How to start using AI in product development today without breaking your existing process

When you go out there to build a product, you want people to use it. As per userpilot, only 17% of users actually use the SaaS products they’re given. Fewer people using your product means they'll miss out on seeing the value of your product and are unlikely to renew their subscription. 

So, building a great product and finding the market fit is essential in any product development lifecycle. Still, understanding potential users, getting deeper insights from customer data, and building prototypes — all take more time than the market is willing to offer you.

Products often go out without much brainstorming or just go out too late. As per a report by Undo, debugging software failures costs roughly $61 billion annually, indicating inadequate testing. However, I sense that the process is going to become more data-driven and easier with the continuous advancements in AI. 

And here’s how.

AI is not the solution itself

Yes, AI cannot do everything for you.

Gif source: Giphy.com

AI tools are there to help you build better features and products faster, but they won’t do an end-to-end job for you. As a product team, you should evaluate your product development process for AI readiness. It means assessing the existing infrastructure, availability of quality data, and the technical capabilities of your team.  

Involving AI doesn't make the process much different from a standard one. Following your standard product development practices and understanding user requirements is still paramount. It can reveal opportunities for intelligent automation or personalized experiences.