Incorporating AI into our products successfully

AI is the new shiny tech toy that is enabling magic to happen in the product space. But the technology itself is not going to make your product successful. The key factors that will drive success are:

• Understanding the AI potential for your product now and in the future (because this space is going to keep changing rapidly),
• using that AI power to solve real problems that drive business & human value (rather than doing AI for the sake of it),
• and work together as cross-functional product teams to bring products enabled by AI to life (let’s get ready to say bye to traditional roles).

There is this amazing thing that happens now and then, where one new possibility comes into the picture and forever changes the way we understand the digital space. I still remember when the iPhone came out and then mobile devices completely changed how we understand digital products.

Well, we are now in another of these wonderful moments where, with the rapid evolution of generative AI, the previously expensive and specialised power of AI is now accessible to all. That feels exciting. But… now what?

AI certainly opens so many possibilities for our products right now. But, as with many other innovations back in the day, the challenge will be to incorporate it into your products to drive real value successfully…

SO… The very cool thing is that adding AI magic to our digital products has already become very easy. Right now, there are great low-hanging fruits that we can incorporate into our products. I think about them in 3 different ways:

• Analytical: AI has a wonderful ability to summarise, classify and analyse stuff
• Generative: Generative AI at its best, generating text, images, videos, music…
• Insightful: AI combines both analytical and generative capabilities to suggest valuable things.

There is much more coming. Around the corner, a few AI directions are getting me very excited as they have the potential to change radically not only the products we build but the way we work ourselves to build them.

• AI Agents, where we will create agents with goals and knowledge to interact between themselves and with humans to achieve any given goal
• AI tools, where AI will impact the way we work in our crafts (product, design, engineering, marketing and beyond)
• AI creative solutioning, where we will use AI combined with creative humans to find solutions beyond human reach at the moment.

BUT… All of this only makes sense if it solves a real problem, makes our customers’ lives easier or drives business value. Rather than get the technology and push it into our products, we need to keep asking ourselves what are the relevant problems to solve. And then use AI as another tool in our tech enabler toolkit that, combined with other tech enablers can make (more) magic stuff happen.

AI by itself is rarely the answer. It makes sense when incorporated wisely in our products, usually combined with other non-AI tech enablers to create a great user experience. When considering AI, ask your teams what is your secret source and use AI to bring it to the next level.

AND ALSO… AI changes the game. As product teams, we need to be ready to work with AI in a way that allows us to learn and iterate until we find that real value. That means saying goodbye to some comfortable habits and getting used to the idea of ditching our traditional roles and processes. Some of the principles that I’ve found are essential to working with AI in our product teams are:

• Continuous Learning Building a successful product with AI while encouraging a culture of learning in our team as the field evolves. Because this, my friends, is just the beginning.
• Cross-functional collaboration Collaboration between AI specialists, tech and our product and design folks is key to ensuring an AI product is built right. Don’t forget the business and marketing peeps ;)
• Iterative Experimentation Adopt a Test-and-learn approach iterating AI through Agile sprints with the collaboration of the full cross-functional team, starting small and making sure we learn before implementing the next step.
• User-Centric Design Always start by understanding the user frictions and needs, to ensure that AI-driven features align with user expectations and ethical considerations.
• Explainability, control & accountability Users and stakeholders should understand how AI-driven decisions are made and control how it is working, mitigating risks and biases.

AI is very soon going to be challenging the way we think and build products. The way our cross-functional teams work is going to be the key to incorporating that potential and truly making a difference.

The idea is not new. But incorporating AI in our products will become critical to create safe spaces where is easy to experiment, learn, collaborate from different perspectives and adapt to an environment that will change faster than ever.