As artificial intelligence continues to reshape industries, a new role is emerging at the intersection of technology, strategy, and innovation: the AI Product Manager. This isn’t just a passing trend—it’s a reflection of how integral AI is becoming in the development and optimization of modern products.

To succeed in this evolving role, AI product managers must do more than understand traditional product lifecycles. They’ll need to navigate complex AI and machine learning (ML) systems, evaluate performance metrics, and ensure responsible, ethical deployment of technology. That requires a unique blend of technical acumen, data fluency, and cross-functional leadership.

Core Competencies of Future-Ready AI Product Managers

To lead in this space, product managers should develop proficiency in the following key areas:

• AI-Specific Technical Competence – Understanding how models are built, trained, tested, and deployed.

• Data Science Knowledge – Ability to interpret data, partner with data teams, and drive data-informed decisions.

• Model Performance Evaluation – Knowing how to measure, optimize, and communicate model performance.

• Ethics, Bias, and Regulation – Staying informed about legal and societal implications of AI systems.

• Education and Influence Management – Evangelizing AI within the organization and aligning diverse stakeholders around AI initiatives.

Why Every Product Manager Needs AI Skills

Just as “internet product managers” were once a niche, only to evolve into the standard model of digital product management, AI is on track to become a core element of every product manager’s toolkit.

According to Forrester, AI will become so embedded in product development that PMs who lack foundational AI knowledge may find themselves at a disadvantage. Generalist product managers won’t need to be AI engineers, but they will need to understand how to integrate AI into product features, make informed trade-offs, and iterate based on user feedback and AI performance.

How Product Leaders Can Prepare Their Teams

Leadership plays a crucial role in preparing product teams for the AI-powered future. That means more than just encouraging learning—it means building a culture that values experimentation, continuous education, and hands-on practice.

Here’s how leaders can start:

• Offer AI literacy programs tailored for non-technical professionals.

• Create hands-on experiences through internal projects, hackathons, or partnerships with AI teams.

• Provide access to online, interactive courses and workshops that blend theory with application.

• Recognize and reward team members who take the initiative to upskill.

Conclusion

AI isn’t just a buzzword—it’s rapidly becoming a foundational element of modern product strategy. As such, the AI product manager role is not only growing but evolving into a key pillar of the future workforce.

Product leaders who invest in upskilling today will set their teams up for long-term success, ensuring they’re not only keeping up with the market but helping to define it.

FAQs

Q: What skills do AI product managers need?
A: They should develop AI-specific technical knowledge, data science fluency, the ability to evaluate AI performance, a strong understanding of ethics and regulation, and the ability to educate and influence across teams.

Q: Why is AI knowledge becoming essential for all product managers?
A: AI is becoming a standard part of digital products. PMs will need to understand how to apply AI responsibly and effectively to remain competitive and meet evolving customer expectations.

Q: How can leaders support their teams’ AI/ML development?
A: Provide access to literacy courses, create hands-on learning opportunities, encourage cross-functional collaboration, and foster a culture of curiosity and continuous learning.

Data and analytics are no longer just about crunching numbers and generating reports. They are now a key driver of business success, helping organizations to optimize operations, improve decision-making, and stay competitive in a rapidly changing world.

Why Data and Analytics Matter

Data and analytics help organizations to:

• • Gain insights into customer behavior and preferences

• • Identify areas for improvement and optimize operations

• • Make data-driven decisions, rather than relying on intuition or anecdotal evidence

• • Stay ahead of the competition by being more agile and responsive to changing market conditions

The Challenges of Data and Analytics

While the benefits of data and analytics are clear, many organizations struggle to implement effective solutions. This can be due to a range of factors, including:

• • Limited resources, including budget and personnel

• • Complexity and technical difficulties in implementing and maintaining data analytics solutions

• • Lack of expertise and knowledge in data analysis and interpretation

• • Resistance to change and cultural barriers to adopting new technologies and processes

Overcoming the Challenges of Data and Analytics

While the challenges of data and analytics are real, there are many ways to overcome them. This can include:

• • Seeking expert guidance and support to help implement and maintain data analytics solutions

• • Investing in employee training and development to build in-house expertise

• • Starting small and gradually building up capabilities and expertise

• • Building a strong business case and demonstrating the value of data and analytics to stakeholders

Conclusion

Data and analytics are no longer optional, but a crucial part of any digital transformation strategy. By gaining insights into customer behavior, identifying areas for improvement, and making data-driven decisions, organizations can stay ahead of the competition and achieve their goals.

Lagging In HR AI And Automation

There are lots of great ways companies can use AI within HR to drive improvements in EX. Did you know, for example, that 54% of respondents to one survey said they had given up on applying for a job they wanted due to poor communication from the employer?

Other opportunities include providing personalized onboarding, reducing administrative work by automating repetitive tasks, engagement tracking and improving many aspects of performance management.

Over-Automating Employee Experience

On the other hand, AI still presents a huge number of challenges, particularly when it’s mixed with humans! And while many companies will make the error of under-investing, just as many will, unfortunately, end up using it in ways that are potentially damaging.

Failing To Offer Personal Development Opportunities

This is critical for both retaining existing employees and attracting new talent. Technology is quickly reshaping industries, but workforces need trained and skilled employees to take advantage of this. Offering career progression planning, upskilling and retraining aimed at empowering them to use technology helps people feel they are investing in their own futures by sticking with a business.

Failing To Measure EX ROI

Investing in EX initiatives without a clear plan or milestones in place for measuring success risks wasting money without delivering tangible benefits.

Neglecting Employee Mental Health And Wellness

Workplace stress and burnout are at an all-time high. In fact, the World Health Organization reports that the US economy loses $1 trillion every year thanks to lost productivity caused by depression and anxiety.

Final Thoughts

Employees are a company’s most important resource, and neglecting EX in 2025 means they will quickly start looking elsewhere. This can be a disaster when business success is more dependent than ever on attracting and retaining the right people!

Conclusion

The message I want to get across is that every business should take a strategic approach to EX, taking care to understand how success or failure will impact goals and overall performance. Invest in staff through training, professional development and wellbeing initiatives, and they will pay you back with loyalty, growth and business success!

FAQs

• What is employee experience (EX)?
  • EX is the sum of all experiences an employee has in a company, including their interactions with colleagues, supervisors, and the organization itself.
• Why is EX important?
  • EX is important because it can directly impact employee productivity, retention, and overall job satisfaction.
• What are some common pitfalls companies make when it comes to EX?
  • Some common pitfalls include lagging in HR AI and automation, over-automating employee experience, failing to offer personal development opportunities, failing to measure EX ROI, and neglecting employee mental health and wellness.
• How can companies improve EX?
  • Companies can improve EX by providing personalized onboarding, reducing administrative work, offering career progression planning, and prioritizing employee mental health and wellness.