Artificial Intelligence is redefining every aspect of our work and life. From virtual assistants to medical AIs that diagnose patients for diseases, the applications of AI are potentially limitless and continuously evolving. According to a 2017 Gartner report, AI technology will be among the top 5 investment priorities for more than 30% of the CIOs. Enterprise mobility has been caught in the sweeping AI revolution and undergoing seismic changes over the past few years. Here are some ways in which AI is transforming the enterprise mobility industry.
Prioritization and Efficiency
The present generation of AIs is learning the usage patterns and behavior of smartphone users. They know their habits and preferences. Therefore, they also know which apps, processes, and resources must be prioritized over others. They can manage the hardware resources like RAM, CPU, ROM, and even app resources to maximize the performance of the processes that are “critical” to the user. The user gets a more intuitive and personalized experience on their smartphones, which improves the productivity of the enterprise users.
Predictive analytics allows AI to anticipate the needs of the users in real-time. Organizations can and do use predictive analytics to improve the user experience of their customers on their apps. With each interaction that the user makes, the AI can anticipate the user’s needs and present them with options and information that make sense to them. The best thing about AI is that it gets increasingly accurate with time, as it crunches more data.
In the backend, predictive analytics allows businesses to predict the future needs of their customers with a higher accuracy and respond to their needs with a more robust business strategy.
AIs are not only smart enough to understand the habits and behaviors on a user level but also an enterprise level. They can use their in-depth knowledge of the organization’s dynamic baseline performance, behavior, and topology, to discover business incidents and security incidents. Based on self-learning, they can automatically identify the anomalies that matter for the specific organization where they are deployed.
Chatbots are increasingly being deployed by organizations to elevate their audience engagement strategies. Voice and messaging chatbots allow businesses to engage their audiences in rich conversations and offer useful information without making them wait or deploying a large team of customer service agents. The chatbots can provide responses in natural language and thereby deliver a superior customer service experience.
The modern AIs are powerful enough to understand not only the meaning of the text content but also the sentiment behind the text. App developers and enterprises use this capability to analyze the customer reviews and understand their sentiments, features they desire, and so on, without reading each review. Complex analyses are performed by the AI to give the enterprises insight into the opinions, satisfaction levels, and responses of their customers.
Although impressive, these use cases are just barely scratching the surface of what AI can do for enterprise mobility, and if Gartner’s report is to be believed, then there are more profound applications of AI in the pipeline.