{"id":22686,"date":"2021-03-16T03:52:00","date_gmt":"2021-03-16T03:52:00","guid":{"rendered":"https:\/\/www.experfy.com\/blog\/why-we-need-more-ai-product-owners-not-data-scientists\/"},"modified":"2023-08-29T13:23:23","modified_gmt":"2023-08-29T13:23:23","slug":"why-we-need-more-ai-product-owners-not-data-scientists","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/ai-ml\/why-we-need-more-ai-product-owners-not-data-scientists\/","title":{"rendered":"Why We Need More AI Product Owners, Not Data Scientists"},"content":{"rendered":"\t\t
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About a crucial, yet underutilized role in AI Product development<\/p>\n

If you think Artificial Intelligence (AI) is a short-lived hype, think again. Stanfords 2021 AI Index<\/a> shows that global corporate AI investment amounted to a record-high $67 bn. Last year\u2019s AI investments topped even 2019’s all-time high comfortably by 40%. According to PWCs 22nd Global CEO Survey<\/a>, 77% of Fortune 500 CEO\u2019s plan to start or already employ AI initiatives. Given the steadily increasing investment in AI, Data Science comes under pressure to deliver tangible results.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Source: State of AI in 10 Charts<\/a>.<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The potential rewards of integrating AI into your business are immense. According to the 2020 McKinsey Global AI Survey<\/a>, AI is contributing more than 20% of EBIT for an elite group of AI practitioners. Additionally, these AI High Performers spend more of their budget on AI initiatives than competitors. They also have the capabilities to develop AI solutions in-house, instead of depending on external suppliers.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Photo by Andy Kelly<\/a> on Unsplash<\/a><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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As Data Science matures, so does the pressure for the field to actually live up to the hype. The field needs to deliver tangible business benefits. A vital, yet underutilized role for the success of AI Products is the AI Product Owner (AI PO).<\/p>\n

In this article, I share my perspective on the importance and required skills of AI POs. Instead of staffing AI Product development teams only with Data Scientists, AI POs increase the chances of successfully developing AI Products. The article describes how to build successful AI Product Teams, the role of an AI PO, and study resources to become one.<\/p>\n

First, let\u2019s analyze the roles of a traditional Product Owner and an AI Product Owner.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Product Owner vs. AI Product Owner<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The role of the Product Owner is defined in the Scrum<\/a> framework. Scrum is a popular agile development method<\/a>. The framework requires the roles of a Product Owner, Scrum Master, and Developer.<\/p>\n

Scrum pays meticulous attention to divide the product and people responsibilities between the Scrum Master and Product Owner. The Product Owner is responsible for maximizing the value of the Scrum team<\/a>. She creates a product vision, communicates with stakeholders, and prioritizes the Product Backlog<\/a>. Scrum alliance<\/a> states that a PO needs business, user experience, technical, and communication skills.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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The AI PO role is an extended, specialized version of the general PO role. AI POs inherit the responsibilities of a general PO. They extend them to maximize the impact of AI-based Products.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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So, what skills do AI POs need? First and foremost, AI POs need to know about the potentials and pitfalls of AI-based applications. What is AI good at, where does it struggle? Which business problems could an AI-based solution solve, where is it misplaced?<\/p>\n

Next, AI POs need to pay special attention to monitoring the predictions of AI models. AI is based on statistical assumptions, so the predictions always carry a degree of uncertainty. Depending on the context, a wrong prediction can cause severe consequences. AI POs should be able to design AI applications to include human decision-making when required.<\/p>\n

Products having ML in their core in a production setting is still a nascent discipline, so there are many learnings being made by both PMs and entrepreneurs operating in this space. \u2014 Sahar Mor<\/a><\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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AI Entrepreneur<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Additionally, AI-based Products are dynamic. They measure how customers react to their predictions. AI Products also need to account for ongoing adjustments to data. When designing AI-based Products, AI POs need to keep the virtuous cycle of AI in mind. The true power of intelligent products comes from their ability to continuously improve based on new data.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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The AI Flywheel allows AI-based Products to continuously improve. Image by author<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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On the technical side, the more technical knowledge AI POs have, the better. AI POs neither need to be former developers nor have a Master\u2019s degree in Computer Science. Yet, it is hard to understand what is easy and what is virtually impossible to implement with AI. The feasibility of an AI Product can be hard to evaluate for AI POs without the proper technical background. Please note that opinions differ here and others believe that technical knowledge is neither required for a PO nor AI PO.<\/p>\n

Last but not least, AI POs understand that AI development is different from the software development workflow. AI development tests different hypotheses and iterates quickly. Traditional software development can follow a more modular and structured approach. Understanding that ML development isn\u2019t as linear as traditional software development is crucial to communicating expectations with stakeholders and delivering value on time.<\/p>\n

\u201cSince the development lifecycle of AI projects is based on \u201csearching\u201d rather than \u201cplanning\u201d, companies need professionals who are trained to look at products as optimization problems rather than a programming problems.\u201d<\/em> \u2014 Adnan Boz<\/a><\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Founder AI Product Management Institute<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Focus areas of general PO vs. AI POs. Image by author<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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After understanding the role of the AI PO, let\u2019s analyze how the AI PO works in an AI Product team.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Structuring data product teams<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Delivering AI-based Products depends on forming cross-functional teams. Cross-functional teams are staffed with experts with complementary skills and roles. Too often, I have seen single-minded Data Science Teams struggling to operationalize their models. Requiring Data Scientists to fulfill all roles required to bring an AI-based Product to customers is a recipe for failure.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Exemplary AI Product Development Team. Image by author<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Instead, the AI PO supports Data Scientists by maximizing business value. The graphic above shows a prototypical AI Product development team with cross-functional experts. Don\u2019t get hung up on the roles, they can change from one product to another. Some products might need AI UI\/UX designers, some might not. However, I do believe that all AI Product teams should at least have an AI PO. You can also see that Data Scientist is just one role in the team, among many others.<\/p>\n

Now that you know what an AI PO does, read on to see where you can learn to skills to become one.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Resources for AI POs<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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As you\u2019ve seen, AI POs can play a significant role in productionizing AI Products. Luckily, there are plenty of resources to teach you to become an AI PO:<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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