They may be ubiquitous nowadays, but mobile phones have been quite a revolution when they showed, and especially when they turned “smart”. Although now it seems like smartphones have been with us forever, this moment was not so long ago – it was only about a decade ago. What’s even more attractive for anyone interested in how new technologies reshape our lives is that smartphones are constantly changing and evolving. Innovative branches of computer science such as artificial intelligence (AI) and data science, and interdisciplinary fields such as robotics, as well as the parallel applicative segments – machine learning, including natural language processing and neural networks, are again raising the threshold of what smartphones are able to do for brands and users.
In essence, AI is technological advancement. But it is partially going forward thanks to a whole set of wider ecosystem circumstances. If it wasn’t for the powerful processors packed in tiny shiny boxes that people can take with them everywhere, it wouldn’t have gone so far.
AI helps businesses turn a new leaf as cross-applicative innovation, which means that it doesn’t stop at smartphones. It is also present on the web and on desktops. But since the smartphones, being the powerful machines they are, serve the always-on, mobile user, they are encouraging mobile app developers to explore its possibilities with AI and machine learning.
Robots or more specifically, bots and chatbots, are another progressive way to help users get better products and services. Bots are used to automate specific repetitive boring tasks, while chatbots do something similar by adopting human conversational capabilities.
We can view each of these technologies on their own. They do their purpose. Yet, the greatest benefits in business applications include solutions that don’t cut a straight line between them. Concrete solutions depend on concrete business needs in a quite disruptive field that hasn’t had its final word yet. But if we are to learn from existing successful applications of AI, machine learning, and chatbots, here is what we should keep in mind and take forward:
AI chatbots. Chatbots have fully reshaped the customer service industry. More and more businesses are using chatbots to handle customer requests because of their obvious advantages. A chatbot doesn’t lose its cool when facing a tough customer. People are so used to using messaging apps that taking to a chatbot reports a 73 percent satisfaction rate. Chatbots can work 24/7 without rest, which makes them available at any time for customers. Mostly because of their availability for simple and more generic customer use cases, it is predicted that chatbots will take over almost 80 % of customer communications in the next few years.
Facial recognition. When training a machine to detect and recognize faces, businesses can introduce a whole load of new machine learning applications with security, identity, and personalized brand experiences. Take a look at this example of 21 successful use cases of face recognition, including identity verification, threat and crime prevention, personalized demographics marketing, and even detecting missing persons or lost pets.
Image and voice/speech recognition. In the historic, over half-a-century timeline, speech recognition has come a long way, now offering almost 95 percent accuracy for major applications, such as Google or Siri. By creating search engine algorithms based on voice/speech recognition, image recognition, and localization, businesses could focus on providing individual value for each customer, as mobile apps that use combined machine learning including all of these are more accurate and attuned to the user demographic qualities. For instance, AI apps are majorly reshaping retail by offering new possibilities for precise shopping recommendations, pricing optimization strategies, and visual product searches.
Predictive analysis. The predictive capacities of AI and machine learning have enabled companies to gather and analyze data from multiple point-of-sale (POS) machines and use the combined knowledge to improve service and conversion rates across the business. As we grow in digitalization, there are more ways to pick up valuable data and let an intelligent machine pick up otherwise unobservable trends. One thing is for sure – machines are usually better than humans at manipulating large data resources and doing automated spiritless work exactly because they are not human. Now that mobile app technologies and smartphones are on a constant improving curve, feeding phones data, giving them machine learning tasks, letting them handle vexing customer complaints, and using their smarts to help us make sense of all that together is creating a new world of user experience. As these trends gain solid structure and proof over time, we will see more of that.