In the world of mobile app developmental processes, Artificial Intelligence (AI) and Machine Learning (ML) has a key role to play.
It has redefined human-machine interactions and has become deeply ingrained in our everyday lives. In fact, now, every business is looking to leverage its investment with AI or ML integration.
What’s All the Fuss About AI?
So to say, artificial intelligence is the simulation of human intelligence through reasoning, machine learning and self-alteration.
This model is most commonly seen in digital assistants since the launch of Siri. For long, it dominated sales, but soon lost its spot to Alexa and Echo. Amazon and competitors like Apple and Google foresee them as becoming a friend in time to come. Most importantly, they realized the impact that artificial intelligence can make on their profits.
A digital assistant relies on AI technology systems, all working together on the device and inside a network of computer data centers that connect to the assistant over the internet.
AI used in apps helps automate processes that add an intelligent layer to predictable course of actions. Further, it integrates progressive learning algorithm to accomplish implausible accuracy.
No wonder, Gartner predicts that chatbots will take over 85% of customer interactions by the end of 2020. It presents many opportunities for companies to redesign their mobile applications by focusing on artificial intelligence tools.
Hence, if a customer-oriented business hasn’t yet capitalized this trend, they’d probably miss the train.
Use Cases for AI in Mobile App Development
Scenarios, where applications enabled with Artificial Intelligence, can make their mark for improving customer experiences (CX) may include the following:
- Increased personalization:
When Google released Assistant in 2016, this was a turning point for voice-based AI-powered mobile applications. Google Assistant completely replenished the user experiences. You can use this app to make calls, send text messages, groove to your favorite tunes, or get reminders to send birthday cards.
Through personalization, AI-infused apps help the companies to gain more insights related to customer behaviors. Based on this data, they use personalized approach to connect with them. Interestingly, this technology captures behavioral patterns in minutes to make accurate predictions.
- Improved predictions:
The process of predictive analysis uses information from the existing databases to determine the ingrained patterns and make predictions. For example, Gmail’s Smart Reply works with machine learning to analyze emails and recommend relevant short replies that can be sent with just one tap.
This feature can be integrated into other enterprise level apps to communicate with the users. When chatbots interact with users in a tone they prefer, it creates lasting impressions and great customer experiences.
- Machine learning:
Using intelligent technologies that deal with humongous data and extract the most actionable bits from it will add better dimensions to your mobile app. That’s machine learning for you. It’s a reliable, efficient and cost-effective computing process that facilitates data-driven decision-making.
For example, ADA, a health-related application, assesses your health conditions based on the personal information provided. It is powered by an AI engine and a huge medical knowledge database. With help of machine learning, it understands the user profiles for fetching personalized solutions. Statistical analysis and predictive analysis are used to recognize the patterns in a user’s data to display the desired results.
- Better content quality:
Artificial intelligence collects data from various sources and helps in creating appropriate content. In the age of search engines getting smarter, it pays if you invest in better content quality over time. After all, it’s about the game of rankings.
To get better spots, your application’s content must focus on the right style, tone and USP for any promotional material created for the app.
- Enhanced voice-based search:
Tech giants like Amazon have already upped this game with launch of Alexa that makes tasks easier for you, the user. In fact, some estimates by ComScore pegged voice-based search as capable of ruling the roost with more than 200 billion searches a month leading to market opportunities worth $50+ billion by 2020.
Seamless interactions are the touchstone for voice interface in mobile apps. But, users are also looking for predictive apps that are context-driven as well.
So, in conclusion, you can say that artificial intelligence in mobile apps is reinventing ways in which users communicate and engage with your business. Cortana, Alexa and Siri have changed the war apps communicate with users.
Now, it’s your turn to make a difference and jump on the bandwagon.