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AI and Ethics in Product Management

Written by
Andrea Saez Andrea Saez
Product Leader & Author

Artificial intelligence has seen a massive uptick in adoption across various industries and applications within the last year. "Powered by AI" is practically a stamp promising next-level innovation; it is truly inescapable. Yet amid the rush to brand every product with this shiny new label, many overlook the serious considerations needed before haphazardly integrating AI. Beyond keeping up with the latest industry trends and buzzwords, there is a level of responsibility and ethical considerations all product managers must keep in mind.

What to consider before you dive in

Let's clarify a critical point: mastering AI is not a catch-all skill but a specialized application of technology. Just as a screwdriver doesn't define a craftsman, AI doesn't define your product. It's a tool to solve particular problems or to offer specific enhancements. The first step for any product manager is to identify what those are. If you can't clearly articulate how AI will improve your product, then you might want to reconsider why you're using it in the first place.

With that in mind, before taking the AI plunge, your roadmap must include a comprehensive ethics checkpoint. This is a foundational part of responsible product management. Just as asking “what” and “why,” we need to take a minute to understand how what we’re doing is affecting future use.

"Just as a screwdriver doesn't define a craftsman, AI doesn't define your product"

Andrea Saez, Product Leader & Author

Key ethical considerations

Data Bias

Data sets train AI models. Therefore, data free from discriminatory or unfair bias is required. Poor training data perpetuates existing inequalities and can even create new ones.


Choose an AI model that allows for ethical auditing. This ensures that stakeholders can trace how decisions are made, a significant factor when accountability is on the line.

User Impact

Ensure that the AI feature offers real utility to the user. If the AI component doesn't help the user or, worse, misleads them, you've not only failed at providing a valuable feature, you've crossed an ethical line.

Stakeholder engagement

Think beyond the user. Engage with community representatives, ethicists, and even regulatory bodies. These interactions can offer perspectives that may minimize ethical blind spots, making your AI integration more responsible and rounded.

Data Privacy

Compliance with data privacy laws is just scratching the surface. Go further by ensuring robust anonymization and security measures are in place for user data. If you are using a third-party AI model, educate yourself around how it is being trained in the first place.

Opt-Out Options

Provide clear pathways for users to opt-out of AI-specific features. This enhances user autonomy and is a mark of ethical responsibility (refer to point above, especially if all data is being processed by a third-party AI model.)


Ensure your AI features are inclusive. From different languages to accommodating those with disabilities, your AI should be as accessible as possible to ensure equitable benefit.

Continuous Monitoring

Post-launch, don't take your eye off the ethical ball. Maintain ongoing oversight on how the AI's real-world performance aligns with your ethical guidelines and make adjustments as necessary.

By addressing these points in detail, you're integrating ethical considerations into every phase of your product's life cycle. This isn't ethics for the sake of optics, it’s really about ensuring that you’re providing a solution that still provides value at every point of interaction.

Shaping user behaviour

All products and features change behaviour in some way. By providing a solution, you’re allowing the user to do things differently somehow – and when those behaviours become repeatable over time, you are having a serious impact as to how people interact and behave within (and sometimes outside) of the boundaries of your product. AI is no different.

With its powerful ability to analyze data and predict outcomes, AI can nudge users towards certain actions more effectively than many other types of technology. But as they say, with great power comes great responsibility. Are these nudges leading users towards behaviors that are in their best interest? Or are they steering users in a direction that primarily serves the business or some other agenda?

For example, think of a social media algorithm that promotes content favoring a particular political stance. It may lead to tunnel vision among its audience, skewing their perception of reality. The product team needs to scrutinize: are we promoting a balanced view, or are we inadvertently pushing an agenda? (aherm, X.)

The good news is that there is a way to map out user behaviours and ensure we’re tracking value accordingly.

The Product Value Creation Plan (VCP) from the book “The Product Momentum Gap” serves as a comprehensive framework for aligning user behaviors with your product's core value proposition. Beyond integrating key aspects of your product strategy, such as target audience, problem-solving capabilities, and use cases, it takes an extra step to include the specific behaviors you aim to influence and the associated perceived value.

What’s important to remember here is that AI is not the solution, but rather a way to implement a solution. Like any other feature being built, one must always take a step back and ask: “what problem are we trying to solve?”


It's crystal clear that the power and allure of AI come with ethical strings attached. Beyond shiny object syndrome, it's a transformative feature that, when improperly managed, can carry far-reaching consequences. It demands more than just a nod toward ethical considerations, and calls for a full-scale, deliberate approach to responsible implementation.

There's a shared responsibility among product managers, developers, and stakeholders to not just ask what AI can do, but what it should do. By closely examining issues like data bias, transparency, user impact, and stakeholder engagement, we can more effectively wield the power of AI in a manner that adds real value to users while respecting ethical boundaries. These considerations are a key pillar to ensuring that your roadmap and product development remain ethical.

Our role as product managers extends beyond maximizing features and capabilities. It involves guiding products through the nuanced ethical terrain that comes with technology as potent as AI. Leveraging frameworks like the Product Value Creation Plan allows us to align user behaviors with value creation in an ethical manner, ensuring that we’re delivering innovative and conscientious solutions.

Remember, in a world where products increasingly shape behavior, the products we build today will help define the societal norms of tomorrow.



Andrea Saez

Andrea Saez
Product Leader & Author

Andrea has collected expert knowledge from over a decade of bridging the gap between product and customers, in a specialisation now known as product marketing.

Working with ambitious start-up's and scale-ups including ProdPad, Airfocus, and Trint, she has influenced and executed strategy, positioning, and cross-team collaboration. She is a go-to advocate for best-practice product road mapping and is active in the product community as a speaker and writer.

Author of The Product Momentum Gap: Bringing together product strategy and customer value, where you can  uncover the transformative power of the Product VCP (Value Creation Plan), a comprehensive blueprint for aligning your teams in creating genuine value for the customer

Author of The Product Momentum Gap:

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