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Get Awesome AI Implementation On Your Apps With These Six Top Tips


Meeting the evolving demands of consumers in the world of mobile apps can be tough. For this reason, an emerging trend among many brands is to make artificial intelligence part of the consumer offering. Given the multiple advantages AI can bring, it’s easy to see why this is a wise move. From providing a more contextual experience to predicting the needs of users, AI has the potential to make mobile apps more personalized than ever before.

And yet given how new AI is as a tool, implementing it correctly can be a challenge. It requires a different approach to design, as well as the need to work alongside existing AI-powered personal assistants such as Siri, Cortana, OK Google, and Alexa, which are constantly reinventing how users discover and use the features of their devices. 

Failing to design and implement AI correctly can be an expensive mistake to make that will bring little or no value to you or your customers. Worse still, it could have an adverse effect on your brand’s reputation.

With that in mind, here are some top do’s and don’ts that I have learned from my own experience in this tricky to navigate field of mobile app development.

Tip #1: DO get your objectives and concept right

At the end of the day, Artificial Intelligence is simply a tool. And as with any tool, having it implemented alone isn’t enough to create sales and success. If you want to make it a viable and profitable business tool the first thing you should do is to draw up clear objectives and a detailed concept. What are you trying to achieve? What benefits does it bring to your consumers? What business processes will it enable? Is there another tool that is more suitable for your objectives? Having the answers to these sorts of questions clear in your mind is a crucial prerequisite for evaluating whether AI is what you need to take your mobile app to the next level.

Tip #2: DO proof of concept with A/B testing

Artificial Intelligence has many variables, and often the line between success and failure can be very thin indeed. That’s why I recommend doing a solid proof of concept using A/B testing that is within the scope of the project concept. It will ensure success, reduce the need for post-launch changes and allow you to calculate more accurately when it comes to the business case.

Tip #3: DO use a cognitive-chain approach

Obtaining data is at the core of artificial intelligence. But making good use of that data is a journey that you will need to go on. The good news is, if we break it down there are really just three simple functions that make up this journey:

Identification functions - These use data to recognize context, conditions, emotions etc.
Consolidation functions - This will turn information coming form the identification function into what you actually need for your app.
Cognitive function - This is the deciding factor in terms of what is delivered when. It does this by dynamically connecting experiences and function to the data coming from the consolidation factions. 

While there are several solutions available for identification functions, the most critical parts are 2 and 3. To carry these out correctly you need a team which is not made up strictly of IT and AI experts but which also includes the likes of psychologists and fashionistas.

Tip #4: DO remember that machine learning is key

By it’s definition, an app that uses AI is “live”. This means it is not fixed, but instead learns from mistakes and adapts to the needs of users accordingly. For this reason, when designing an AI powered app it is critical to assign the appropriate time and resources for creating these learning paths. That way your app can truly evolve. Important questions include: what are the key experiences that need to be adapted? What information needs to be collected and weighted to determine effectiveness? How will you check that the learning process has been successful? These considerations are commonly overlooked, which can have damaging consequences for the success of your AI powered app.

Tip #5: DO start small and plan big

A the core of a good concept and business case is the roadmap. You need to take a minimum viable product approach, which means that you start small (but fast), and set challenging objectives along your roadmap. The exciting thing about AI is that it’s potential is far greater than we can even fully understand right now. So as real data on your app begins to emerge, you’ll be able to make alterations ad improvements to your user’s journey much faster than you might think.

Tip #6. DON’T forget that Apps are not what they used to be

When implementing AI for your app, consider that apps are lightyears away from where they were even a couple of years ago. Users expect to be able to interact with your app even when they are not using it. For instance, it will need to skillfully interact with device personal assistants (like Siri and Cortana), or provide actionable notifications (on smartwatches) or offer dynamic interfaces (like the Siri powered watch faces).

As you can see, the interaction context is all about the os rather than the app, and this means a meticulous approach to design. The business benefits of this new trend can be big, since your consumers have more opportunities to interact with your brand. But don’t forget that every other app out there is vying for your user’s attention too, so be sure to play them at their own game by understanding what you are up against.

If you want to implement AI into your apps but have questions or concerns about your business case, implementation or design, I’d love to share the wisdom of my experience. Simply reach out to the Emozionella team and we will do everything we can to answer your questions.

Connected links to the topic:
Emozionella Concept
Emozionella AI


Fabio Valeri

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