AI Product Management: Bridging Technology and Strategy

Over the last couple of months, I’ve been making it my mission to socialize as much as my schedule permits. While embarking on a new role at a new company demands a lot of your time (and honestly for me, lots of brain power too), I challenge my own reasons for staying in, choosing instead to actively engage and connect with others. Truth is, I find it empowering driving myself Downtown because I really want to, rather than a weekly obligation.

From former and new colleagues to old and new friends, from people reaching out to me for networking to newcomers in the Citizen development community and key figures in Calgary’s Product and Entrepreneurial scene, my once small world has expanded dramatically since I chose to broaden my horizons.

However, despite the wide variety of conversations sparked by each one of my social groups, I often find myself recounting the story of how I became an AI Product Manager with ATB’s A3 I Team (Advanced Analytics Artificial Intelligence), my almost ancient-Greece-level odyssey to get my new work permit (which I’ll tackle in a future article) and of course: what is it that I do in my new role.

So, what is it exactly that you do as an AI Product Manager again?

During the specialization on AI Product Management from Duke University I took last summer, I learned that an AI Product Manager is the evolution of Technical Product management. They are responsible for guiding the strategic development and management of AI-driven products. They bridge the gap between technical AI capabilities and the business's strategic goals, ensuring that AI technologies are effectively integrated into products to meet user needs, solve real problems, and drive value.

Since AI became a mainstream technology in November of 2022, the evolution of Artificial Intelligence has been exponential. Emerging as a game-changer, it is revolutionizing how businesses operate and innovate. AI's impact is far-reaching, affecting various sectors from finance to healthcare, and from customer service to customer relationship management. However, harnessing the full potential of these technologies requires more than just technological know-how; it requires a strategic approach to product management.

To be honest, I’m still shocked when I come across posts or learn that X company’s AI strategy hinges only on ChatGPT (or broadly speaking, on Generative AI). Instead of identifying valuable applications for advanced technologies like machine learning, neural networks, or deep learning, there seems to be a rampant rush among companies to come up with hasty strategies, driven by the constant fear of falling behind. This is precisely where the role of an AI Product Manager becomes critical.

Positioned at the crossroads of technology and strategy, AI Product Management plays an essential role in transforming AI capabilities into tangible business successes. Boosted by the relentless march of artificial intelligence, the world of product management is undergoing a paradigm shift. Even though our approach is still very much customer-centric, we are no longer solely focused on user interfaces and feature sets, modern product managers are increasingly tasked with navigating the complex fusion of cutting-edge technology and strategic vision.

The AI Landscape beyond 2024

Before diving into the intricacies of AI product management, a quick snapshot of the current landscape is essential. According to Next Move Strategy Consulting the market value for artificial intelligence (AI) of nearly 100 billion U.S. dollars is expected to grow twentyfold by 2030, up to nearly two trillion U.S. dollars, reflecting its extensive impact across industries. Chatbots, image generating AI, and mobile apps are all among the major trends improving AI in the upcoming years. From personalized shopping experiences to fraud detection in financial services, these trends are reshaping the way businesses operate and consumers interact.

It's clear that the field is not just growing; it's evolving in ways that promise to redefine how industries operate. And yes, among the most notable trends is the rise of Generative AI, which is set to revolutionize content creation, decision-making processes, and even the way we interact with digital interfaces. With leading products like Google Gemini, ChatGPT (GPT-4V) and Runway Gen-2, Multimodal AI is at the forefront of this revolution. Combining text, images, and audio to create AI models, Multimodal AI brings understanding and interaction with the world with a more nuanced and context-aware approach.

The Rise of the AI Product Manager

What I’ve quickly realized in the past 6 months is that in this dynamic landscape, traditional product management skills are no longer enough. A new breed of AI Product Managers is emerging, equipped with a unique blend of:

Technical understanding: Familiarity with core AI concepts, ML algorithms, and data science principles is essential for informed decision-making.

Data analysis skills: The ability to interpret and translate complex data insights into actionable product strategies is crucial.

Strategic vision: Balancing the technical possibilities of AI with the bigger picture business goals requires a keen understanding of market trends and competitive landscapes.

User empathy: Ultimately, AI products are about serving users. AI Product managers must retain a human-centric focus, ensuring that technology serves, not replaces, user needs.

So, going back to the potential AI brings to a wide number of industries, let’s focus on fraud detection in financial services as an example. Some of the smartest Banking Digital Assistants today are able to detect shifts in your spending patterns. This opens the possibility to trigger alerts to customers of a possible fraud of course, but diving even deeper they can also validate the authenticity of those spending shifts with you and even suggest a pre-approved limit increase to your line of credit.

A good Product Manager would go for a quick win and add Fraud Detection as a feature that results in direct benefits for the customer. A great AI Product Manager will roadmap the complete flow (fraud detection, spending validation and credit limit increase) to bring huge benefits for the customer and massive business value and profits to the corporation. Why? A survey by Gartner found that 86% of customers are willing to pay more for a better customer experience, leading banks to focus on personalized and interactive experiences. It was projected that by 2023, 25% of customer service operations would use virtual customer assistants, up from less than 2% in 2019.

Bridging the Gap: Key Strategies for AI Product Management

Successfully navigating the intersection of technology and strategy in AI product development requires a deliberate approach. Start with problem-solving, identify a clear and well-defined problem that AI can address effectively. Don't force-fit AI solutions onto existing products. Always remember that data is king: High-quality, relevant data is the fuel that drives AI engines. Invest in robust data acquisition and management strategies.

Embracing iterative development and rapid prototyping allows for continuous learning and refinement of AI algorithms. Don’t forget that a POC is only that, a proof of concept. Never stop development on your main product in favor of an untested idea. Agile experimentation is the key concept here, so don’t try to boil an ocean before starting work on a prototype.

Finally, AI Product Managers require a relentless commitment to ethical considerations and cross-functional collaboration. Ensuring transparency, fairness, and bias mitigation is not just a part of responsible AI development; it's a critical aspect that must be prioritized throughout the product lifecycle.

Equally important is fostering close collaboration between technical teams, including data scientists and machine learning engineers, product managers, executive leaders, and business stakeholders. This collaborative approach ensures that AI solutions are not only technologically advanced but also aligned with business goals and user needs.

What’s next on the agenda for AI Product Managers

The field of AI product management is still in its infancy, but its potential is limitless. As AI technology continues to evolve, we can expect increased integration of AI across diverse product categories: From healthcare, finance and education to manufacturing, energy and transportation, AI will permeate virtually every aspect of our lives. Focus on explainability and trust will become the norm. In time, this newfound trust will see the rise of human-AI collaboration. Rather than replacing humans, AI will increasingly augment human capabilities, leading to more productive and creative partnerships.

Overall, AI product management is a challenging yet rewarding field with the potential to shape the future of technology. By bridging the gap between technology and strategy, AI product managers will play a pivotal role in unlocking the transformative power of artificial intelligence for businesses and advocating for an ethical approach to AI for society as a whole.

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Additional Resources:

• AI Product Management Specialization – Duke University
• The AI-Powered Product Manager: Combining Strategy and Technology by Luis Jurado