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AI (Artificial Intelligence) Powered Product People

Artificial Intelligence women

AI (Artificial Intelligence) Powered Product People 

Have you ever wondered how artificial intelligence can transform not only our lives but also our professions? As someone passionate about technology and digital product development, I have always been intrigued by new tools and how they can improve our lives and careers. 

In recent times, artificial intelligence (AI) has captured my attention. Despite fears that it could replace us or destroy jobs, I prefer to see it as an opportunity to grow and develop further as a person and professional. Understanding how these tools work, and their advantages and disadvantages, is crucial for me and should be for any professional in their industry. 

I truly believe that people who work in technology and especially in digital product development issues should at least know how they work, what they are for, and what the advantages and disadvantages of the main libraries, languages, and tools are to be better professionals… There is a huge world out there to explore, with many opportunities to learn, and take the first step. 

In this post, I want to share with you some ideas on how you can use Artificial Intelligence to be more productive, creative, and efficient in your daily life as well as in the product management lifecycle:

0. Define

The main thing in this phase is that you define clear business objectives for this cycle in which you will surely have hundreds of meetings with your main stakeholders.

To have better active listening and have all my attention on the interlocutor, video analysis AI tools to take notes and extract the main bullet points of each conversation.

1. Discover

In this phase what you want is to find the pain points of your users and those jobs that the market you are targeting wants to solve.

During discovery it becomes crucial to ask the right questions to the right people and to do this normally my approach has been to initially ask them alone and then refine them using some generative AI tool using key topics in the prompt such as from what point of view am I interviewing, as well as letting the AI know what the role of my interviewee is and the main topics I want to address with those questions. 

In this phase you can also use AI tools to analyze end-user surveys and support tickets, for example, to synthesize their responses and identify patterns from different sources of information in massive quantities, saving you time and enriching your evidence where you should focus to make better decisions faster.

2. Validate

In this step what you are looking for is to verify that the problems you thought about are a pain for your users and to know if you are right or not to move with viable solutions.

But… what is the best solution for your problem? The best solution is one that can maximize your customers’ satisfaction and guarantee a greater return on your investment. 

Many times we tend to skip this phase because it is so time-consuming and we stop doing validation interviews with our clients, but one way to save more time is also by uploading the recordings of these interviews to AI tools, these tools will be able to provide you with the main points of your interviews, knowing the tone with which the user expresses themselves, additionally combining these insights with the evidence collected during the discovery, the AI could give you recommendations based on all this information. 

But that is not all, with some design tools with AI or non-code you can create quick prototypes from prompts to validate a flow or wireframe for example, and thus have much more anticipated feedback without having to wait for something to be developed by you. complete.

3. Build

Now you must materialize those validated ideas that you bring, to do this you have to work together with your development and design team as planned, this is when you share or adjust the business roadmap.

With AI, you can support yourself to incorporate product tests early into the product roadmap, AI can analyze your code in general and tell you how the feature change will impact your entire product in general.

AI can analyze vast amounts of data for patterns indicative of cyber threats, automate threat detection, and enhance security protocols. By integrating AI-driven security assessments and response strategies into the development process, companies can proactively address vulnerabilities, ensuring products are not only functional and user-friendly but also secure against evolving cyber threats. This emphasis on cybersecurity is vital for protecting both the product and its users from potential risks. But one of the features that I think many of us product people feel happiest with is the generation of documentation, with the help of AI we can create more precise user stories, and product requirements documents (PRD) that highlight the capabilities that are going to be included in each deployment for the development and design teams and finally clear acceptance criteria that guide our QA teams in a better way.

4. Launch

It is time to let the world know what you have done and to have a plan so that your clients adopt what you are offering them and continue using it for longer, working closely with your marketing team, customer success, and sales.

In this case, you can use AI tools to launch your product in a controlled and more intelligent way as you have more feedback from your users and greater use, you can deploy your new functionalities little by little, do A, and B testing when you see it necessary and even pivot if you want. 

AI tools will also be able to personalize your product according to the usability of your users and in this way provide different values according to the needs of each user or even guide them and find the precise moment for your user to move from being a free user or a paid user.

5. Evaluate 

What we need most here is to use both quantitative and qualitative data to measure the success of your launch

AI will help you understand insights into your users’ behavior, identify their frictions, and recognize how your users are using the application. Additionally, with this information together with the customer feedback or the Net Promoter Score (NPS) provided you will be able to understand if you managed to solve the problems identified during the discovery phase and provide you with recommendations on the next steps.

6. Iterate

Determine how you can continue improving your product based on the data you have collected to start the next cycle again.

In this phase, it is your opportunity not only to start the entire cycle again but to compile everything you have learned and continue evolving your skills in the company of Artificial Intelligence. 


In the fast-moving world of AI, focusing on data privacy, ethics, and security is key. As AI changes how we work and create, it reminds us of the need to use it correctly, keep your data safe, and make sure our systems are secure. This approach helps us use AI in a way that is innovative, responsible, and trusted, making sure we move forward with care and respect for everyone’s rights. 

As we explore these diverse applications of AI across product development phases, it’s vital to adopt a robust governance framework to ensure ethical, responsible, and effective AI use. 

Perficient’s PACE framework provides a holistic approach to responsibly operationalizing AI across an organization. PACE empowers organizations to unlock the benefits of AI while proactively addressing risks. Adopting such a governance framework can help mitigate risks, foster trust, and ensure that AI contributes positively to organizational goals and societal welfare, If you want to learn more about our PACE framework you can do it here.

As you can see, artificial intelligence will not replace us…yet…but at this very moment, it will give us greater abilities to analyze information, be more creative, better organize our ideas, and take more informed actions. Remember that in the role of product, we do not add value only by creating and developing new functionalities but for the business results we achieve. 

My final invitation to you is to explore the use of AI in at least one phase of the product management lifecycle. Share it with me if you have already done it or know of a new tool. Together, we can continue learning and making the most of these incredible products. 

Based on Pendo.IO AI for product management course.

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Felipe Garzon C

Felipe Garzon Correa is Talent Development Manager at Perficient with over ten years of experience leading people to grow. Felipe is an AI and product management nerd and behavioral scientist.

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