Scrum pays meticulous attention to the distribution of product and personnel responsibilities between the Scrum Master and the Product Owner. The Product Owner is responsible for maximize the value of the Scrum team. It creates a product vision, communicates with stakeholders and prioritizes Product backlog. Scrum Alliance States that a PO needs business, user experience, technical and communication skills.
The AI PO role is an extended and specialized version of the general PO role. IA POs inherit the responsibilities of a general PO. They extend them to maximize the impact of AI-powered products.
AI-based products differ from traditional software products. First, AI uses data to learn patterns implicitly, instead of developers implementing rules explicitly. Second, AI-based products have the ability to continually improve with incoming data. Third, machine learning allows us to create products that were not possible before in this quality, like voice assistants, automated driving, or medical diagnosis. Therefore, POs need to adjust their skills to deliver AI-based products.
So what skills do PO AIs need? First, AI POs need to be aware of the potentials and pitfalls of AI-based applications. What is AI good at, where does it struggle? What business problems could an AI-powered solution solve, where is it misplaced?
Next, AI POs should pay special attention to monitoring AI model predictions. AI is based on statistical assumptions, so there is always some degree of uncertainty in predictions. Depending on the context, a bad prediction can lead to serious consequences. AI POs should be able to design AI applications to include human decision making when necessary.
Products with ML at their core in a production context are still an emerging discipline, so a lot of learning is done by PMs and entrepreneurs operating in this space – Sahar Mor, AI Entrepreneur
In addition, AI-based products are dynamic. They measure how customers react to their predictions. AI products must also take into account continuous adjustments to data. When designing AI-powered products, AI POs should keep the virtuous cycle of AI in mind. The real power of smart products comes from their ability to continually improve based on new data.
On a technical level, the more technical AI POs have, the better. AI POs do not need to be former developers or have a master’s degree in IT. Still, it’s hard to understand what is easy and what is practically impossible to implement with AI. The feasibility of an AI product can be difficult to assess for AI POs without the proper technical knowledge. Please note that opinions differ here and others believe that technical knowledge is neither necessary for a PO nor an AI PO.
Finally, AI POs understand that AI development is different from software development workflow. The development of AI is testing different hypotheses and repeating itself quickly. Traditional software development can take a more modular and structured approach. Understanding that ML development is not as linear as traditional software development is essential for communicating expectations with stakeholders and delivering value on time.
“Since the development lifecycle of AI projects is based on ‘research’ rather than ‘planning’, companies need professionals trained to view products as optimization problems rather than as optimization problems. programming problems. ” – Adnan Boz,, Founder of the Institute for AI Product Management
After understanding the role of PO AI, let’s analyze how PO AI works in an AI product team.