The Imperative for AI Upskilling

A Tech PM’s Perspective Amidst Uncertainty

Background

I was just laid off in Q4 of 2024 from a Fortune 100 company. As I sat in contemplating my future in the tech industry, the reality of potential layoffs everywhere looms even larger.

To be honest, its pretty obvious - The job market is very bleak for PMs.

Yet, amid this uncertainty, I find myself more determined than ever to embrace the transformative power of Artificial Intelligence (AI) in product management.

Every day, I see new headlines about AI reshaping tech. I want to be a part of that wave. I want to upskill, thrive, and help lead this shift. Firms are pouring money in, but they need people who get AI’s nuances. That’s you and me.

Hence I started writing about my “Learn with me series” in my newsletter recently

As we move toward 2025 & beyond, the integration of AI in product management is not just an option; it is imperative for staying competitive.

The Hard Truths on AI

• A recent KPMG AI Quarterly Pulse Survey shows that nearly 70% of leaders want to spend between $50 million and $250 million on generative AI in 2025. But only 31% expect to see a measurably clear ROI in the next six months. Source: The ROI Puzzle of AI Investments in 2025

  • KPMG also reveals 85% of leaders worry about data quality, and 71% fret over privacy and cybersecurity. We’re eager to adopt AI, but real concerns slow us down.

• Microsoft's 2024 Work Trend Index Report reveals 79% of business leaders agree that their company needs to adopt AI to stay competitive, a lack of clear AI vision and pressure to showcase immediate ROI is stalling plans for widespread adoption. Source: Microsoft's 2024 Work Trend Index Report

• Talent Shortages: A lack of skilled professionals capable of implementing AI technologies hampers progress. Only 7% of organizations have reached a high maturity level in their AI adoption journey.

• Governance and Compliance: Over 50% of IT leaders cite governance as a primary barrier to AI adoption. The need for structured frameworks to ensure compliance complicates implementation efforts.

This gap presents both risk and opportunity. As a Product Manager, I see the tension: we crave AI benefits, yet we’re afraid of mistakes and wasted budgets.

We are investing big, yet we’re unsure when—and how—it will pay off.

But Are We Ready?

The role of the Product Manager (PM) is rapidly transforming. As a PM, I feel this dilemma acutely. On one hand, there’s the promise of AI to revolutionize our workflows; on the other hand, there’s a pervasive fear of job displacement and a lack of understanding about how to leverage these technologies effectively.

Traditionally, PMs acted as the bridge between engineering teams and market demands. Today, they are expected to be strategic thinkers who can harness AI's capabilities to create data-driven insights.

Imagine a world where AI enhances every aspect of product management—from user research to feature prioritization—allowing us to innovate faster and make data-driven decisions with confidence. (Note: I will write a detailed post on the AI tools like chatprd, bolt, etc. I have encountered that helps PM to become 10x)

Yet, many of us are still hesitant, caught in a cycle of skepticism and fear.

Why are we waiting on the sidelines when the future is beckoning?

The Need for Upskilling in AI Product Management

Andrew Ng aptly noted, "Given a clear specification for what to build, AI is making the building itself much faster and cheaper." This highlights the critical role of well-defined product strategies in harnessing AI's capabilities.

As AI technologies advance, the skill set required for effective product management is changing. Here are key areas where PMs Andrew also mentions we need to focus on upskilling:

• Technical Proficiency: Understanding AI fundamentals is crucial. PMs must grasp what is technically feasible and how AI can be integrated into products.

• Data Literacy: AI products rely heavily on data. PMs should be comfortable with data analysis to inform product decisions and strategies.

• Iterative Development: Unlike traditional software development, AI projects often require ongoing adjustments based on real-world performance. PMs must adapt to this iterative process.

• Managing Ambiguity: AI can be unpredictable. PMs need strategies to navigate uncertainty and make informed decisions despite it. We also need to advocate to creating products that foster trust and transparency among users.

• Continuous Learning: The pace of AI innovation means that staying updated on the latest trends and technologies is essential for PMs

Bridging the Gap Between Teams

AI product managers play a vital role in simplifying complex technical processes for non-technical stakeholders. They ensure that everyone—from engineers to marketing teams—understands how AI can enhance product offerings.

This bridging function is critical as organizations increasingly rely on cross-functional teams to innovate rapidly.

But the journey won’t be easy. Find out why.

PM bridges the Organization’s Innovators and Skeptics

Laggards—those who adopt technology only when it becomes essential—play a critical role in shaping market dynamics. Their reluctance often stems from:

• Risk Aversion: Many organizations prioritize reliability over innovation, leading them to delay adopting new technologies until they are proven.

• Resource Constraints: Limited budgets and personnel often prevent laggards from experimenting with AI solutions, leading to missed opportunities.

Understanding these concerns allows product managers to tailor strategies that address hesitations while promoting the benefits of AI adoption.

This involves:

• Open Dialogue: Encouraging discussions that address concerns while highlighting potential benefits creates an inclusive environment conducive to innovation.

• Iterative Implementation: Starting with smaller projects that demonstrate tangible results builds trust in AI capabilities over time.

• Continuous Feedback Loops: Establishing mechanisms for ongoing feedback allows teams to adapt quickly based on user experiences and concerns.

• Showcase Success Stories: Highlighting case studies where AI has successfully improved processes can help alleviate fears associated with new technology.

• Provide Hands-On Training: Offering training sessions on how AI tools work can demystify the technology and build confidence among skeptical stakeholders.

While embracing this shift, it is equally important to acknowledge and address skepticism surrounding it.

By understanding both sides of the conversation—advocates and naysayers—product managers can navigate this evolving landscape more effectively.

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Conclusion: A New Beginning

Yes, layoffs hurt. Yes, times are tough. But AI is growing fast. I’m on a journey to learn, build, and adapt. It’s not easy, but it’s the best plan I have.I’m documenting it all in my “Diary of Learnings.”

Here, I have personally outlined a thoughtfully structured curriculum as a map divided into different themes. Each level progresses from foundational AI concepts to advanced agentic workflows, ensuring that traditional product managers transitioning into AI roles have a clear roadmap. If you want to start now, this is the best place.

Join me. See how AI can reshape our careers, one step at a time.

→ Subscribe here:

Let’s turn this uncertain season into our next chance. It all starts with AI—and it starts now.

P.S. If you're aware of any exciting AI Product Management opportunities in India, please feel free to reach out to me at ravi@ravitejapalanki.com. I’d love to connect!

Find me on LinkedIn and this is my personal website for more learning themes.

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