AI and PO: Partnership instead of competition

For many product owners (POs), a large part of their daily routine consists of administrative work: maintaining tickets, formulating requirements, sorting information. This is precisely where artificial intelligence (AI) is becoming increasingly powerful. It can structure texts, offer variants, recognise patterns and speed up routine tasks. In many areas, it already does this better than some product owners. It is therefore not surprising that there is widespread concern that the role could become less important.

However, the real question lies deeper: what does AI actually do and what is at the core of product ownership? The clearer the answer to this question, the clearer it becomes that AI is changing the role, but not its core. It is becoming a partner for efficiency, not a competitor for responsibility.

This creates an opportunity for product owners: less time for administration, more space for decisions, value and orientation. This is precisely where the work begins that artificial intelligence cannot (yet) perform. [1]

AI automates administration, but not responsibility

AI is powerful when tasks are clearly structured. It can formulate initial story drafts from notes, suggest test case ideas, cluster support messages or convert information into useful formats. This support saves time and reduces errors. However, all of this relates to areas that are often confused with the PO role, but do not form its core. [2]

The core of product ownership is not writing tickets. It lies in making decisions. Understanding value, justifying priorities, identifying risks, weighing options, supporting stakeholders, and providing guidance. These are tasks that require context and responsibility. AI can make suggestions, but it cannot decide what is right. It can provide analyses, but it cannot take responsibility for them.

This highlights a fundamental point: it is not the role of the product owner that is at risk, but rather an overly narrow understanding of it. When organisations reduce POs to administrative tasks, they create an image that AI could actually replace. However, when product owners are responsible for value and direction, AI actually strengthens this work.

The PO role is interpreted differently, which creates uncertainty

In practice, there is a wide spectrum of how the role is interpreted. Some product owners work closely with strategy, market, stakeholders and development teams. Others focus on formulating requirements, maintaining the backlog or clarifying minor details.

Both approaches are common and arise primarily from structures and expectations, not from personal decisions. Teams, processes, and management systems shape the role. Job descriptions often emphasise operational activities. In some companies, strategic responsibility lies with product managers, line managers, or committees. In such contexts, the role automatically becomes more operational.

This is neither wrong nor unusual, but it can lead to confusion when the term product owner is associated with ownership.

There are also environments in which POs consciously make decisions, steer value and moderate conflicting goals. In these environments, AI is not seen as a burden, but as a relief. It reduces overhead and creates time for what the role is really about.

The key point is therefore that the role of the product owner is clearly defined, but is interpreted differently in everyday life depending on the company and context. AI shows more clearly which activities are administrative and which require real creativity. It is precisely this clarity that helps POs and teams to live and develop the role more consciously.

Collaboration remains at the core of the role, and that is where the strength of AI ends

The value of a product owner rarely arises from working alone. It arises from exchange. Good product decisions are based on joint discussions in which teams test assumptions, assess risks, clarify goals and set priorities. This negotiation is often emotional, complex and full of uncertainties.

This is precisely where the strength of AI ends. It can formulate texts, but it cannot recognise tensions in the room. It can organise options, but it cannot assess which compromises are viable. It can collect arguments, but it cannot shape relationships.

An example from regulated areas illustrates this clearly: anyone who has to take medical workflows, MDR requirements or clinical risks into account needs not only facts, but also judgement. AI can process data here, but it cannot decide how to balance patient safety, market requirements and technical feasibility. Even beyond regulated environments, the central task remains human: providing guidance, managing expectations and representing decisions.

This makes it clear that collaboration, moderation and contextual understanding are not becoming less important, but more central. AI facilitates the peripherals. However, it does not replace the core.

How POs can use AI effectively and strengthen their role

For AI to become a partner, conscious decisions need to be made in everyday work. The following levers have proven to be effective:

Use AI for routine tasks.

Story drafts, summaries, test case ideas, research or sorting information are ideal use cases. What AI does faster gives POs more freedom to take on responsibility.

Actively shape context.

AI provides many suggestions, but no reason why something is important. POs set priorities, justify decisions and combine technical, professional and human perspectives. This work remains exclusively human.

Strengthen collaboration.

Good product development comes from dialogue. Product owners who create spaces for dialogue, prepare decisions and moderate conflicts increase impact and speed. AI can support, but not lead.

Clarify role understanding.

In many teams, it is unclear what a PO is really supposed to do. Those who actively clarify expectations can strengthen their own role and resolve misunderstandings.

Develop AI competence.

Product owners do not need to be experts. It is enough to know the strengths and limitations of AI and to use it in a targeted manner. This skill becomes part of professional product work.

This creates a true partnership: AI takes over routine tasks, POs take over direction.

Conclusion

AI is changing the work of product owners, but not its core. It takes over routine tasks and highlights which tasks are administrative and which generate value. In doing so, it does not question the role, but rather its practical understanding.

Where POs primarily write tickets and sort information, AI will significantly reduce their workload. Where POs bear responsibility, provide guidance and prepare decisions, AI becomes a tool, not a replacement.

This does not weaken the role, but rather sharpens it. AI reveals what really matters: responsibility, clarity and collaboration. This is precisely where the work begins that no model can take over.

AI and PO are therefore not in competition. They form a partnership. The machine ensures efficiency, the human being provides direction. And it is precisely this connection that makes successful product development possible.

Notes:

[1] Amara’s Law states that we tend to overestimate the impact of a technology in the short term and underestimate it in the long term. Accordingly, this article might be written differently in 2030.

[2] The Scrum Guide deliberately defines Product Owner not as a role, but as a so-called accountability, i.e. a responsibility. Nevertheless, in many organisations it continues to be a role.

Here you can find a German podcast episode from ‘Die Produktwerker’ about the influence of AI on product development.

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Michael Schenkel has published further articles on the t2informatik Blog, including: