Designing Effective AI For Smart Apps
Are you looking for a practical approach to using AI?
Let’s first off take a real world view of AI. One big AI in the sky to solve all problems or revolutionize the world is just that, pie in the sky. Much better is to consider how to use the readily available AI services that are out there. These provide a practical way for us to make our apps smarter, easier to use by their users, more profitable for publishers and more competitive in the app store shelves.
AI has application in many areas of apps:
- On the front end, AI powered chatbots are perhaps the most visible sign of AI adoption. There are thousands out there but few examples that really work well. Keys to success are managing expectations of consumers as to their range of ability (or skills). They should be integrated tightly into the UX and business processes that you want the AI to support. With good design, many readily available AI powered bot platforms from the Google or Amazon can bring Siri like capabilities to your very own app!
- Sitting in the middleware, UX’s can be made more engaging with AI’s which understand consumers more, anticipate their needs and use big data to make the most relevant product recommendations and suggested actions.
- On the back end, AI powered business models, will personalize pricing and premiums for greatest ARPU and long term customer satisfaction.
I love to use this model, cribbed and adapted from McKinsey to help us determine areas of the CX where we can add value and more readily drive people around any app’s consumer life cycle. We aim to be smarter designers using smart, data driven insights that AI offers.
If this sounds like a worthwhile approach to stimulate thinking on how best to adopt AI for your digital business idea, drop me an email at firstname.lastname@example.org.