, such as VPs or CPOs, can earn over 230,000.
AI Scientists start slightly higher, around 98,000 to 127,000. Senior scientists often earn 128,000 to 182,000. The top 10 percent in this field may earn up to 234,000.
While Product Managers can out-earn AI Scientists at the executive level, AI professionals tend to earn more earlier in their careers. Total compensation can vary significantly depending on company, location, equity, and bonuses.
Skill Sets Required
Product Managers need strong business acumen, strategic thinking, user empathy, and leadership skills. They are not usually expected to code but must understand how technology is built and delivered.
AI Scientists require deep technical expertise. This includes proficiency in programming languages like Python, understanding of machine learning frameworks, statistics, research, and the ability to run complex experiments and models.
Which Career Path Is Right for You?
Choose Product Management if you enjoy shaping product direction, collaborating across teams, solving user problems, and thinking about both business and customer needs.
Choose AI Science if you are passionate about data, algorithms, and cutting-edge research. If you enjoy solving hard problems through technical experimentation, this could be your space.
There’s no one-size-fits-all answer. Both paths are valuable. The best choice comes down to your strengths and what kind of work energizes you.
Thinking About Switching?
If you’re a Product Manager curious about AI, start by taking online courses in machine learning or AI fundamentals. Join or advocate for AI projects at work. Consider building a side project using AI tools to showcase initiative.
If you’re an AI professional looking to transition into product, begin by working with product teams, learning about product strategy and roadmapping, and getting involved in customer discovery and research. Hybrid roles like AI Product Manager can also be a great fit.
Final Thoughts
There is no definitive answer to which role is better. Both are in demand and offer long-term growth—just in different ways.
If you lean toward leadership, customer strategy, and product development, product management is a great path.
If you prefer technical innovation, research, and algorithm development, AI science may be more aligned.
Whatever you choose, stay curious, stay adaptable, and keep learning.
Want to continue the conversation? Reach out to us at info@productsbywomen.com — we're planning a roundtable soon for anyone navigating career decisions like this.
— Team Products by Women