Artificial intelligence (AI) is still at the frontier of media when it comes to tech news and digital products. While AI is still young, many claim that it is an overhyped piece of technology and we are striving to find the "next big thing". The problem isn't with the technology itself however, it is with the application.
To prove this, we can look to a recent headline of OpenAI's release of GPT-3. Once again the world has seen the progress AI is making. GPT-3 is an incredible leap in engineering and can generate written content that could fool most.
The application of AI in products is often overlooked and simply misjudged, the fact of the matter is this; most modern products would benefit in some way from machine learning (ML) or artificial intelligence, but we often don't prioritise this due to perceived lack of time, budget or ideas on how to apply this technology.
How to implement AI/ ML into your product
First and foremost, there is one key element to all AI/ML systems. Data.
Data is the true king here and without it, your system won't have anything to learn on. Data gives clarity on what is normal, it gives information to both you and machines on real-life aspects.
Now most products out there will have the data required to make enhancements through AI or ML. First you have to understand what your product is before trying to improve it. For example, Google used machine learning to pick up on what people often say next. They understood that their users wanted to write emails as quickly as possible and without machine learning their tap to type system that auto-completes sentences would not exist.
Apple understood that their users were trying to find photos of people they know and love (their family). So they used artificial intelligence to scan photos for people and use facial recognition to tag photos with the predicted family members.
Both use cases here are perfect examples of understanding what users are trying to do and then applying technology to really enhance the experience of the user. Put more simply, the idea of putting users-first is paramount to applying AI to your product.
Understand your users and what they are trying to achieve
Understand what the largest type of data you have is
Try and think of aspects that could be improved from that data you collect
Speed and Delivery
There have been many times where implementing machine learning was seen as high-cost and therefore put on the shelf of good ideas. When Brego first started, the use of machine learning and artificial intelligence together was key to the success of the product. Without the technology, it was not possible to achieve the level of accuracy that Brego manages.
The founders were initially concerned over the cost and speed of creating such AI systems, however - due to the vast data collected as well as the subject knowledge held - the ML system was up and running in a matter of weeks (start to finish). In comparison, a typical landing page would take about the same time from design to implementation. The point being, don't be put off by how complex AI seems it is much easier than you would expect in order to get a good result to enhance your product.
If you'd like to know more or you're just curious about AI in product management, reach out! We'd love to hear from you and while it's not our primary business, talking about AI excites all of us at Brego! Hopefully you look into the idea of implementing AI into your product and enhancing the experience for your users!