Patient recruitment plays a major role in the timelines and success of a clinical trial. But the traditional recruiting process has been nothing less than a mammoth task. Besides being time-consuming and costly, a lot of effort is needed to find the right candidates and of course, chances of dropouts will also be high.

Artificial Intelligence (AI) for patient recruitment in clinical trials has proven to be a game-changing solution. AI uses pattern recognition and medical record analysis to find eligible participants for clinical trials.

Want to know more about how AI technology advances patient recruitment in clinical trials? This article explores the role of AI in streamlining recruitment, real-time use cases, and challenges in AI implementation for clinical trials.

Challenges of Patient Recruitment in Clinical Trials

Patients who participate in medical research are the most important assets for a clinical trial. If this process gets extended or delayed, it can impact the timeline of the trial, and sometimes even the trial can be terminated prematurely.

During the process of recruitment, finding patients who meet the strict eligibility criteria is one of the primary challenges. The task gets even more complicated with a huge amount of data to analyze. During this labor-intensive process, there is a high risk of human error as well.

Even if suitable candidates are enrolled for the clinical trial, managing them throughout the trial process is another challenge. Due to several factors like lack of engagement, insufficient support, and inconvenient study protocols, patients might drop out in the middle of research work.

Apart from these challenges, the traditional recruitment process also suffers from limited reach and inefficiency. Depending on referrals, local advertising, and outreach programs may not be helpful in gathering a large pool of participants.

These challenges highlight the need for more effective recruitment solutions to ensure the success of clinical trials. 

Role of AI in Streamlining Patient Recruitment

Artificial intelligence has helped to transform and redefine several aspects of healthcare, including patient recruitment for clinical trials. Using NLP, data analysis, and machine learning, AI addresses the challenges often faced with the traditional recruitment process. Let us explore how AI manages to address them efficiently.

Patient Identification and Matching

This is the most significant advantage of using AI in clinical trials. Traditional methods heavily rely on manual processes and broad criteria, often leading to mismatches or missed opportunities. But AI uses machine learning algorithms to easily analyze large datasets to identify eligible candidates.

AI algorithms can identify subtle patterns and correlations that human recruiters can miss. For example, AI can examine electronic health records (EHRs), medical histories, and other relevant data to find out who is eligible for the clinical trial. Since this is an automated process, eligible participants can be identified with less effort and time. This high level of accuracy not only speeds up the recruitment process but also ensures the overall quality of the participant pool.

Furthermore, the ability to analyze data in real-time helps AI monitor and stay up-to-date with patient information. For example, if the initial recruitment process has not resulted in the expected yield of candidates, then AI can either identify alternative options or adjust the criteria to broaden the search without compromising the trial’s integrity.

Avoiding human error is another crucial benefit of using AI in patient recruitment. The manual process of patient identification and matching is prone to mistakes, leading to inefficiency. But with AI’s automated system, there is less chance of errors. So, the recruitment process stays efficient and reliable.

Patient Engagement and Retention

Another crucial factor in ensuring the success of a clinical trial is patient retention. Previously, in traditional methods, the changes in dropouts and patients’ lack of motivation were high. These factors often contribute to trial extension and determine the validity of a study.

AI’s innovative solutions track patient engagement through personalized communication and support strategies. AI platforms can create customized communication plans for every participant to ensure they receive timely information throughout the trail. They use machine learning algorithms.

AI chatbots and virtual assistants are quite helpful in these situations, as these tools provide 24/7 support to patients. They are available 24/7 to answer questions, guide participants, and address concerns throughout the trial. This process builds trust and motivation among the participants to feel valued and connected to the trial.

Using predictive analysis, AI can analyze patterns in patient behavior and identify any potential dropouts beforehand. This early detection allows trail coordinators to provide encouragement and support to ensure the continuity of the study.

Furthermore, AI can also optimize study protocols to improve participant convenience and satisfaction. For example, AI algorithms can suggest adjustments to data collection and visit schedules based on preferences and lifestyles. This flexibility ensures the participants adhere to trail requirements without disrupting their daily lives.

Integrating AI with Electronic Health Records (EHRs)

Electronic health records contain medical histories, treatment records, and demographic information. One of the key benefits of integrating AI with EHRs is the ability to conduct real-time analysis. AI algorithms can monitor EHRs for any updates in patient information, ensuring that recruitment efforts remain current and respond to changes in patient status.

Furthermore, AI’s integration with EHRs ensures data privacy and compliance with regulations. Advanced AI systems are designed to operate within the confines of data protection laws. These systems use encryption and secure protocols to handle sensitive patient information.

AI Application for Patient Recruitment in Clinical Trials- Real-time Examples

Several research institutions and pharmacy companies have already started using AI for their clinical trials to ensure smooth processes and remarkable results. Below, we have mentioned a couple of successful stories about using AI for patient recruitment.

Case Study 1: IBM Watson Health and Mayo Clinic

IBM Watson and Mayo Clinic have collaborated to streamline patient recruitment for their clinical trials. Using AI and machine learning algorithms, Watson Health was able to analyze EHRs and other patient data to identify eligible candidates quickly. This collaboration has significantly reduced the time required to recruit participants. And since AI was able to process vast amounts of data accurately and quickly, researchers were able to focus more on patient care and trial management than administrative tasks. 

Case Study 2: Pfizer’s BLUE-SKY Initiative

Pfizer started BLUE SKY initiative to explore artificial intelligence and other innovative technologies. By integrating AI tools with their recruitment process, Pfizer was able to improve patient identification and engagement. Through an AI-driven approach, Pfizer was able to communicate with candidates more efficiently, which led to successful studies. This initiative has demonstrated how AI could be integrated into large-scale pharmaceutical operations.

Challenges and Limitations of AI in Patient Recruitment

Although AI greatly improves patient recruitment for clinical studies, it does come with a few challenges. The main issues are data privacy and ethical issues, since AI systems need access to sensitive health data. To keep patients’ trust, compliance with data security laws is essential. There are other technical difficulties as well, like training the AI algorithms, which require huge sets of data and on-going maintenance to keep the systems stable.

Balancing human touch and AI automation is essential in clinical trials. Relying just on AI can lead to impersonal interactions, which would undermine trust. If the data that is fed to AI is unreliable or biased, then it can negatively impact the recruitment process.

Conclusion

Artificial intelligence is making a huge impact on the recruitment process for clinical trials. As AI continues to evolve, its role in clinical trials is expected to grow, paving the way for more effective and timely medical advancements. Using data analysis, pattern recognition, and personalized communication, AI provides accurate and efficient results in patient recruitment. AI-driven tools streamline identification and matching of eligible patients and improve participant retention through tailored support.

Despite these advancements, it is crucial to address the ethical, technical, and practical challenges associated with AI implementation. Furthermore, fostering a better understanding and acceptance of AI technologies will be key to their successful integration into clinical trials.

USM, the best AI development company, will help drug development companies seamlessly find patients for clinical trails, and streamline end-to-end processes.

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AI in Logistics Industry: Key Benefits and Use Cases (AI use cases in transportation)

Just imagine the world without a transport facility! If you want to travel long distances, how would you go?

And, if a leading manufacturing company has to transport goods to its customer locations, then how it will do that without transport and logistics facilities?

I think you understood the significance of the transportation industry. It’s a mandatory need for both individuals as well as businesses.

Do you believe or not the history of the initiatives across the transportation industry has exploded in 1787 when the steamboat has invented. Later in the 19th century with the invention of the bicycle, the industry moved to its next level. After that motor car era had come in the 1890s, trains in the 19th century, and finally aircraft in 1903. Manufacturing of more vehicles that meet all human transportation needs based on market demand.

This was the major reason behind the advancements in this sector using innovative technologies. Automobile or vehicle manufacturers are focusing on spreading the wings of artificial intelligence across the sector to gain from the increasing demand.

Artificial Intelligence (AI) is one of the best technology supporting the transportation industry in many ways. AI-enabled applications in transportation have transformed the transportation sector tremendously. AI Applications in Transportation are making our lives easier, safer, and more efficient.

Artificial intelligence in public transport, private transport, and personal transport has progressed in such a level that vehicles are moving without any assistance from humans. Thanks to Artificial Intelligence (AI) technology. Artificial intelligence technology in transportation is helping the industry to enhance safety, reduce unexpected accidents, reduce traffic, carbon emission, and also lower complete financial expenses.

On the businesses front, Applications of Artificial Intelligence in Transport increases productivity, automation level, and overall excels sales indicators.

USM, the best mobile app development company, has immense experience in using artificial intelligence technology to develop futuristic travel apps that make trips more effortless. In addition, being one of the best AI app development companies, we also build enterprise-level AI solutions for helping logistics firms track their fleet in real-time.
Would you like to know what we delivered to the transportation sector? Please go through one of our significant AI in transportation case study.

Recommend: How Automotive Industry Is Evolving With Artificial Intelligence?

AI technology in transport will bring huge revolutions, not only to the vehicles but also to the complete ecosystem. Let’s take some examples of AI use cases in transportation.

The Role of AI in Logistics and Supply Chain Management

Top 6 AI use cases in the transportation sector

Artificial intelligence use cases or applications in transportation let you know why the transportation business players are looking to invest in artificial intelligence technology. Here, we briefed out a few top use cases of artificial intelligence in the transportation industry. Let’s have a look at the below AI in transportation examples.

#1 AI for autonomous or self-driving vehicles

Will transportation become autonomous?

Japan has already launched its first version of autonomous vehicles in the country. Accordingly, the United States transportation & logistic industries are also holding the power of AI to spread self-driving trucks for reducing operational costs. Likewise, the global developed and developing markets are adopting AI in their transportation rapidly.
AI is playing a major role in the manufacture of self-driving vehicles. We all know that the biggest automobile manufacturers like Nissan, Toyota, Hyundai, and so many vehicle manufacturers will introduce their model of driverless vehicles.
It is just the beginning, but we can’t imagine the market with the complete expansion of AI in the development of driverless cars.

Be ready to see a drastic change in transportation using artificial intelligence!

#2 AI Applications In Transportation

Artificial Intelligence applications in transportation for managing traffic is one of the popular use case of the technology. AI for traffic management is one of the best AI applications for the traffic management system. Artificial intelligence systems predict and reduce traffic congestion and improve road safety.

The AI-powered traffic management system provides greater flexibility to driverless cars in the future. However, the integration of the IoT-enabled high-resolution cameras would also bring a big revolution in the sector.
Hence, AI, together with cloud and IoT, will completely reduce wait times at traffic signals and reduce the traffic over the roads.

#3 Reduce passenger wait times

AI mobile apps for Android and iOS are allowing users to book taxis online and ensure safe trips. Using computer vision and Data Lake techniques, transport apps are making the best data-driven decisions for reducing the waiting time of passengers who booked their service.

#4 Drone Taxis

It is one of the advantages of AI in the transportation industry. Drone taxis are one of the best innovative AI applications in transportation. Drone systems have already been expanded in delivery systems. The technology developments would also help to design and manufacture intelligent drone taxies soon. No wonder in it.

#5 Remote controlled cargo ships

It is also one of the best answers for How Will AI Impact the Transportation Industry. Along with the benefits of Artificial intelligence in public transport systems, for the past few years, cargo ships will also be controlled remotely using artificial intelligence.

Logistics departments can monitor their cargos and stay in connection all the time to track their safe arrival to destinations. It is one of the best use cases of AI in transportation. Hence, it is expected that AI will drive autonomous cargo ships to fullest in the future.

#6 AI in Trucking

The truck transport business is one of the fields where the implementation of AI is growing rapidly. Artificial intelligence and machine learning technologies are improving freight efficiencies. As the market trends are predicting that AI technology and automation are the future of the transportation industry, self-driving trucks are more crazy innovations among others. Hence, AI in transportation and logistics offers more fruitful business results to the service providers.

Future of AI In Transportation

The growth and advantages of AI in the transportation industry cannot be explainable. The practical use of A.I. in transportation will 100% ensure profitable business for organizations across the transportation sector.

AI has already had its grip on changing industrial processes and the transportation sector is also greatly impacted by AI. As we discussed, the examples of AI implementation in transport will give unbelievable results to service providers than expected. With the craze towards autonomous vehicles, increasing concern towards safety and security, and focus on reducing operational costs, the demand and adoption of AI technology in transportation are growing increasingly.

According to the market reports, it is estimated that the AI transportation market will be valued at $3.5 billion by 2023. In particular, North America (US, Mexico, and Canada) region is anticipated to contribute more to the AI in the transportation market value.

Here are a few more business advantages of AI in transportation.

Advantages Of AI In Transportation

Let’s discuss a few artificial intelligence opportunities that are delivered to the transportation sector.

How has technology changed transportation?

#1 Smart Logistics Functions

Leveraging real-time sensor data and previous data regarding traffic, weather, waiting time, stop maintenance, etc., the transportation system can navigate the routes smartly.

#2 Forecasting Vehicle Maintenance

The future of AI in transportation for forecasting vehicle maintenance would be promising. The AI systems can forecasts vehicle maintenance with the help of data collected from smart sensors. You can use telematics solutions to monitor the vehicles in real-time. AI solutions will send alerts and conditions of the vehicles so that you can save yourself from probable hazards.

#3 Track planner with traffic expectation and real-time updates

While traffic congestions are inescapable, AI can predict the traffic jams and accordingly adjust your path.

#4 Intelligent Staff Management

To advance the productivity and safety of drivers, intelligent driver behavior monitoring apps will be useful. Using data captured by the IoT sensors, you can manage your fleet through data-controlled dashboards for smart trucks, ships, and trains connectivity.

Hence, AI in the transportation industry is quite impressive. The impact of AI-enabled applications in transportation are resourceful. USM, the best #AI development company, is a leader in offering quality AI-based solutions and artificial intelligence services to customers across various industries.

Are searching for a reliable AI solutions provider or artificial intelligence Service Company, then you’re in a perfect place. Get in touch with USM!

AI in Mobile App Development: Explanation, Examples and Benefits

Yes, driven by the increasing usage of smartphones, there exist several mobile apps in the market. Artificial Intelligence In Mobile App Development are playing a vital part in human life. They are gaining more attention from customers with its flexible features. The users are looking at flexible advanced mobile apps that meet their requirements quickly and easily.

The mobile AI applications meet the needs of both individuals and service providers. Without mobile apps, no sector will gain profits. Innovative and intelligent mobile apps help retain customers for the long run in this current digital era.

Particularly, banks and finance companies are highly investing in mobile applications. This sector needs innovative mobile apps to engage their users confidentially. Mobiles apps also taps the needs of users in seconds. By just log-in to the app with banking credentials, the users can continue their search from any corner of the world.

Credit card/debit card details, transactions, and loan information, what else everything is possible using mobile apps. Every data is available on the fingertips. Every client request is processed and solved by banks through apps only. Thus, AI in the banking and finance industry is witnessing tremendous growth.

Accordingly, AI in e-commerce are also attracting customers with high-speed android apps. For instance, the online grocery stores through apps offering easy-to-choose products, notifying customers about special offers, discounts & new launches, and encrypted payment gateways.

Thus, mobile app development companies bringing their experience and skills together to introduce an advanced mobile app that includes the capabilities of next-generation cognitive technologies like artificial intelligence.

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Is AI Offer Opportunities to Mobile App Developers?

The apps with something new features and benefits compared to the existing ones will quickly expand in the market. Integration of mobile Artificial Intelligence (AI) into your apps might help you stand out from the crowd.

According to market estimates, the mobile app industry is gradually shifting to Artificial intelligence. To achieve marketing gains, AI is one of the best investment areas for all businesses now. In particular, driven by the increasing expansion of smartphones, mobile app development companies are investing heavily in designing apps that infused AI capabilities.

As consumers are preferring and installing mobile apps with intelligence features, the mobile app developers and service and solution providers are focusing on developing apps that improve user experience, engage them efficiently, and provide useful data for which they search.

Mobile applications of AI can analyze data and produce valuable insights to identify the behavioral patterns of every app user. AI mobile apps intellectual abilities that deliver significant domino effects without the need for human assistance.

Learn more: How USM’s AI Solutions Benefit Your Business?

AI apps can adopt a new set of data and deliver continuous and valid results. This led AI to revolutionize in the industry and offering intensified market opportunities to the app developers. Thus, most of the mobile app developers investing in AI to engage with their customers confidentially.

Are Artificial Intelligence-Driven Mobile Apps Getting Smarter?

Increased usage of smartphones has led to the expansion of AI in the industry. Smartphone users are spending much of their time on Apps. Thus, the companies are adopting artificial intelligence with the belief that it can ultimately manage their customers efficiently.

AI-infused mobile apps or smart mobile apps are currently gaining momentum in the industry and also from the customer perspective. AI technology is improving the experience of mobile app users since the recent past few years. The AI apps easily navigate and assist the users in completing the activities that they need.

On the other hand, as app technology is advancing, the expectations of users are also increasing. The users are expecting predictive mobile apps that meet every need of them.

According to Gartner, to meet the changing user’s preferences, by 2020, maximum technology giants to introduce the most advanced AI-based mobile apps. Starbucks and Taco Bell have already released their intuitive and interactive mobile apps using AI. These apps can analyze user’s purchase trends and thus improves sales. Hence, Starbucks and Taco Bell achieved customer retention, profits, and huge ROI too.

Now, we can image the competition level in the industry. If your mobile app is not updated with AI, then your customers may choose your competitor’s app. Before they opt for your competitor’s app, you attract them with next-generation, high-speed, intelligently build AI mobile applications.

The Future of Artificial Intelligence in Mobile App Development

Mobile apps are re-shaping the way businesses operate. Statistics reflect that mobile app downloads to reach 258 billion by 2022. No wonder, if this number exceeds!

So, businesses need to move forward with more innovations and developments to fulfill the increased customer demand for intelligent mobile apps. In particular, customers are showing more interest in downloading mobile apps that provide more personalization services to them.

We found five significant mobile app trends that you should know in 2020 to remain competitive in the market. These trends would help to boost their business operations by knowing the opportunities as well as challenges that the businesses and developers face in the future of the mobile app industry.

1. Artificial Intelligence and Machine Learning (ML) enabled mobile apps increase personalization

Nowadays, smartphone users are looking to get more personalized mobile apps that meet their needs faster. So, the old app technologies need to be upgraded to deliver personalized mobile apps. This will be done by using AI and ML technologies in mobile app development.

AI and ML allow mobile applications to understand and analyze the user’s interest and perform necessary actions without being told to do so. This kind of artificial intelligence apps for iPhone and android helps to improve user personalization experience. Hence, the importance of AI in app development is extremely high.

2. Voice-enabled mobile apps will attract more user

Voice-based intelligent mobile apps are more in demand in the market. As technology is developing day-by-day, the development and launch of more advanced mobile apps are also growing in the market.

Though a full conversational virtual mobile assistants are not yet designed, few of the best AI-based mobile apps are grabbing user attention. They can understand the user-written content and spoken language and responding accordingly.

3. Rapid Developments of 5G Technology

The introduction and complete roll-out of 5G technology will not only offer high-speed internet services but will also give opportunities to mobile app developers as it creates a complete data-driven environment.

5G network technology ensures high-speed connectivity as well as the best smartphone experience. It takes very little time to respond to the user search request. Data collection, processing, and sharing every task will be completed 10 times faster than existing networks. Hence, mobile app developers should deliver apps that support the upcoming 5G network.

4. Cloud technology- based mobile apps will be in attention

Cloud technology was a proven record of its significance in the mobile app development industry. To store a vast amount of user data, developers are focusing on integrating cloud technology into mobile apps. It means that data stored in physical devices will be mounted on the cloud and can be retrieved as per the user requirement.

By mounting mobile apps data in the cloud, users can access the app features and use them without bothering about device storage space. Yeah, cloud-based mobile apps along with increasing productivity, they also make the development process faster and simple.

5. M-commerce Will Drive The Mobile App Development Industry

Intelligent mobile apps are allowing users to buy or sell things over the internet through their mobile devices. For instance, google wallet is one of the best apps that allows users to pay using mobile instead of using payment cards such as credit or debit cards. To develop this kind of app, mobile app developers need to integrate a secured payment gateway to the apps that can process every transaction.

USM has similar kind AI-based mobile app solution. Explore Now!

Well, Now, What About Your Mobile App?

Now, it’s time to engage your customers with AI and ML-based mobile apps. USM’s AI experts with forward-thinking abilities deliver next-level mobile apps by embedding AI capabilities with ML and deep learning techniques.

Who knows, the integration of your thoughts and our expertise may introduce one of the intelligent apps that keep you forefront in the competition. You’re only a click away from success! Connect USM to know how our Mobile apps help your business.

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Restaurant apps continue to drive the food industry and experience amplified demand from users.  Convenient food ordering facilities and hassle-free ways to find nearby restaurants are helping users order on the go as well as experience excipient dining options. Yes, restaurant apps are now offering seamless ways to users in browsing menus, choosing food items, find nearby restaurants, book dining tables, and opt for convenient door delivery or flexible takeaway.

Moreover, real-time order tracking, personalized recommendations on their favourite items, exclusive discounts, and other loyalty programs are further increasing the demand for usage of restaurant apps.

On the other hand, restaurants too are reaping the benefits from mobile app investments. Improved customer experiences, extended brand reach and visibility, order efficiency, streamlined operations, more sales, and customer retention are a few of the significant benefits to restaurants offered by restaurant app development (Android/iOS).

The KFC app or KFS online ordering app is one such mobile application developed by multinational restaurant conglomerate KFC. Since its launch to the market, this app has generated over 10 million downloads and offers the fastest way to order delicious KFC food online conveniently. KFC was also been popularized as it allows users to find nearest KFC outlet and order food, ensuring quick door deliveries. 

If you running a restaurant and executing only offline, then the time has arrived to create a mobile app for kickstarting your online presence. In this digital age, without a mobile app, it will be tough to extend brand awareness and generate cashflows.

In this article, we have discussed the must-have features and functionalities of the Indian biggest restaurant apps like KFC. You can also get cost information to create a KFC India online ordering app like a popular restaurant platform.

Here we go!

Features and Functionalities To Consider For KFC App Like Similar Platform

The features of the KFC app have significantly contributed to its business growth and app success in India. This largest food delivery app in India is now the first choice of techies to meet their KFC chicken cravings without reaching KFC outlets.

Top Features for User Panel Development

• User Registration and Login
• Social Media login and sharing facility
• User profile management
• Attractive UI
• Search option with custom filters
• Menu Section
• Orders tracking real-time
• Nearby nearest Outlet finding facility
• Orders history
• Multiple payment options
• Payments history
• Discounts and coupons apply
• Quick & speedy delivery
• Pre-order feature
• Re-order to save users’ time
• Push notifications
• Reviews and Ratings
• Voice-enabled search functionality
• In-app customer support chatbot
• In-app messaging feature 

Must-have features for Delivery Agent Panel Development

Delivery agent panel development needs to integrate features that streamline the process of order deliveries and ensure a superior level of communication between customers and delivery agents. Here are a few top features for making the delivery agent functionalities smooth and collaborative.

• Delivery agent signup and login
• Rider profile management
• Updates on orders in real-time
• Orders Management (Accept or Delete)
• GPS navigators for route optimization
• In-app communication, such as calling or chatting facility
• Delivery status updates
• Payment Status updates
• Agent support services
• Ratings and Feedback

Integration of these friendly features into your KFC-like food delivery application ensures efficient delivery services, thereby benefiting the restaurant in terms of customer loyalty and end-customers in terms of reliable and quick deliveries.

Are you looking to know the cost of building an app like KFC? Here is the information you looking for:

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How Much Does it Cost to Create an App Like KFC?

The average cost of KFC food delivery app development will range from $20,000 to $40,000. However, the cost of KFC-like restaurant mobile app development will depend on many factors. Restaurant app development companies consider factors such as app size, features, design complexity, technology stack, app development platform, and many more to decide the cost of building an app like KFC.

Moreover, testing and QA, maintenance & support, and app promotional and post-launch maintenance all impact the estimated budget of mobile app development like KFC. From research, design, and development to update, maintenance, and promotion, every phase is significant and needs a budget. All factors will impact the estimated cost of building an app like KFC.

Let’s delve deep into the factors that impact the cost of building an app like KFC.

1. Development Platform and Type

The choice of application development platform significantly affects the final app development costs. Your choice between native app development, hybrid app development, or cross-platform development that supports Android, iOS, and/or web OS impacts the code complexity, resource utilization, and investment of time.

If you choose native app development on either Android or iOS involves huge development costs as compared to hybrid and cross-platform application development. This is all because native apps are specific to the operating system and mobile app developers need to write separate codebases for ensuring efficient performance and nativity. It will increase the development costs.

Whereas code written for cross-platform applications using Flutter and React-native-like frameworks is portable and platform-independent. Hence, the mobile app development team can write code once and deploy it on multiple platforms, thereby reducing development costs. So, be smart in selecting a mobile app development platform and type.   

2. Features and Functionalities 

The features and functionalities of either Android app iOS app or Web app play a significant role in deciding their development costs. The complexity of features will increase the development time and expertise required for mobile application development.

Adding advanced features and functionalities, such as real-time location tracking, restaurant finding, in-app AI customer support chatbot, voice-enabled search functionality, etc., need more time and incur higher development costs. Hence, the features and functionalities will contribute to variations in mobile application development costs. A set of complex features and advanced functionalities will increase the app’s size and price, but they improve the app’s uniqueness.

Top mobile app development companies like USM are experts in balancing the app’s requirements and your budget. Get a free quote for KFC-like food delivery app development.       

3. Design Complexity 

The User Interface (UI) and User Experiences (UX) designs play a crucial role in determining apps’ appearance to the end-users and success rate. It directly deals with the user experiences. Market research of users’ preferences, proper planning, requirements analysis, and end-to-end collaboration between the development team and UI designers are mandatory to come up with an intuitive mobile app design. It will increase the front-end development costs of KFC-like software development.

The best mobile application development agency like USM with seasoned UI designers designs appealing UI/UX designs and ensures seamless user experiences, contributing to better user engagement. We balance the time, budget, and resource availability and provide cost-effective mobile app development services to clients across various industries. 

4. Technology Stack 

The technology stack you select will also significantly impact the development cost of KFC a famous online food ordering and delivery application. The set of programming languages, UI frameworks, libraries you import, plugins, and databases you choose for storage, will all directly impact the development costs.

Moreover, to include AI-chatbot-like features, mobile app development companies will use Artificial Intelligence (AI) like cutting-edge technologies. Using such leading-edge technologies to create an app like KFC, needs expert AI developers. It will potentially increase the overall development cost of a KFC-like food app.

Moreover, when the application needs to be compatible with various other platforms, application scalability, and performance issues will also incur hidden costs. But, hiring USM-like a top mobile app development company in the USA will balance technologies and budget constraints. Understanding your application requirements, our top app developers choose the right technology stack to ensure flawless performance and reduce scalability issues. 

5. Mobile app developers’ location 

The region of mobile app developers you hire will determine the cost of building an app like the KFC food delivery app. The hourly rate of mobile app development services will be different from region to region. For instance, if you hire top app developers from North America with higher cost-of-living regions, then the app development expenses will go beyond the estimated price.

In contrast, top mobile app development companies in India and other Asian markets will offer budget-friendly software development services to their clients. So, while hiring Android or iOS app developers, it is essential to balance their hourly rates of development teams with your budget limit to experience cost benefits. 

6. Team Size

The team size of mobile app developers impacts the final costs of KFC clone app development. To create a mobile application (Android or iOS), you should hire a company with a team of resources specialized in development, designing, testing, code debugging, and quality assurance experts. Hiring such an experienced team increases development costs, however, their expertise ensures faster development within fewer sprints.

USM, the best mobile application development company, determines your project complexity, timeframe, and your budget. Our expert software development team leverage their proven best practices in food delivery app development and ensure to deliver cost-effective and high-performance application within deadlines.

7. External API Integrations 

Integration of third-party Application Programming Interfaces (APIs) into your KFC clone app will impact on overall development costs of software. Significant licensing charges required for deployment and usage of external APIs contribute to extra costs. However, integration of APIs, such as secure payments APIs, will improve the application functionalities and enhance user experiences. 

8. Maintenance and Support 

Mobile app developers should emphasize the significance of MVP development with key features for reducing the burden of extra development expenditures. Because ongoing maintenance and support to incorporate changes in features and external APIs will further impact long-term development costs. Regular updates to the software, bug-fixing. performance optimization, user feedback analysis, and support services will all incur extra costs.

Being a popular #software development firm USA and India, USM helps in the design and development of budget-friendly Android and iOS apps. We deploy highly functional, secure, and highly advanced mobile apps using leading-edge technologies.

Wrapping Up!

We hope that this article has given information to companies across the food industry who have plans to create a mobile app. Starting from market research and user-friendly app design to integration of delivery agent features and functionalities, every module influences the development costs.   

Do you have a restaurant app development idea? 

Get in touch with USM to avail cost-effective application development services!

The role of AI and ML in transforming credit risk management in banking

Credit-card fraud has been a prime challenge for customers and financial organizations in this digital age. Globally, more than $28 billion was lost last year from credit card fraud. It is going to rise in the future, and hence there is a need for robust risk management mechanisms.

Previously, risk in credit card portfolios was managed through a variety of manually developed procedures for fraud detection and prevention. However, traditional methods have become ineffective against today’s intelligent hacking methods.

Fortunately, the advent of AI and ML has transformed credit card risk management processes. These technologies process huge volumes of data and can effectively detect anomalies, mitigating threats. This technological shift shall create a better transaction security experience for customers through reduced false positives and smoother and safer transactions.

The article will discuss how AI and ML can solve traditional credit card risk management problems. We are also going to look into the different techniques used, the benefits of using AI and ML for credit card risk management, and some case studies with real-world examples.

An Overview of Credit Card Risk Management

It is the process of identifying, assessing, and mitigating the risks associated with credit card transactions. Therefore, this whole process can be regarded as paramount to protecting consumers and even financial institutions against fraudulent activities.

Traditionally, credit card risk management depended on rule-based systems and manual reviews. In the rule-based system, as the name implies, predefined criteria are used in the identification of risky transactions. For example, transactions exceeding a certain amount or originating from unusual locations raise red flags. While providing some form of security, these measures were typically inadequate to handle increasing volumes and sophistication in credit-card transactions.

This can often result in the generation of a lot of false positives by rule-based systems misinterpreting a legal transaction as fraud. This might anger customers and put additional workload on customer service. Further, fraudsters are continuously inventing new techniques that make it pretty hard for the static rule-based system to detect new threats.

The Role of AI and ML in Credit Card Risk Management

1. Transforming Risk Management

AI and ML have transformed credit card risk management with much more accurate, efficient, and dynamic approaches toward fraud detection and mitigation. These technologies use large datasets and complex algorithms that enable identifying trends and outliers in real time. This approach opens up avenues for proactive threat detection and response.

2. Real-Time Fraud Detection

AI and ML systems are very good at real-time fraud detection, for they continuously monitor transactions and user behavior. While traditional, rule-based approaches could not detect these newer styles of distributed fraud schemes, AI and ML adapt rapidly to new patterns of fraud once they appear. This will ensure that financial institutions are always one step ahead of fraudsters in the identification of suspicious activities before they can cause great damage.

3. Pattern Recognition and Anomaly Detection

The major strengths of AI and ML in risk management are their ability to identify complex patterns and detect anomalies indicative of fraudulent behavior. Such systems create baseline behaviors through the analysis of historical transaction data, user profiles, and contextual information. Deviations from these norms trigger alerts for further investigation. This level of precision helps in distinguishing genuine transactions from fraudulent ones, thus reducing the incidence of false positives.

4. Continuous Learning and Improvement

These AI and ML models learn from new data continuously, which can only improve their fraud detection capabilities over time. As more transactions are processed and different fraud scenarios unfold, these models will fine-tune their algorithms to be more accurate and efficient. This is an ongoing spiral of improvement, ensuring the risk management system will change as the landscape of fraud evolves.

5. Automation and Efficiency

AI and ML can substantially reduce the need for reviews subject to risk management by automating a number of aspects involved in this particular area. Automated systems can process volumes of data at lengths and speeds inconceivable to any human analyst, allowing for effective fraud detection in a timely manner. This not only improves operational efficiency but also frees human resources to deal with more complex and risky cases that require nuanced decision-making.

6. Integration with Existing Systems

AI and ML technologies can be combined with pre-existing frameworks of risk management, thereby delivering greater potential and effectiveness without requiring an overhaul in their entirety. Equally, this will give a financial institution a chance to utilize the current running infrastructure and receive all the benefits coming from advanced AI and ML-driven insights. The result is going to be an ultimately more solid, responsive system of risk management that is able to adapt itself to polished threats and challenges.

Key Challenges and Considerations To Overcome

While AI and ML have huge potential in credit card transaction risk management, there are also a number of pitfalls and issues that arise with their implementation. Bringing solutions to these problems will be key to maximizing the effectiveness of the technologies and their ethical working.

1. Data Privacy

Since AI and ML systems are data-driven, the door is also wide open to a number of potential data privacy and security issues. However, the financial institutions should be in a position to protect sensitive customer information and establish mechanisms of data collection, storage, and processing that consider applicable privacy regulations under GDPR and CCPA; this argues further that appropriate encryption methods, access controls for customers, and good anonymization techniques will be implemented accordingly.

2. Regulatory Compliance

One of the major challenges institutions face in implementing AI and ML is managing the complex landscape of financial regulations relevant to the use and processing of data. This requires stringent controls and the associated transparency expected by regulators. Hence, institutions will have to ensure compliance with these regulations, which may involve regular audits, documentation, and reporting of AI and ML models to regulatory authorities.

3. Implementation Barriers

AI and ML technologies can be resource-intensive to adopt. Some of the common challenges faced while implementing AI and ML include:

• High Costs: Setting up AI and ML infrastructures, software, and personnel with exceptionally high skills can be really resource-intensive.
• Technical Complexity: The development and maintenance of AI and ML systems require special knowledge and expertise that are often absent in some organizations.
• Integration problems: The overall incorporation of AI and ML into underpinning systems and workflows has proved to be quite problematic. Careful thought in planning and execution will be needed if the technology is to work seamlessly.

Real-time Case Studies and Real-World Examples

Real-world examples will attest to how AI and ML find practical applications in credit card risk management. Case studies will illustrate how financial institutions have tapped into such technologies to frustrate fraud, enhance security, and improve customer satisfaction.

Many of the leading financial institutions have included AI and ML within the risk management framework with quite excellent results:

• JPMorgan Chase: AI-driven systems for tracking and analyzing millions of transactions every day have been put in place. Its AI models detect fraudulent activities with high accuracy, reducing false positives drastically and increasing the security of overall transactions.
• HSBC: ML algorithms at HSBC enhance their capability for fraud detection. Analysis of the historical transaction data will help in discovering the spend pattern; therefore, these companies can ensure prevention and prediction accordingly. This proactive policy has caused a notable decrease in fraud-related losses.

USM Business systems is also a pioneer in AI-powered mobile app development fraud detection. We help you keep your and yours esteemed customers data privacy and financial safety through developing high-quality advanced credit risks management apps.

Conclusion

AI/ML-powered mobile app development for fraud detection is the best option in this digital age. These technologies provide better accuracy, real-time processing, cost efficiency, and an improved customer experience.

At the same time, all the challenges and considerations involved do not overshadow the bright future awaiting AI and ML in risk management. Only those financial institutions that embrace these technologies will adapt to the ever-changing landscape of credit card fraud and ensure safe and satisfied customers.

How AI Is Reshaping Marketing Operations?

In this digital environment, Artificial Intelligence (AI) means a lot to digital marketing teams. AI marketing solutions are offering the best ways to derive valuable insights from the marketing data and helping organizations to build strong brand awareness in this competitive digital space.

Artificial Intelligence in marketing help marketing teams to build an efficient interactive platform between customers and businesses and reach maximum targeted audience base over online. Most of the digital marketers have already recognized the importance of AI in marketing for brand promotional activities.

Herein, we will give a brief on AI in Marketing: Benefits, Use Cases, and Examples. In this article, we give you a guide on-

• What is Artificial Intelligence (AI) Marketing?
• Why AI is so powerful for marketers?
• What are the major gears of AI marketing?
• How AI will Impact Your Digital Marketing?
• Top 10 benefits of using AI in digital Marketing?
• Top 8 AI Stats/trends that you must know as a digital markets
• Will AI be the future of digital marketing?

What Is AI In Marketing?

AI marketing is defined as one of the best approaches to predicting the customer’s next step for providing a better experience. Further, the use of AI in digital marketing will also assist marketing executives in analyzing the preferences of the targeted audience and offering personalized offerings to them. Such AI prediction would help organizations increase customer retention rate and boost sales.

Using significant AI concepts like Machine Learning (ML), Deep Learning, Predictive Analytics, and Big Data are helping marketers to boost digital marketing activities and derive the best results from automation, intelligent, and forecasting capabilities of AI.

Moreover, using the power of big data insights, digital marketing teams can efficiently analyze customers search patterns, their interests, and build a perfect image of their marketing strategy.

Hence, the use of AI and ML in marketing helps businesses of all sizes to aggressively run digital campaigns, find the targeted group of audience, know their preferences, and execute the best brand promotional campaigns. Hence, AI in marketing operations plays a key role in generating sustained leads for the company, thus ensure strong business line in this competitive era.

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Why AI Is So Powerful for Digital Marketers?

The role of artificial intelligence in marketing is showing great impact on digital marketing activities. The use of AI and ML in marketing operations is very much needed in this 21st century. According to market research, over 45% of completely matured enterprises have already deployed artificial intelligence marketing solutions for analyzing vast amounts of customer data, forecast their needs, and improve experiences. Hence, digital marketers are being implementing AI strategies to reaching their marketing targets.

Global digital marketers believe that applications of AI in digital marketing empowers online marketing approaches and take the brand value to new heights in this digital space.

Overall, AI will be a powerful asset for conducting aggressive and thoughtful digital promotional activities. Artificial intelligence in digital marketing continues to advance its existing marketing approaches and make every business smarter.

Get Smarter With Artificial Intelligence (AI) Digital Marketing Tools

AI Marketing Trends to Watch Out In 2024

Let’s take a look at the top trends of AI in Digital Marketing.

#1 Big Data

The primary role of big data in digital marketing is to help marketers in making decisions faster based on the insights derived from customer data.

Yes, Big data is a vast concept of data collection from various sources. It is an effective component for doing digital marketing campaigns. It helps digital marketers’ in segmenting complex customer data sets, deriving insights, knowing personalized preferences, and providing the best services to customers at the right time through a selected communication channel.

#2 Machine Learning

Artificial intelligence marketing solutions developed using machine learning will help digital marketers to derive valuable insights from this massive quantity of data. The use of ML in digital marketing help to identify market trends, predict demand, and provide customer-oriented services. Hence, adoption of ML algorithms in AI marketing allow marketers to perform revenue-worthy operations.

#3 Emotional AI

Technology is advancing more than ever like before. AI-based solutions for digital marketing can interpret customer emotions and communicate accordingly. It’s a wonderful thing that happens using emotional AI technology.

Learn more about how USM AI Solutions can help you expand your marketing operations.

How AI Will Impact Your Digital Marketing?

We have explained in many of our blogs that Artificial Intelligence is revolutionizing many industries, including marketing. Ranging from baking and finance, and healthcare to retail, manufacturing, and travel, AI is changing the way of doing business.

Various AI concepts such as text-to-speech recognition, Natural Language Processing (NLP), and voice recognition technologies are all enabling machines to perform human-like tasks with more intelligence. AI-based conversational chatbots are one of the best examples of intelligent customer support solutions or NLP apps in digital marketing.

So, how is AI used in marketing?

• AI in digital marketing sends personalized content to users based on their search
• Artificial intelligence in marketing helps marketers to segment their targeted audience based on their interests
• Streamlines communication channel with a Live chat customer service
• AI can transform the way of business and customer interaction
• Increase operational excellence and optimize the user experience
• AI offers continuous customer services with the use of AI chatbots
• The use of AI in marketing helps brands in cutting costs and increasing revenues

Benefits Of Using AI In Digital Marketing

Now, in this section, we’ll have a brief discussion on how can AI help marketing teams.

AI marketing is becoming popular day by day with the visions it provides to digital marketers. Let’s look at a few core benefits of using AI for your digital marketing purpose.

#1 Advanced and intelligent search

Are you a digital marketer?
If yes, you should remember that not only emerging technology solutions becoming smarter but also the customers too. Nowadays, customers are smarter. They prefer fast and quick response platforms and search engines.

Artificial intelligence and big data solutions can analyze user search patterns and help digital marketers for identifying key areas where they need to put their efforts. It is one of the best benefits of using for digital marketers. The digital marketing team can track their audience preferences and improve lead conversions by offering personalized services/product recommendations.

#2 Smart Advertising Strategies

Smart advertising is the best application of AI in marketing. AI reduces the efforts of digital marketers by automating advertising campaigns. It is one of the applications of AI in digital marketing. AI tools, digital marketers can publish service or product-specific ads across various mediums and reach a broader audience base.

What Is Artificial Intelligence In Advertising?

Artificial intelligence in advertising helps marketing teams to better use their keywords to target their customers quickly. The AI strategy and solutions for marketing allow digital marketers to efficiently engage customers and boost revenues.

#3 Automates Every Marketing Process

It is one of the best applications of AI in digital marketing. Marketing automation using AI is like fueling traditional marketing businesses with more and more emerging technologies. Every manual digital marketing task will be automated using artificial intelligence technology.

#4 Personalized and Superior Content Delivery

It is one of the top benefits of using AI in digital marketing. Personalized content delivery systems are the best innovation of AI technology. The importance of artificial intelligence in marketing for delivering adapted content to a targeted audience is gaining momentum in the industry.

Using AI tools, digital marketers can make use of data and target the right audience at the right time. Artificial intelligence tools and solutions in digital marketing allows marketing teams to find potential buyers and send more personalized content that meets their needs.

#5 Evolving AI Chatbot Services

It is one of the best applications of AI in marketing. Customer retention was a challenging task for digital marketers. With the use of AI-powered customer service Chatbots, marketers can retain their customers efficiently. However, over 50% of online marketing companies are depending on customer service bots to increase lead conversion rates.

#6 Lead Management and Nurture

It is one of the top benefits of AI for digital marketers. AI tools and applications in marketing identify possible potential customers and develop a healthy sales pipeline.

Artificial intelligence greatly helps digital marketing teams with Lead Management and Lead Nurture smartly.

USM Business Systems, the best custom AI development company, has a strong knowledge of using artificial intelligence technology and delivering AI solutions that improve your digital marketing operations.

#7 Find Opportunities and Trends

Digital marketers can use AI technology to find the most attractive business growth opportunities for brand expansion. Competitive Intelligence capabilities of innovative AI tools can scan a vast quantity of data to derive and analyze current market trends.

This will help marketers to forecast to build strategies that help to find new ideas for running innovative marketing campaigns.

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#8 Integration of technology and marketing teams

A combination of AI technology and your customer service team gives unbelievable marketing benefits to your business. Market analysis, customer demands, and quick response everything possible by integrating AI into your customer service teams.

#9 Conversational AI

The advantages of implementing conversational AI in marketing are wonderful. They can provide personalized experiences to your customers, and add value to your brand beyond sales. Hence, conversational AI is one of the best approaches that help you build strong relationships with your customers.

#10. Generate More Revenues

One of the best use of Artificial intelligence in marketing is analyzing the competitors’ move to witness strong sales and thus huge revenues. In addition, AI helps marketers to find patterns that are likely to impact the future of marketing business.

These are the top 10 ways to use artificial intelligence in marketing activities. On top of all, personalized content deliveries, lead management, streamlined activities, automatic email marketing campaigns, and virtual customer support services by AI assistance are all the top benefits of AI for digital marketers.

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Top 8 AI Stats That Digital Marketers Must Know

We captured a few significant statistics about the market estimation of AI in digital marketing. They include-

• Organizations that implemented AI strategies in marketing and sales were reduced by 70% of reductions in call-time
• According to McKinsey, AI will double the leads count
• The combination of AI and ML technologies reduces the percentage of shopping cart removal to 30%
• As of Venture Harbour, approximately 60% of digital marketers believe that AI is the best technology to build data strategies
• AI-enabled voice assistants would drive the growth of digital marketing
• According to Forbes, over 86% of companies are using AI to predict sales growth and improve their email marketing campaigns.
• AI trends say that AI increased online shopping frequency by 50%
• In the next three years, every digital company will make use of AI in their sales processes

Start with a plan and change your digital marketing ways with AI tools and apps.

Will AI Be The Future Of Digital Marketing?

How is AI transforming the future of digital marketing?

By reading the above information, how many of you believe that artificial intelligence is not only the technology that empowers the marketing channels today but also allows businesses tomorrow?

AI solutions for digital marketing assist marketers in automating SEO, SMM, SEM, keyword research, lead management, and email campaigns like operations and improve conversion rates.

USM’s custom AI developers in the USA and India have already predicted the market demand for AI and ML in marketing (artificial intelligence in digital marketing). Our creative technology experts are already ready with the AI-powered marketing solutions that you require.

Our artificial intelligence services and solutions take over tedious, complicated, and time-taking digital marketing operations that marketers face trouble dealing with.

As a leading AI app development company, USM delivers AI solutions for the most engaging smart digital marketing strategies.

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Impact of Artificial Intelligence on The Insurance Industry

The Impact of Artificial Intelligence AI in Insurance

Artificial intelligence is changing the world in the best way possible. It began to take over several sectors, including insurance. The insurance and finance industry has brought radical transformation since the evolution and use of AI in insurance underwriting.

AI is altering conventional insurance operations and methods significantly. Due to the high volume nature of insurance firm activities, AI technology can indeed have a digital transformation effect.

Some of the insurance companies use Artificial Intelligence (AI) and machine learning (ML) technologies to automate certain stages of the claims management process and improve customer service. Furthermore, blockchain technology is being used for fraud detection.

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How Does AI Impacts Insurance Industry?

If you are an insurance and finance service provider, you must have to know about Artificial intelligence in insurance use cases and the impact of AI on the future of insurance services.

Here, we have compiled a list of top AI applications in insurance and the adoption of this Artificial intelligence in insurance use cases will bring automation to processes, optimize productivity, and aid insurers in delivering top-notch digital experiences to their clients.

1. AI for Digital Insurance Claiming

Claim processing is a core function of insurers. It consumes lot of time of resources in manually verifying the documents.

AI for digital insurance claiming is one of the best applications of the technology. Unlike messy paperwork’s, AI insurance services digitally captures required information from smart copies and makes insurance claiming faster and efficient. Intelligent AI algorithms will take over and automate all the early claiming processes with more accuracy.

2. Risk Management Use Case in Insurance

Artificial intelligence insurance aids insurance, investment, and finance companies identify fraudulent claims and financial risks faster. AI apps or AI solutions build a secure platform between customers and insurance executives to make the process seamless.

AI and ML algorithms will verify customer documents and find risk profiles in minutes. By validating the information regarding credit, financial stability, and personal behaviour, AI-powered insurance apps help service providers’ possible insights into risks.

3. AI In Insurance Underwriting

The use of AI in insurance for automating the manual process of underwriting will save a lot of time of resources and improves productivity. Leveraging the capabilities of AI, ML, and deep learning, intelligent AI insurance app gathers massive data from various resources like external applications, insurers, and customers. Later, this information will be automatically categorized by in-built segregation tools and stored in respective records.

So, such an automated process will aid insurers in analysing claim type, customer risk profile, deciding the insurance eligibility, etc. Hence, AI in insurance underwriting is the best digital solution to save time, automate the underwriting process, and prevent manual errors in data.

4. Artificial intelligence Insurance for Budget Panning

Price is central to customer decision-making for creating new budget-friendly insurance plans. Artificial intelligence in insurance use cases for determining competitor plans and creating customer-friendly plans is gaining popularity.

AI and ML applications in insurance analyse data and insurance offers of rivals and offer new term plans for existing customers. Such friendly insurance offers also help brands to grab the attention of new customers seamlessly.

This is the future of AI in insurance. Not only these, but the impact of AI on the future of insurance will also be far-fetched and move to new heights that you cannot imagine. AI insurance companies will become a leader in the industry, deliver top-notch automated performance over traditional companies, and be a quick responders to people who are interested to claim long-lasting life insurance coverages and many more profitable schemes.

So, ready to become a leading AI insurance company and stand out from the list of companies that follows traditional insurance processes.

Also Read: How Corona virus epidemic effect AI innovation in the insurance industry?

How Can Insurers Prepare For AI-driven Future?

Insurance sector is fueled by the widespread adoption and integration of deep learning, automation, and external data ecosystems. While none of us forecast what insurance industry will look like in the coming decade i.e. 2030, carriers can now take importance like below to prepare for AI-driven future.

Distribution:
The insurance purchasing experience is faster with less involvement of the customers and insurance executives. AI algorithms create risk profiles that provide sufficient information about personal behavior, thus reducing the cycle time to minutes or seconds to complete an auto, life policy or commercial insurance purchase.

Underwriting and Pricing:  
By 2030, manual warranty/ underwriting for personal and small-business products will cease to exist throughout accident, life and property insurance. With a combination of deep learning and machine learning models built into the technical stock a large percentage of the underwriting is automated and supported so the underwriting process is reduced to a few seconds.

Pricing:
Price is central to customer decision making, while carriers innovate to reduce competition entirely on price. Advanced ownership platforms connect insurance companies and customers and provide customers with different aspects of the industry like value, features and experiences.

Price competition Exacerbates and razor-thin margins are the norm in some segments. In other segments, specialized insurance offers allow differentiation and margin expansion. Within the jurisdiction that embraces change, the pace of price innovation will be faster.

Pricing is based on data-rich risk, consumption, dynamic, and empowers people to make decisions about how their actions affect insurance, coverage, and most importantly, pricing.

Claims: 
Claims processing will remain the primary task of carriers in 2030, but the head count partnered with claims will be minimized by 70% to 90% compared to 2018 levels. Advanced AI and ML algorithms increase the efficiency, accuracy, and routing of initial claims.

Claims for small-business insurance and personal lines are increasingly automated, allowing carriers to gain direct processing rates of over 90% and dramatically reducing claim processing time from days to minutes or hours depending on the task.

Also Read: How the Corona virus epidemic effect AI innovation in the insurance industry?

How Can Insurers Prepare For AI-driven Future?

Insurance sector is fuelled by the widespread adoption and integration of deep learning, automation, and external data ecosystems. While none of us forecast what insurance industry will look like in the coming decade i.e. 2030, carriers can now take importance like below to prepare for AI-driven future.

#1 Get Smart On AI-related Trends and Technologies

Although tectonic changes in the industry are tech-focused, addressing them is not at all the job of the IT team. Instead, board members and customer experience teams should invest resources and time to gain an in-depth understanding of technologies like AI and ML.

Also, insurers should understand market dynamics and discover smart solutions to address changing insurance needs. You should create plans that elevate your brand and your services on a global scale.

#2 Develop & Implement A Coherent Strategic Plan

Insurers need to develop a perspective on the areas in which they want to invest in AI to meet the business requirements and beat the competition. For example, AI is best suitable for automating processes, creating new connected infrastructure, or augmenting and modifying internal strategic capabilities.

#3 Create & Implement A Comprehensive Data Strategy

AI technologies work best in processing data and deriving results-driven insights. These insights will assist companies in creating data strategies that optimize the operational flow.

 #4 Create A Good Talent & Technical Infrastructure

The insurance company of the future needs talent with the right mind and skills. The front-line insurance workers of the next decade will be in high demand and must be willing to work in a dynamic mix of creativity, technology, and constantly evolving machine-supported and semi-automated tasks.

AI insurance company needs to integrate the skills, technologies, and insights to provide unique customer interactions, and experiences and generate value from the AI use cases of the future.

Final Thoughts

Well, the future of AI in the insurance industry will be expected to leave tremendous growth opportunities to the service providers. And, future of AI in insurance is expected to draw unbelievable automation across the value chain of insurance processes as we discussed in this article.

AI Insurance Services is ready to disrupt the insurance field like never before for both customers and insurers. Artificial intelligence insurance provides seamless user experiences at affordable rates and erases the complex paperwork insurance processes in the coming years. Yes, we cannot imagine the impact of AI on the future of insurance.

Insurance firms need to save money and time by making their processes more effective and efficient. With AI-based solutions, the possibilities are endless, and only a matter of time before we can see and experience these improvements.

If you are looking for the best AI service provider in India, USM Business Systems in the USA and Europe countries to automate your insurance business.

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 Car Rental App Development Cost and Features:

In this digital age, on-demand mobile apps (Android/iOS) are gaining momentum across the global nations. Convenience in booking services and reliability in service delivery, service delivery apps such as food delivery apps, car rental apps cab booking apps, and package delivery apps are in traction.

Yes. Service delivery apps are becoming popular across diverse industries and car rental is one of them. Today, through this article, we would like to share a guide on how much it costs to create a car rental app like Ekar. Herein, will walk you through the must-have features of on-demand car rental app development and the factors that impact the mobile application development costs.

Firstly, let’s take a look at the benefits of car rental apps to end-users.

What Is The Purpose Of The Car Rental App?

Renting a car has never been easier, but online car rental booking apps made this possible in minutes. Car rental apps are mobile apps or responsive web apps that help end-users avail of self-drive car services or driver-assisted care rental services on-demand. Offering a range of Cars and allowing users to toggle between fuel options, hassle-free payment options, and door delivery of booked cars, Car rental applications provide quick and affordable rentals to users.

Moreover, pay-per-hour, pay-per-day, and pay-per-month like plans, and car rental apps are offering users convenience in choosing from multiple rental options to meet their desired travel needs. Transparent pricing, free-parking slots finding facility, 24/7 customer support, GPS navigators, location-tracking facility, and flexibility to hire a car with or without fuel are all a few cool features that are creating waves for Car Rental Apps demand worldwide.

Must-Have Features To Add In A Car Rental App Development 

Features of a mobile application are core pillars that decide its success rate. Before commencing the development process, make sure to list the best features that deliver seamless experiences to users and derive great business value over time. Top mobile app development companies conduct thorough research on competitor apps, market opportunities, user preferences, and trends to create the best car rental app with the most useful features and functionalities.

Here are a few must-have features that you must integrate into a car rental app like Ekar development.

Must-have features of a Car Rental App development for users

• Quick registration
• Signup/login in simple steps
• Social media login feature
• User profile
• Multi-language feature
• Tracking available vehicles
• Location pinning
• In-app map integration
• Customized ride options
• Schedule pickups
• Two-way authentication
• Online payments
• Ride history
• Rebook vehicle
• Push notifications
• GPS navigators to track location in real-time and finding nearly parking slots

Features for driver module development of Car Rental Apps like Ekar Clone Development: 

• Signup and registration
• Driver profile management
• Bookings management (Pickup/Cancel/Door delivery of rented vehicle)
• In-app map integrations for tracking destinations
• Route optimization algorithms
• Rides history
• Payment history
• Push notifications

Must-Have Features To Develop Car Rental App Admin Module 

• User Profile Management
• Driver profile management
• Vehicles management
• Orders or bookings management
• Payments management
• Push notifications management
• Rental or ride pricing management
• Reviews and ratings management

The features and functionalities you selected will impact the final cost of a car rental apps. Ekar-like clone pap development needs certain features developed using Artificial Intelligence and IoT like cutting-edge technologies for ensuring remote monitoring, traffic monitoring, and driver behavior analytics, and vehicle performance monitoring etc. Adding such features will increase the development costs of car rental apps but take it to new heights.

Which Technology Stack Is Best for Car Rental App Development? 

The technology stack you select for car rental app development plays a significant role that impacts performance, application scalability, responsiveness, user experiences, security, and overall decides its success rate.   

• Best programming languages for Car Rental App development on Android OS- Kotlin, Java
• Most preferred programming languages for Car Rental App Development for iOS- Swift and Objective C
• Programming languages for Cross-platform Car Rental App development- Flutter, Xamarin, and React Native
• Frameworks used for Mobile App Development– Android for Android app development and iOS SDKs for iPhone app development
• Database: MongoDB
• Push Notifications: Twilio
• Storage: AWS and Google Cloud
• Payments: Third-party Payment Integrations

How Much Does It Cost For Car Rental App Development?

The cost to develop an Ekar-like car rental app development will range between $30,000 to $75,000. However, the development costs of a mobile app will depend on many factors such as features and functionalities, app development platform, and application type (native app development, cross-platform development, or hybrid application development.

Further, the cost of a car rental platform like Ekar will also depend on the tools and technologies used in the development process. Integrating car rental apps with advanced technologies, such as Artificial Intelligence will offer several benefits, such as dynamic pricing, AI chatbots, license recognition, etc. It will increase the development costs of the car rental platform beyond $100,000, but automate the processes, and improve the operational excellence and experiences.

Moreover, mobile app developers’ location and their team size are also significant cost-impacting factors that determine the cost of car rental app development like Ekar. For instance, top mobile app developers in the USA and European nations will charge approximately $100-$150/hr, which is very high compared to the best mobile app development companies in India like budget-friendly markets.

The car rental app development cost will also depend on the post-launch services, including app maintenance and support. If you introduce your MVP into the market, you can save money to an extent, however, you must incur certain costs for updating features as per the user needs.

Are you planning to invest in car rental app development and have an idea?

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