How AI is transforming product teams and why measuring behaviour matters
At Product Day 2025, several keynote speakers shared their insights on the evolution of product work, the role of AI, and the challenges today’s product teams face. Afterwards, we spoke with one of the keynote speakers, Büşra Coşkuner, about AI in Product Management and how this technology is reshaping the role of Product Managers.
Büşra is a product coach, trainer and internationally known as “The Metrics Lady”. In her keynote at Product Day 2025, “What gets measured gets gamed”, she explained why poor metric choices send product teams in the wrong direction, and why behaviour change matters more than data alone.
The impact of AI on product teams
The benefits of using artificial intelligence as a Product Manager
1. AI makes product work faster and cheaper
According to Büşra, the first major shift is obvious: AI drastically accelerates work.
“We can do the repetitive daily tasks much faster. Writing documents, micro-research, creating prototypes for testing... Low-complexity or repetitive tasks go quicker. We still need human judgement to understand the quality of the output and to handle complex and strategic tasks but the time savings are enormous.”
It’s not ChatGPT, she notes, but specialised models and tools that make the biggest difference. They deliver higher quality, save time, and make products quicker and cheaper to build.
“What used to take weeks of engineering time, we now build in days if we use the right models and tools. Which also requires the companies and teams to work in a different way than today.”
2. AI removes bottlenecks
A second advantage, according to Büşra: AI democratises small but crucial tasks and gives teams more power. Examples include:
- Designers who can deliver first code versions
- PMs who solve small UX issues themselves
- Teams running usability tests faster
This reduces pressure on engineering teams.
“Small improvements that used to be postponed can now be tackled immediately. That makes teams more agile and improves quality.”
New challenges for product teams created by AI
1. Increased workload
Because AI speeds everything up, leadership teams expect PMs, designers and engineers to deliver faster as well.
“Now that everyone can do everything ‘a little bit’, organisations expect everyone to do more. That increases workload and stress.”
2. Hallucinations undermine product work
Like many others, Büşra warns against blindly trusting AI output. She refers to the recent example of Deloitte Australia, where an AI-generated report full of inaccuracies and fabricated sources was published.
“AI is not a shortcut for thinking. You need to know when it’s right and when it becomes dangerous.”
3. AI-generated output puts product teams under pressure
AI-generated mockups and prototypes can be extremely convincing sometimes too convincing.
“People end up debating the colour of a button while the real problem lies in the core value of the product.”
Sales teams also present AI-generated prototypes, putting pressure on product teams to build “something that looks good”, even when it’s not feasible.
4. Privacy and the European AI lag
Another major concern is that Europe currently lacks strong alternatives to US and Chinese AI models.
“In Europe, we care about privacy. Companies, public authorities, and many consumers quite rightly don’t want to send sensitive information to the US or China, two countries that generally don’t value privacy to the same extent. This hesitation slows down AI adoption and, in the long run, risks putting us at a disadvantage. To avoid that, we need our own AI models built on European values such as privacy protection and respect for individual human rights. Initiatives like Mistral and Apertus (Swiss Ethical AI) are already moving in this direction. Proton is also working in this space, developing privacy-first AI models.”
The role of Product Managers is fundamentally changing
AI requires stronger fundamentals and critical thinking
Büşra sees it daily while coaching companies. AI requires Product Managers to know and do more, not less.
Although AI takes over much of the execution, Product Managers must now be stronger in strategy, product value and decision-making.
A PM must have:
- Strong domain knowledge
- A clear product vision and strategic thinking capabilities
- Outcome-focused
- Critical analysis of AI output
- “Context container” skills
- Critical thinking and good judgement
- Business acumen
She stresses that Product Managers must feed AI with the right context.
“You need to know which background information is required to get good output. Without context, AI delivers poor results.”
Why measuring behaviour matters for product teams
What are poor metrics for Product Managers?
In her keynote “What gets measured gets gamed”, Büşra outlines three mechanisms that cause product teams to make wrong decisions based on metrics. These mechanisms existed before AI, but AI amplifies them because it makes shortcuts even easier.
1. Goodhart’s Law
Goodhart’s Law states:
“When a metric becomes a target, it ceases to be a good metric.”
Teams start optimising the number rather than the customer experience. It looks like the product is improving, but in reality, only the dashboard gets prettier.
2. Campbell’s Law
Campbell’s Law says: the more important a metric becomes for decisions, the more likely it is to be manipulated intentionally or not.
Teams adjust definitions, count steps differently, or filter out data to make results look better.
3. Path of least resistance
People naturally choose the easiest path to reach a goal even if it doesn’t create customer value. Büşra’s example: a team needed to reduce cancellations and simply stopped counting upgrades and swaps as cancellations.
According to Büşra, true impact is not about vanity metrics, but about behaviour change.
“We must prove that customers act differently because of our product. Only then do we create business impact.”
Her approach: behaviour-change first. Metrics second.
Teams must:
- Determine which customer behaviour needs to change (e.g., complete the first meaningful action faster)
- Define the right signals (e.g., time to first action, onboarding drop-off)
- Measure that change through clear, sharp metrics (e.g., time-to-value, completion rate)
- Make sure that the solution for those metrics is accepted and liked by customers
- Show how the behavioural shift leads to business impact
She identifies this as the core of product work: behaviour changes are the backbone of product growth.
Google’s GSM framework (Goals, Signals, Metrics) provides a clear structure for this.
What does she want Product Managers to do differently starting tomorrow?
Büşra is clear: “Stop making vague statements about ‘making the customer happy’. Define what ‘happy’ means, measure that behaviour, and show how it contributes to your business objective.”
Teams should work in an outcome-driven way and clearly connect:
- Customer behaviour
- Product outcomes
- Business value
The future of Product Managers
AI offers product teams new possibilities: faster work, lower costs, fewer bottlenecks. But at the same time, it raises the bar for Product Managers, who need deeper expertise, sharper critical thinking, and a stronger understanding of product value.
And when it comes to metrics, “The Metrics Lady” is clear:
“First understand and influence behaviour. Only then measure.”
Those who master this build products customers value and that generate real business impact.
What does Büşra take away from Product Day 2025?
Learning remains a core competency.
“The world changes every day. Tools change. Technology changes. Product Managers must keep learning too.”
She identifies three types of learning:
- Theoretical learning (reading, podcasts, articles)
- Practical learning (experimenting, failing, discovering)
- Learning through exchange (conferences, conversations, cases)
Conferences like Product Day are ideal for that third type.
“You learn through conversations with others, by asking questions, and by hearing how others solve problems.”
But she adds:
“There is more knowledge than one person could ever absorb. You must choose don’t try to learn everything.”
Who is Büşra Coşkuner?
Büşra Coşkuner has over 15 years of experience in Product Management. She worked at companies such as Doodle, home24 and Telekom Deutschland, and today coaches product teams worldwide.
She is known in the international product community as “The Metrics Lady”, a nickname she earned through her expertise in metrics, impact mapping and outcome-driven product development.
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