Are AI Product Managers The Role Of The Future?

In the early days of the internet, job opportunities for “internet product managers” began to appear as companies recognized their need for this new technology. As the internet evolved, other roles such as “web product manager” or “digital product manager” became common. While these roles to some extent still exist, having internet experience is now an expected prerequisite for most product management roles. Today, you are probably seeing more “AI product manager” or “AI product owner” job titles. A Google search on “AI product managers” today reveals anywhere from a thousand of these roles to over twenty thousand jobs with these title or skills requirements.

While “AI PMs” might go the way of internet product manager in the future, today it is clear that there is a demand for individuals with traditional product management skills and AI-specific expertise.

Key Areas Of Proficiency Are Required For The AI Product Manager

• AI-specific technical competence: AI product managers will need to demonstrate an understanding of AI and machine learning technologies and how AI models are trained, tested, and implemented.
• Data science skills: As AI models are dependent on their underlying data, AI product managers will need to deeply understand data requirements, quality, and potential biases that will impact a model’s performance.
• AI model performance: An AI product manager will need to understand how AI models are developed and iterated with the goal of improving usability, accuracy, reliability, and scalability along with the time and costs involved in that process.
• Regulatory, ethics, and bias understanding: AI models sometimes replicate biases in the source data for the models. An AI product manager will need to understand the sources and effects of these biases and how to test for them, as well as an understanding of how privacy, regulatory, and ethical issues should be managed.
• Education, evangelization, and influence management: Given that generative AI is a quickly evolving technology, AI product managers will be called on to evangelize the business benefits and bring stakeholders up to speed.

Many of the challenges today for the AI product manager will differ slightly from those of their traditional colleagues. More than working on product features, AI product managers are focused on model performance, acceptable error rates, understanding new types of user interaction, and management of risk and cost trade-offs. Of course, core similarities remain: the focus on solving real customer problems, setting vision and strategy, roadmap prioritization and trade-offs, stakeholder management, and working with marketing, sales, and customer success.

Every Product Manager Will Be An AI Product Manager, So Start Learning Today

Just as the “internet product manager” evolved to become a component of today’s standard product management practice, Forrester predicts that AI will also become part of the standard product manager’s role in the future. Generalist PMs will need a baseline understanding of AI so they can thoughtfully integrate AI capabilities into existing products and continually improve those capabilities based on technology changes and customer feedback. They will also need to understand the basics of model behavior, data privacy, and ethical considerations.

Product Leaders Must Support Their Teams’ AI/ML Learning

Product management leaders must take a strategic approach to upskilling their teams about AI and ML by fostering a culture of learning and providing hands-on experiences. A good start is providing AI literacy courses (such as those from Coursera or LinkedIn Learning), hands-on learning opportunities like AI hackathons or instructor-led AI bootcamps, and online interactive options such as Google’s ML crash course. Finally, product leaders must encourage team members to experiment with today’s popular tools in their everyday lives. A suggestion: Make one day a week a “no search engine” day, encouraging use of AI tools instead.

Register to attend Forrester B2B Summit North America from March 31– April 3 in Phoenix Arizona, or online to learn more about AI product strategy in a fast-changing world.

This post was written by VP, Principal Analyst Lisa Singer and Principal Analyst Tony Plec and it originally appeared here.