The Invisible Role Reshaping Product Teams

Business Analysts are quietly disappearing from product teams. Once essential for translating business needs into specifications, their traditional role is now increasingly automated, absorbed, or rendered obsolete by new ways of working. Simultaneously, Product Owners (introduced by Scrum as a keystone role) are also beginning to lose relevance. Their responsibilities are often misunderstood, fragmented, or reduced to a glorified Jira admin. In many organizations, POs are stuck in delivery cycles without real influence over product vision or strategy.

This isn’t about job titles vanishing overnight; it’s about a more fundamental shift in how we build digital products and what kinds of thinking those products require. Agile, as a movement, flattened hierarchies and made room for cross-functional collaboration. But now we are in the midst of a deeper transformation: one driven by AI, systemic complexity, design thinking, and product-led growth. And this new landscape demands more than just writing user stories or managing sprint backlogs.

Teams today don’t need a middleman to gather requirements. They need someone who can shape the actual thinking behind a product. Someone who can distill complexity into clarity, orchestrate meaning across disciplines, and challenge assumptions before a single line of code is written. That person might still be called a “PO” or “BA” on paper; but in reality, the role is morphing into something else entirely.

We are seeing the rise of a new archetype; a hybrid that blends strategic foresight, systems design, product intuition, and a kind of cognitive facilitation that’s hard to name with legacy labels. This emerging role doesn’t just gather or prioritize work; it designs the very mental architecture of how a team reasons, makes trade-offs, and defines value. It's a role less focused on delivery mechanics and more on how thinking happens across a product lifecycle.

Some organizations are already evolving in this direction. Spotify has experimented with roles like Product Insights Leads, which combine discovery, user research, data, and strategic framing into one function. Design consultancies like IDEO or Fjord embed design strategists who don’t own roadmaps but shape the way roadmaps come to life. At Google, certain AI-focused teams now employ people who understand model behavior, product constraints, and user expectations all at once; roles that sit between research scientist, product manager, and UX designer.

In each of these examples, the same pattern emerges: someone is actively shaping the invisible scaffolding of decision-making. They're designing workshops, simulations, model prompts, service blueprints, or experiments; not because they’re facilitators or designers per se, but because they understand that modern product development is less about control and more about crafting the conditions for meaningful progress.

This person might start their day reviewing AI-generated customer feedback summaries, draft three different conceptual flows for a new feature, map stakeholder incentives for an upcoming pilot, and then lead a session to uncover hidden assumptions in the team’s current success metrics. They think in loops, not lines. They prioritize coherence over speed. And they are comfortable working in ambiguous domains where there isn’t a single clear right answer.

AI will accelerate this transformation. Already, tasks that defined traditional BAs; like documenting flows, mapping requirements, comparing features, are increasingly handled by language models and analysis tools. Similarly, POs stuck in backlog refinements or acceptance criteria hell are slowly being bypassed by teams who can visualize and test ideas directly with AI-assisted design and prototyping platforms. As automation eats up the transactional layers of these roles, what’s left is the work that cannot be easily automated: curiosity, synthesis, pattern recognition, critical reframing, and guiding humans toward better collective decisions.

This isn’t a role for everyone. It requires radical contextual intelligence, fluency in different modes of thinking, and emotional maturity. It’s someone who can read a market signal and a stakeholder's anxiety in the same breath. Someone who knows that good strategy is not a document but a living conversation, and has the tools to host that conversation well.

If you're a Product Manager looking to sharpen your edge in the age of AI, The AI-Powered Product Manager by Luis Jurado is a must-read. It offers a clear, practical roadmap for integrating machine learning into product strategy, no data science degree required.

Maybe it won’t be called “Product Designer of Thinking.” Maybe it’ll emerge under titles like Strategic Product Lead, Discovery Architect, or AI-Enhanced PM. But the function is already emerging, piece by piece, across progressive product organizations. It’s not about replacing POs or BAs; it’s about transcending the limitations of those frames entirely.

In the end, the ones who will thrive in this new terrain won’t be the ones clinging to familiar titles. They’ll be the ones comfortable designing thinking itself.