It seems that almost all corporations and businesses are on the bandwagon for developing AI-powered products and services. Because the enthusiasm for building such applications is fairly recent, the future of AI-powered apps remains uncertain to many.
However, there are some emerging trends that can be spotted as new AI-powered applications are developed. Let us dive into what these trends are all about and how you can implement them within your own applications to make them more favorable for customers.
Top Trends for AI-Powered Applications
- Personalized suggestions
Training an AI model to deliver personalized suggestions to customers is a quick and easy way to make your customers feel valued and persuade them to make a purchasing decision. The most common method of implementing such a solution is to have dedicated chat windows on your application for the purpose.
Allowing AI applications to interact with customers in this way makes the shopping experience better for the user and the vendor. Deciphering user intent and providing relevant results is what AI applications do best as they leverage their capabilities the most.
- AI-powered chatbots
Ever since powerful language models were made available to the public, chatbots on websites and applications have become quintessential. The utility of these chatbots cannot be underestimated, as they help businesses in more than one way.
From providing instant support to customers regarding any problems to providing product information to increase the chances of driving sales. It also drives down the costs spent on customer acquisition and customer support by taking care of the majority of issues faced in these fields using its ability to understand and respond to human queries.
- AI-powered analytics
Analyzing data using AI-powered applications is a choice that makes a lot of sense, given how AI applications are able to go through thousands of pages of information within minutes. Not only can it go through information fast, but it can also fully comprehend what the data is all about at similar speeds.
Once the AI is done scanning through all the information, it can then make its meaning concise and easy to understand for the end-user. As you can imagine, this significantly speeds up the whole process of data analytics and automates most of the procedures involved.
- Cybersecurity
Coming up with new ways to make your applications is a tiresome and stressful process that takes a lot of time to bring to fruition. Using AI, you can speed up the process of finding any weak points in your application and devise solutions to counteract them.
This way you can not only keep your application safe from malicious attacks by recognizing them beforehand. You can also keep user data secure and increase the level of trust that customers have in your products and services.
- Healthcare
The use of AI in the healthcare industry has been very prolific in recent years, and its impact on humanity is by far the greatest of any other AI-powered application. Everything from treating patients remotely to diagnosing illnesses before they become acute can be done using AI-powered applications.
While the utilization of AI technologies in the healthcare industry is still in its infancy, it is not long before more technologies, such as computer vision, get integrated into the field for rapid diagnosis and treatment for all individuals across the globe.
Essential technologies for AI-powered applications
1. Computer vision
Computer vision is the field of technology that involves making computers recognize and interpret visual data. Depending on the requirements, computer vision can be adapted to understand visual input in real-time or through image uploads on a local system.
The applications for computer vision systems are limitless as they can be used for a lot of sectors as they bridge the gap between the physical and virtual worlds. Perhaps the most widespread use of computer vision has been in e-commerce for enhancing the shopping experience.
Through computer vision, customers can take advantage of augmented reality programs that allow them to experience a virtual product in a physical environment without having to travel to an experience center.
2. Reinforcement learning
Reinforcement learning is the process of having an AI model act in an ideal manner by reinforcing the correct responses with rewards. Similarly, to dissuade the model from giving out inappropriate responses, penalties are employed to reinforce the expected behavior.
As you can imagine, this technology is very important for public-facing AI models that need to be as safe as possible to not ruin the brand image of the product owner. Some users also tend to use reinforcement learning to make the AI application behave in a way that resonates the most with their brand identity, leading to a personalized experience for users of the application.
3. Natural language processing
Natural language processing is how AI models decipher user intent from text and provide coherent responses in return. This technology is what makes chatbots function as they do and is thus vital to the world of AI-powered applications.
By converting text into tokens, the AI model is able to interpret what the user is trying to convey and then deliver the right message. Because the comprehension of AI models is so refined by NLP, it can also be used for highly accurate translation and detailed questions and answers, which raises the usability of the model quite drastically.
Conclusion
In the ever-evolving world of AI-powered applications, it is quite easy to be overwhelmed by the number of advancements being made. But at the core of all the advancements in AI applications lie a few essential technologies paid with a lot of refinement to get the ideal solution to problems.
So far, the trends in AI technology just show how existing processes and applications have their abilities amped up through machine learning. For example, technologies like menu-based chatbots have evolved into AI-powered chatbots that are much more capable of handling customer issues effectively.
Luckily, because AI technologies are still relatively new as far as applications are concerned, it opens up a large window of opportunities for smaller businesses to capitalize on with their own AI-powered applications.
Author Bio – Hardik Shah is a Tech Consultant at Simform, a leading mobile app development company in Los Angeles. He leads large scale mobility programs that cover platforms, solutions, governance, standardization, and best practices. Connect with him to discuss the best practices of software methodologies @hsshah.
