A few years ago the buzz word in the Software Industry was #Agile, then came #Devops and now certainly the word that is ruling the roost is #AI. In these changing times where the lines are getting blurred and roles are evolving at a rapid pace; how can Product Ownership remain untouched by AI.
How does AI impact Product Ownership?
To answer this question we might have to ask ourselves a couple of more questions. But before that let’s re-explore the concept of Product Ownership.
The core of a Product Owner's role has always been about making sharp, value-driven decisions under conditions of uncertainty. Our job has always been to envision the product, understand the needs of our stakeholders and customers, help developers understand those requirements so that they can create increments of the desired product, get the product in the hands of its users to generate the desired business impact, and so on.
Can AI be our partner in doing all of the aforementioned activities or can it help us do all of these activities in a more efficient way? The answer is tending towards a YES.
Having said that, let's get back to the questions that we need to ask to understand the impact of AI on Product Ownership.
Q1: Am I a Product Owner who is building an AI Product or Am I just using existing AI tools to support my existing work?
To me this is the most important question one has to answer before embarking on the AI Product Ownership journey. Understanding the Product Owner role at this AI crossroads defines your focus, your skill set, and your product's very nature.
The AI-Augmented Product Owner
This is the role most Product Owners would be stepping into right now. You aren't necessarily building an AI-native product. Your product could be an e-commerce platform, a mobile banking app, or an internal HR tool. Here, you leverage generative AI tools like Gemini or ChatGPT as a personal superpower to enhance your core competencies. Such tools improve your effectiveness manifold for ex:
- Market Research: You take up all your competitors information, feed it into an AI model and then ask to generate a summary of top 5 underserved needs of the customers and potential market threats.
- Requirements Clarity: No more need to think of a detailed specification of your requirements. Provide a high-level concept and ask your AI-bot to generate the desired level of specification. Tell it the desired syntax and voila you may also have the requirement expressed as a User Story and Acceptance Criteria jotted down in Gherkin.
- Data-Driven Decision Making: You can quickly get a summary of all the surveys/questionnaires that you ran with your stakeholders/users last quarter and decide which features should make it to your next Sprints.
The AI Product Owner
This is a completely different ball game. As an AI Product Owner, the AI is the product. You're not just using AI as a tool; you are responsible for a product whose core feature is typically a Large Language Model or Natural Language Processing or a generative algorithm.
Here you need a completely different approach. You have to embrace the uncertainty of the domain and make decisions around how you can apply the concepts, neural networks, data science and probabilistic outcomes in a way so that your AI models do not spit out biased results and uphold the ethics of AI.
Q2: Why is AI the only or best way to solve this problem, and what is our non-AI baseline?
Once you have established which kind of Product Owner you are, the next step is to answer - WHY AI is the only or best way to move forward?
We have seen this happening in the industry time and again with all the trends that come and go. We applied Agile, we applied Scrum even at places which were not meant for them. And results have been, let's say, less than beneficial.
I see the same trend emerging again with AI. Everyone, everywhere is thinking - how do I apply AI to the work that I am doing? Social media influencers bombard us with ads - “Learn ChatGPT and earn 42 Lakhs INR/annum” or “Learn these 20 tools and become the smartest person in the room”.
Product Owners are not paid to jump on the bandwagon. They are paid to think critically, creatively and thoroughly - how to create customer outcomes and business impact. For that you need to pause and ponder - do you really, really, really need AI for the stuff that you are doing?
Q3: What If…
The last question I ponder upon, not just as a Product Owner but in many cases, is “What If…”.
And this is a very powerful question that allows you to explore the possibilities and opportunities as well as the pitfalls and threats.
Let’s take, for example, that you are the AI Product Owner where you are building a new AI product.
What if this new AI Product turns out to be ‘Ultron’ instead of ‘Vision’?
'What If' often is a crucial question. Models will fail. Your product may make embarrassing mistakes or show biases hidden in the data.
Answering this question will help you come up with the alternatives that truly shape your role as a product owner - the decision maker, the influencer.
Conclusion:
As a Product Owner the most important thing on the AI crossroads is to clearly determine - what are you trying to achieve? Are you simply improving your skills by applying AI tools to your advantage or you are creating a whole new AI product? Having this clarity will enable you to choose your path forward in this new world that is slowly becoming AI-First.
P.S: I hope this helps. If it made sense to you, do share it with someone who might benefit from it. Also, share your thoughts in the comments so we can have some interesting conversations.
P.P.S In case your interested in exploring further role of Product Owner, then I invite you to our course page: https://agilemania.com/professional-scrum-product-owner-pspo-training