Mobile AI: A Novel Solution for Online Platforms to Deliver Personalized Services to their Customers

The introduction of AI in smartphones is one of the most interesting developments in the last few years. Artificial Intelligence technology has been developed to mimic human intelligence and perform tasks that require human decision-making and problem-solving capabilities. Over the years, other innovations such as robotic process automation, machine learning, neural networks, etc., have become a part of AI-based tools, thus increasing their efficiency and scope of operability.

Almost all end-use sectors in the global economy including finance, healthcare, retail, etc., have started adopting AI technology to strengthen their footprint in the long run. At the same time, the use of smartphones has been gradually increasing annually around the world. Also, the rising pace of digitalization has led to the expansion of the e-commerce sector as various companies have started online delivery of goods and services. To adapt to this evolving scenario, these businesses have developed mobile applications with the help of AI-based tools to effectively address the demands of their customer base.

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Mobile AI for enhanced user experiences

As mentioned earlier, modern-day mobile applications are embedded with AI technology to help users browse through various services and features seamlessly. A key application of mobile AI is in automating chatbots. Almost all mobile apps have dedicated grievance redressal and customer complaints sections wherein users can get their queries addressed. To simplify the process, software developers have started integrating ML algorithms to help the chatbot understand the query, fetch relevant data from the server, and dispatch it to the customer. For example, retail e-commerce companies such as Amazon, Flipkart, eBay, Alibaba, etc., use mobile AI to provide customers with information regarding the estimated delivery date, shipment details, transport routes, etc., automatically.

In certain sectors, mobile software applications use robotic process automation to enhance the operational efficiency of the tasks. For instance, many insurance companies have started deploying RPA-based tools to automate some tasks and even eliminate redundant processes, thereby accelerating activities such as underwriting and claims processing. Moreover, the use of mobile AI also assists these insurers to periodically update their services as per the evolving compliance regulations, thus saving time and costs for the company. In July 2024, Universal Sompo, a leading insurance firm, announced the launch of AI-based solutions for claims settlement processes, viz., 'Universal i Gen' and 'Universal I Assess'. Designed especially for vehicle indemnity policies, the tools use neural network imaging technologies to assess the damages. The application allows users to click images through their smartphone which are then analyzed by the software using ML algorithms and natural language processing techniques. Once the real-time assessment and analysis are done, the claims processing activities are automated to reduce the paperwork and expenses.

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Mobile AI to offer predictive analysis and personalized services

Recently, Allied Market Research published a report on the mobile AI market which states that the industry, which accounted for $8.56 billion in 2020, is estimated to gather a revenue of $84.80 billion by 2030, rising at a CAGR of 26.44% during 2021-2030. The increasing preference for AI tools by healthcare companies to offer personalized services to patients is anticipated to help the sector flourish in the coming period.

In June 2024, Wheel, a healthcare technology solutions provider, unveiled its AI-powered solution viz., Horizon for offering different medical care services to its users. From creating patient profiles to analyzing medical history and lab reports, the application aids doctors in effectively diagnosing the symptoms and recommending tailored treatment plans accordingly.

To sum it up, the mobile AI industry is expected to gain a huge revenue share shortly due to the rising adoption of advanced technologies such as machine learning, natural language processing, etc. Furthermore, the increasing penetration of smartphones and the gradual transition of different end-use sectors toward AI-based tools has broadened the scope of the market significantly.

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