Tag: Artificial Intelligence

Artificial Intelligence (AI) evolved from a concept of science fiction to a transformative force that permeates our daily lives. From autonomous vehicles to voice assistants, AI has already made significant inroads in various sectors.

However, one area that stands to gain immensely from AI’s potential is the supply chain. As the backbone of global trade, the supply chain encompasses complex networks and intricate logistics. It is an ecosystem where efficiency, accuracy, and agility can make or break success.

With its vast array of applications, AI has the potential to streamline operations, enhance decision-making, and unlock untapped opportunities. In this journey through AI’s rising capabilities, we will delve into real-world use cases that demonstrate how AI is revolutionizing the supply chain. Furthermore, we will also explore the specific benefits that AI brings to the supply chain domain.

Role Of AI Optimizing the Supply Chain

Every business owner dreams of a supply chain that is finely tuned, seamlessly efficient, and adaptive to every twist and turn of the market. A business where warehouses run like clockwork, shipments arrive precisely on time, and customer demands are anticipated with uncanny accuracy is not a far-fetched dream; it’s a reality being shaped by the game-changing role of Artificial Intelligence (AI) in optimizing supply chain operations.

At the heart of AI’s transformative influence are three key components that work in harmony to revolutionize the supply chain landscape. Let’s uncover their captivating role in reshaping the future of supply chains.

• Machine Learning and Predictive Analytics: Machine learning and predictive analytics in the supply chain are like having a trusted, experienced mentor by your side, whispering valuable insights and guidance into your ear. Machine learning algorithms analyze vast amounts of historical data to uncover patterns, trends, and potential pitfalls. 
• Natural Language Processing and Chatbots: Natural Language Processing (NLP) allows you to simply ask a question about your supply chain and receive instant, accurate answers. With a chatbot available 24/7, customers can get instant responses, while supply chain teams can focus on strategic decision-making.
• Robotics and Automation: Robots, equipped with advanced sensors and AI algorithms, can perform repetitive tasks with unmatched precision and speed. From inventory management to order fulfillment, these tireless machines streamline operations, reduce errors, and enhance efficiency.

How AI Solves Supply Chain Challenges

The world of supply chain management is like a complex maze with numerous challenges at every turn. Thankfully, AI emerges as the trusty guide, equipped with the tools to solve some of the most daunting hurdles. Here are some for your reference: 

1. Demand Forecasting and Inventory Optimization: This AI-powered assistant acts as your supply chain ‘savant,’ it understands your historical consumption patterns, market trends, and even factors like seasonality or promotional events. 

2. Supplier Selection and Relationship Management: Choosing the right suppliers and maintaining strong relationships is like finding the perfect dance partner. AI steps in as a knowledgeable matchmaker. By analyzing vast amounts of supplier data, performance metrics, AI algorithms can assess and rank potential suppliers based on criteria such as reliability, quality, and cost. 

3. Warehouse and Inventory Management: AI acts as a vigilant warehouse manager, optimizing layout, guiding picking and packing processes, and even predicting optimal storage locations. With AI-powered systems, warehouses can maximize space utilization, minimize errors, and accelerate order fulfillment, resulting in streamlined operations and satisfied customers.

4. Transportation and Logistics Optimization: AI takes on the role of coordinator who has a bird’s-eye view of the entire transportation network, utilizing algorithms to analyze real-time data on factors like traffic, weather conditions, and delivery constraints. By optimizing routes, load planning, and vehicle assignments, AI enables efficient transportation management.

5. Quality Control and Defect Detection: Think of a diligent quality inspector who never misses a flaw in a product. AI becomes this meticulous inspector, utilizing computer vision and machine learning algorithms to analyze visual data and detect defects with remarkable accuracy. 

6. Risk Management and Supply Chain Resilience: AI plays this vital role just like a risk management expert. It analyzes a wide range of data sources to identify potential risks and vulnerabilities, ensuring supply chain resilience in the face of uncertainties.

7. Customer Service and Satisfaction Enhancement: AI takes on the role of a customer service representative who can swiftly address customer inquiries, provide accurate information, and resolve issues with ease. AI-powered customer service tools offer instant responses, personalized recommendations, and seamless assistance, enhancing customer satisfaction and loyalty.

Watch: Artificial Intelligence – how to navigate AI if you are not a tech company.

Remarkable Real-world examples of AI in the Supply Chain

AI transforms supply chain management like never before. Don’t take our word for it. See it in action as implemented by big players in the industry:

Use Case 1: Precision Prediction by Amazon

Problem: Traditional demand forecasting and inventory management methods often struggle to predict customer demands and optimize inventory levels in real-time accurately.

Solution: To address this challenge, Amazon has harnessed the power of AI algorithms to revolutionize demand forecasting and inventory management. By analyzing vast amounts of customer data, historical sales patterns, and even external factors like weather forecasts, AI algorithms can accurately predict demand with remarkable precision.

This AI-driven approach allows Amazon to optimize inventory levels, ensuring that popular products are readily available while minimizing excess inventory and reducing the risk of stockouts. By aligning supply with demand, Amazon is able to enhance customer satisfaction and maintain a competitive edge in the dynamic e-commerce landscape.

Use Case 2: Substitution Solution by Walmart

Problem: In online grocery shopping, customers often encounter situations where certain items they ordered are out of stock. This can lead to dissatisfaction and inconvenience, as customers may have to manually search for suitable substitutes or go without the desired product.

Solution: To address this issue, Walmart has implemented an AI-driven product substitution system. Using advanced algorithms, the system analyzes product attributes, customer preferences, and available inventory data to suggest suitable substitutions for out-of-stock items.

When an ordered item is unavailable, the AI system automatically identifies the best possible substitute based on factors such as brand, size, price, and customer feedback. It takes into account the customer’s past purchase history and preferences to make personalized recommendations. The system provides clear and transparent information to customers, ensuring they are aware of the substitution and have the option to accept or reject it.

Use Case 3: Real-Time Routing by UPS

Problem: Traditional route planning methods often struggle to optimize delivery routes efficiently, resulting in inefficient use of time, resources, and fuel.

Solution: UPS leverages AI algorithms for route optimization, enabling them to analyze real-time data on factors such as traffic patterns, delivery constraints, and even weather conditions. By considering these variables, UPS can generate optimal delivery routes that minimize distances, reduce fuel consumption, and optimize delivery time.

Through the implementation of AI in its logistics operations, UPS achieves significant cost savings, improves delivery efficiency, and reduces its carbon footprint. This AI-driven approach allows UPS to stay ahead of the competition and provide exceptional service to its customers.

Use Case 4: Valuable Vending by  Coco-Cola

Problem: Traditional vending machines often lack the ability to gather real-time data on customer behavior and gauge the effectiveness of different brands and product offerings. 

Solution: To overcome these limitations, Coca-Cola has implemented AI-enabled next-gen vending machines. These machines are equipped with advanced sensors, cameras, and AI algorithms that gather real-time data on customer behavior, purchasing patterns, and brand preferences.

With this newfound understanding, Coca-Cola can optimize product placements, tailor offerings to specific locations, and develop targeted marketing campaigns. Furthermore, the AI-enabled vending machines also allow Coca-Cola to remotely monitor inventory levels, predict demand patterns, and optimize restocking schedules. This ensures that the vending machines are always well-stocked with popular products, reducing the likelihood of stockouts and maximizing sales opportunities.

Use Case 5: Wonder Warehouses by Alibaba

Problem: Traditional warehouse management practices often face challenges related to inefficient storage utilization, suboptimal picking processes, and delays in order fulfillment.

Solution: Alibaba has embraced AI technology to develop smart warehouses that leverage automation, robotics, and AI algorithms. These AI-enabled warehouses optimize storage utilization, streamline picking and packing processes, and enable efficient order fulfillment.

Through the integration of AI, Alibaba achieves faster and more accurate inventory management, enhances warehouse operations, and improves overall efficiency in its supply chain. This innovative use of AI allows Alibaba to meet the demands of the e-commerce market and deliver exceptional service to its customers.

Checkout out our Infographic: Successful Logistics and Warehouse Management Practices.

Solid Supply Chain Solution with AI by Fingent

Advancements in AI technologies continue to shape the supply chain landscape, with machine learning algorithms becoming more sophisticated, natural language processing capabilities evolving, and robotics and automation becoming increasingly intelligent and adaptable. These advancements enable businesses to make data-driven decisions, automate repetitive tasks, and optimize operations like never before.

At Fingent, we understand the immense potential of AI in supply chain management and are committed to helping businesses harness its power. Our expertise lies in developing innovative AI solutions tailored to specific industry needs, integrating AI with emerging technologies, and driving digital transformation in the supply chain.

Whether it’s building intelligent forecasting models, implementing AI-powered automation, or leveraging AI-driven analytics, Fingent is dedicated to empowering organizations to thrive in the AI-driven supply chain landscape.

Businesses that embrace its potential will gain a significant competitive advantage. By leveraging AI technologies, integrating with emerging technologies, and partnering with experienced custom software solution providers like Fingent, organizations can unlock new frontiers of efficiency, innovation, and success in the dynamic world of supply chain management.

Reach out to us to get the best supply solution for your business. 

Today we live in a world where machines possess an extraordinary ability to learn, reason, and make decisions, much like the human mind. This remarkable realm of technology known as Artificial Intelligence is not merely a product of science fiction or futuristic imagination. It has become an awe-inspiring reality that is transforming the landscape of countless industries.

But that’s just the tip of the AI iceberg.

In mobile development, AI can transform your customer’s device into a personal shopping assistant, a language guru, or a creative photographer all in the blink of an eye. 

The integration of AI in mobile app development doesn’t stop there. 

It unlocks a realm of possibilities for your customers, from personalized virtual assistants that organize their life, to fitness apps that act as their personal trainers, to healthcare apps that monitor their well-being.

But how do we understand the concept of AI in mobile apps?

Unraveling Artificial Intelligence in Mobile Apps

Simply put, AI is like the brain behind the scenes, making your apps smarter and more interactive. 

One of AI’s superpowers is Machine Learning (ML). It’s like a super adaptable brain that learns from data and experiences. Machine learning algorithms analyze massive amounts of information to get better at tasks. They can recognize patterns, make predictions, and even understand your preferences.

Another clever component is Natural Language Processing (NLP). It’s like an AI language translator that allows you can talk to your app, ask questions, and it magically understands and responds. NLP allows your AI sidekick to grasp the meaning behind your words, making conversations with your app feel more human-like. 

How does it help?

Read more: Understanding NLP: Will It Reign Supreme In Near Future?

From Mundane to Marvelous – Benefits of AI In Mobile Apps

Weaving the powers of AI into your mobile apps can enhance user experience. How? Like a brilliant and intuitive companion, AI-powered mobile apps can provide personalized recommendations. AI algorithms analyze user behavior, learn their tastes, and curate a world of suggestions. 

Plus, it learns and grows with them. The more your customers use your apps, the smarter those apps become, tailoring their suggestions to your customer’s ever-changing whims and fancies and predicting their move, and effortlessly serving up what they need.

Read more: https://www.fingent.com/blog/is-ai-powered-mobile-app-what-you-need-for-your-business-now/

Key Applications of AI In Mobile Apps

AI brings a layer of intelligence to your apps that takes them to the next level. Here are some key applications that this has made possible: 

1. Voice Assistants and Natural Language Processing

40% of mobile users use voice search at least once a day. – Comptia.

Natural Language Processing (NLP) enables the integration of voice assistants like Siri, Google Assistant, and Alexa into mobile apps. No matter how they phrase it, NLP enables your app to decipher the meaning and context of their spoken words. 

It is capable of unraveling the intricacies of slang, deciphering accents, and even understanding complex sentences with multiple layers of meaning. It’s like having a language expert at your beck and call. But it doesn’t end there. NLP allows voice assistants to learn from every interaction, becoming more intelligent over time.

2. Personalized Recommendations

AI algorithms can analyze user data to provide personalized recommendations in mobile apps by utilizing machine learning techniques:

• Data Collection: Mobile apps collect user data through various means, such as user registrations, app usage tracking, explicit ratings, and implicit signals like clicks, views, and interactions.
• User Profiling: Such data is used to create user profiles that capture individual preferences, interests, and behaviors. 
• Pattern Recognition: AI algorithms can identify similarities based on factors like item attributes, past behavior, and user demographics.
• Recommendation Generation: Based on the identified patterns, the algorithms generate personalized recommendations. For example, in a music app, the algorithm might suggest songs or artists similar to the user’s previous listening habits or recommend popular tracks among users with similar tastes.

The benefits of personalized recommendations for user engagement and satisfaction are significant:

• Enhanced User Experience: Users are more likely to discover new content they enjoy and spend more time using the app.
• Improved Discovery: Personalized recommendations help users explore new music genres, discover new movies or shows, or find products that suit their tastes, leading to greater satisfaction.
• Time and Effort Saving: With personalized recommendations, users can find relevant content more quickly and easily.
• Increased User Retention: When users receive preferred recommendations, they are more likely to remain engaged with the app. 
• Business Benefits: Personalized recommendations result in improved conversion rates and increased customer loyalty.

3. Image and Video Recognition Tasks

AI plays a crucial role in mobile apps across industries, including e-commerce, social media, entertainment, gaming, and more. For example:

• Facial Recognition: This technology is widely used in mobile apps for various purposes, such as authentication, photo tagging, and personalization.

• Object Detection: With AI algorithms, mobile apps leverage object detection for a range of purposes, such as visual search and safety features.
• Augmented Reality (AR) Experiences: AI algorithms are employed in mobile apps to enable applications like virtual try-on for shopping, gaming, and navigation.

Read Case Study: How Fingent helped build a unique mixed reality application for a leading university that enables users to identify people using facial recognition!

4. Intelligent Chatbots

The integration of AI-powered chatbots in mobile apps revolutionizes customer support and interaction by enabling efficient and automated communication with users. Using AI algorithms, chatbots recognize the intent behind user queries and quickly search and retrieve relevant information to address user queries effectively.

Success Stories

Mobile apps have been able to enhance user satisfaction, drive revenue growth, and achieve operational efficiency, resulting in their success in the mobile app market. Here are some examples:

1. Instagram

Instagram, one of the “big three” social media platforms, utilizes AI algorithms to provide personalized content recommendations in the Explore tab. This greatly improves user engagement by helping users discover relevant posts and accounts. AI is also used for content moderation, and identifying and filtering out inappropriate or spammy content, thus creating a safer user environment.

Impact: AI integration in Instagram has contributed to increased user engagement by facilitating content discovery and improving user safety by detecting and removing harmful content. Today it is 4th most used social media platform and 5th most visited website.

2. Uber

Uber, a ride-hailing platform, employs AI algorithms to optimize its dynamic pricing system. Machine learning models analyze supply and demand patterns, traffic conditions, and historical data to determine surge pricing, ensuring efficient allocation of drivers and meeting high-demand periods.

Impact: AI integration in Uber enables efficient pricing strategies, ensuring the availability of drivers during peak demand and generating increased revenue for the company.

In 2022, Uber experienced substantial growth with a revenue of $31.8 billion, marking an 82% increase from the previous year. Furthermore, the number of completed trips also saw an increase, with Uber drivers recording 7.6 billion trips, exceeding the previous peak of 6.9 billion trips in 2019. 

3. Amazon

Amazon, a leading e-commerce platform, extensively uses AI across its mobile app for personalized product recommendations, dynamic pricing, inventory management, and fraud detection.

Impact: AI integration in the Amazon app has led to increased user engagement by providing relevant product suggestions, improved customer satisfaction through personalized experiences, optimized pricing strategies, and enhanced operational efficiency.

In Amazon, it was observed that there is a 42% likelihood of a customer proceeding to a prospective product purchase. On the other hand, Walmart and Etsy have recorded figures of 16% and 13% respectively.

Amazon’s Alexa has taken over the world’s smart speaker industry, by securing an impressive 26.4% market share.

Emerging Trends in AI For Mobile Apps

Emerging trends in AI for mobile apps are shaping the future of mobile app development. Here are two key trends:

1. Edge Computing: Edge computing involves processing data locally on the device or in nearby edge servers, reducing the reliance on cloud computing. This trend enables AI-powered mobile apps to perform complex tasks and analysis directly on the device, leading to faster response times, enhanced privacy, and reduced dependency on internet connectivity.

Implications: The increasing adoption of edge computing enables apps to respond quickly to user inputs, process sensor data in real-time, and provide immediate feedback, leading to faster and more seamless experiences.

2. Federated Learning: Federated learning allows AI models to be trained collaboratively on decentralized data from multiple devices without transferring sensitive user data to the cloud. Each device performs local model training, and only model updates are exchanged, ensuring privacy and data security.

Implications: Future advancements will likely include greater transparency, explainability, and fairness in AI algorithms to ensure user trust and mitigate potential biases or discriminatory outcomes.

Personalize, Engage, and Future Proof with AI

In this era of technological revolution, artificial intelligence stands as a beacon of innovation and possibility. AI integration in mobile apps offers compelling benefits such as personalized experiences, improved user engagement, increased efficiency, advanced functionalities, data-driven decision-making, competitive advantage, and future-proofing. 

These reasons make AI integration a strategic choice for app developers looking to deliver exceptional user experiences and drive the success of their mobile app projects.

By partnering with Fingent, you can leverage our expertise in AI and mobile app development to unlock the transformative potential of AI in your app projects. From custom travel apps to apps using AI enabled chatbots and virtual assistants, Fingent has created unique solutions for clients across the globe. Our commitment to delivering tailored solutions, adherence to data privacy, and end-to-end services make us an ideal choice for AI mobile app development.

Contact us, the leading custom software development company, and let’s explore the possibilities together.

“A simple rule: always give people more than they expect.”    –  Nelson Boswell 

The cycle of business starts and ends with customers. Keeping them satisfied and happy is the number one rule of any business that dreams of being successful. Customer needs and expectations never cease, so businesses should always be prepared to meet and exceed their needs. Artificial Intelligence has been a substantial help in this area since the late 19th century, and it consistently finds new innovative ways to amplify its presence in modern businesses.

Meeting Customer Needs and Exceeding Expectations

Recent research reported that a good number of executives have already planned to invest more in rising technology to gain a competitive advantage. Due to the Covid-19 pandemic, almost all businesses were forced to move to an online platform to survive, further underscoring the need to adopt AI technology.

It is extremely imperative to recognize and address the needs, desires, and emotions of people which change from moment to moment. Businesses have to provide their customers and clients with care beyond purchases and respond to the intricacies in their lives. In a world that moves forward so fast, it’s best not to fall behind.

Read more: Realizing Self- Service in Modern Customer Experiences

What Is Artificial Intelligence and How Does It Impact Customer Experience?

The textbook definition of Artificial Intelligence is – a semblance of human-like intelligence processed by machines, especially computer systems. AI is used by developers to:

• efficiently perform mundane tasks that humans otherwise do.
• connect with customers.
• recognize patterns.
• solve problems.

AI Customer experience is when artificial intelligence tools are used to learn about customers and improve their business experience. The AI technologies that are famously emerging include machine learning, natural language processing, automation, chatbots, virtual assistants, and even enhanced customer experience platforms.

There are three major ways in which AI impacts Customer Experience –

1. Better Understanding Of Customer

Artificial Intelligence combined with machine learning enhances the gathering and analyzing of social and factual data of customers, which then facilitates businesses to gain an accurate understanding of their customers. AI is known for continuously learning and improving from the data it surveys. This enables it to predict customer behavior perfectly.

2. Real-time Decision Making

Making decisions in real-time is the ability of AI to collect fresh data from current interaction with a customer and make a decision with near-zero delay. It is a very effective marketing strategy and often leads to predictive analysis, which is the process of analyzing statistics, data mining, and modeling to make accurate predictions.

3. Hyper-Personalization

Artificial Intelligence, along with all its advanced technologies, proffers content that is specifically relevant to the customer. This eradicates the need to search for services the customer requires manually and adds a layer of comfort to the business and its customization techniques.

Top Ways Businesses Use AI To Tweak Customer Experience

Following are the top 8 utilities that Artificial Intelligence provides to boost customer experience –

1. Personalization

Businesses can easily gain a clear picture of their customer preferences and requirements by using AI and ML technologies which acquire and analyzes social, factual, and behavioral data. AI is built to predict client behavior by regularly surveying and improving the data it collects. This facilitates companies to analyze customer demographics and personal preferences. This, in turn, highlights the relevant products and resources during the browsing process.

2. Chatbots

A chatbot is a conversational AI using machine learning and natural language processing. It is automated and programmed to pretend to be human and carry out programming tasks based on specific triggers. Its unique ability is to conveniently and efficiently generate conversations between two people.

The most commonly found type of chatbot is a “question-answer bot” —this form of chatbot refrains from using advanced artificial intelligence but instead accesses a smaller knowledge base and utilizes pattern recognition.

Artificial Intelligence powered Chatbots make a business’s presence accomplished by allowing customers to find what they are looking for while simultaneously delivering a seamless experience.

Did You Know: 35% of customers want to see chatbots being used more often to improve communication and offer a better experience overall.

The best examples of Chatbots are – Apple’s Siri, Amazon’s Alexa, and Google Assistant.

Using simple rules and past interactions, bots provide insightful replies to any query, making their responses accurate, short, and creative.

3. Predictive Analysis

Predictive analytics, by definition, is to use data collected to predict a business’s future. It utilizes statistical algorithms blended with internal and external data to foresee future trends, ultimately enabling businesses to optimize inventory, enhance delivery times, boost sales, and reduce operational costs. A more accurate and punctual prediction occurs when Artificial Intelligence is added to the mix. Predictive analytics can be used by advanced analytics tools and machine learning models across any industry or business function.

4. Voice Recognition

The voice recognition model functions purely with the aid of AI to

• analyze the user’s voice and language,
• learn the words spoken,
• and then bring forth outputs with transcription accuracy as text data on a screen or model content.

With the help of this technology, devices can interact and respond to human questions in uncannily natural language.

With the ability to understand and converse with human language, Voice AI has opened up great opportunities for businesses to serve their customers better. It efficiently speeds up processes, increases productivity, and scales operations.

Approximately 55% of virtual assistant users prefer speech recognition apps be they proffer a complete hands-off operation of devices.

Examples of businesses that integrated AI for voice recognition and have successfully replaced touch-screen devices are – Amazon Echo, Siri, Google Assistant, Google Home, Amazon Alexa, and a few others.

5. Sentiment Analysis

A sentiment analysis system collects specific customer feedback and uses it to improve company products and services. When AI technologies are fused with this system, it can identify objects or situations that customers feel any negative emotions towards as expressed in text. AI understands the undertone of a statement rather than simply noting a negative or positive connotation.

Sentiment Analysis is majorly utilized by marketers to better understand their consumers’ sentiments, beliefs, and motives perfectly to make advertising to specific groups effective. It has a wide array of benefits ranging from patient insights and online reputation management to competitor analysis and product development.

Almost all social media platforms use Sentiment Analytics powered by AI. This way brands and companies can keep track of the content being shared and censor or filter content that could evoke negative emotions and cause problems.

6. Customer Journey Mapping

A customer journey map as the name suggests, is essentially the visual representation of the customer’s journey from brand discovery to purchase and post-purchase. It enables businesses to retrace a customer’s footsteps and see where their services might need any improvements or upgrades.

All through this journey, AI and Machine Learning play a vital role in ensuring a headache-free shopping experience. There are three essential stages to customer shopping: the Pre-Purchase, purchase, and post-purchase. With the assistance of AI and ML, customers thread these maps and help brands analyze and prioritize activities that impact customers, boosting internal collaboration and coordination.

The benefits of creating a customer journey map are that it helps:

• streamline the customer experience,
• optimize customer service costs,
• accelerate proactive sales solutions to customer problems, and lastly, boost customer retention rate.

Examples of businesses using customer journey mapping are – Home Depot, JPMorgan Chase, Starbucks, and Nike.

7. Fraud Detection

Fraud detection is another surprising area that AI has a distinguished hold over. AI can work with internal security to help organizations improve and protect corporate activities. Businesses can use AI to examine large quantities of exchanges and unravel misrepresentation patterns.

In the case of online fraud detection and prevention, machine learning consists of a collection of AI algorithms that are specially trained with the company’s data to suggest risk rules. The business owner can then enforce the rules to block or allow certain user actions, such as suspicious logins, identity theft, or sketchy transactions.

When fraud detection is handed over to AI and Machine Learning, businesses reap great benefits like – faster and more effective detection, reduced manual review time, faster predictions with bigger databases, and cost-effective solutions.

8. Personal Data Protection

AI and Data Protection are like two sides of the same coin; both are very important, and one cannot progress without the other. We all see and know that AI technology is advancing rapidly; it raises important questions about the use of personal data and the protection and storage of said data in AI systems.

AI is frequently used to minimize the risk of privacy breaches by encrypting personal data and detecting potential cybercrime incidents. It is, therefore, pivotal for businesses to maintain a balance between technological advancements and artificial intelligence with respect for data protection rules and guidelines.

The main benefit of Data Protection Artificial Intelligence is the elimination of human errors and its keen sense for spotting new trends and patterns.

Amazon, Apple, Facebook, IBM, Microsoft, and many other grandiose organizations have implemented this system, and many more are predicted to follow.

Read more: How AI and ML are reshaping customer experience.

AI In Action – Use Cases

AI has been implemented in virtually every facet of our lives and in every industry imaginable. Here are 3 Use Cases that will give you a gist of how they can be applied successfully.

1. Chatbots Creating Engaging Learning Experiences

Learning experiences become unique and personalized when the right assistance is provided at each stage of learning. That’s where leading educational institutions are now deploying Automated Intelligence-driven ecosystems to facilitate students to interact with AI-enabled Teaching Assistants (AiTA). The system, when tightly integrated with other Teaching Assistant Bots, enables improved interaction, easy instructor-led training, and enhnaces student-instructor relationship.

2. Simplifying Claims Management for Legal Firms

A typical compensation claims processing takes up to three years for case settlement costing an average of $85000. It’s often challenging for legal firms to balance time, money, and the cases in hand. That’s why they are now implementing AI and machine learning to improve performance efficiency. Utilizing AI and machine learning to settle claims can help legal firms reduce costs up to 57%.

3. Netflix Gets You!

Netflix is the largest streaming platform, with more than 200 million customers globally. It gained a majority of its popularity due to its personalization feature. This streaming service uses AI to create a personalized home screen interface for individual subscribers and accounts. When viewers create a new account, they are directed to pick a few of their favorite TV series and movies. The AI at the crux of Netflix analyzes the data fed to it and provides recommendations similar to the favorites picked by the user. It continues to customize the suggestions displayed based on what the user watches.

4. Rolls-Royce Rolls Out Smart, Responsible Manufacturing

To exemplify the impact of AI on Predictive Analytics, we can look at Rolls-Royce, one of the world’s largest manufacturers of aircraft engines. It deployed predictive analytics to help drastically reduce the amount of carbon produced in its engine’s product while simultaneously optimizing maintenance to assist clients and keep their planes flying longer.

5. Ask Julie!

“Ask Julie” is Amtrak’s virtual assistant. Amtrak, the national passenger railroad company of the United States has implemented this chatbot to the best advantage. Ask Julie has successfully helped provide Amtrak provide a seamless customer experience to “over 375,000 customers on their website each day and over 30 million passengers on over 300 trains each year.” The result – an 8X return on investment, more effective customer services. and reduced email costs.

Finding The Right AI Partner – A Few Tips

Digitalizing a business can be very daunting, especially when you want to integrate Artificial Intelligence into its core. Finding a partner who understands you and can communicate well with you is quite hard to find, but you must not give up hope! Keep looking because it is better to spend a little more at the start and have a quality setup rather than spend less and have a wobbly foundation that could jeopardize your whole AI implementation. Here are a few tips to keep in mind while looking for a capable AI partner –

1. Priorities

When looking for your potential AI partners, choose someone who can help the business and its employees prioritize and manage workloads.

2. Comprehend The Difference Between Machine Learning And Artificial Intelligence

Although the two may sound like they perform the same functions, do not be fooled. They each have their own region of expertise so look for someone who acknowledges that.

3. Invest In The Right Tools

In the current economy, businesses can not afford to splurge money on luxuries. Pick a partner who understands your company’s budget and can plan a perfect setup for you.

How Fingent Can Help Seamlessly Leverage AI For Customer Experience 

Artificial Intelligence is a wide ocean of opportunities, if you have the right swimming gear, you can glide on its surface. Making the right decisions and trusting the right people with your projects should not be taken lightly. Fingent is committed to providing impactful software solutions to meet business goals seamlessly. Our certified experts focus on client-centered transparency and offer complete services with a wide range of Artificial Intelligence capabilities. Our team can boost your business to be more efficient and robust through intelligent technology. We have nearly two decades of experience and completely understand our client’s needs and requirements. Give us a call and let us know how we can help you.

The automobile industry is one of the largest sectors in the world. In just the U.S., the car & automobile manufacturing industry boasts a market size of $104.1 billion.

However, even an ecosystem as large as the automotive industry is not immune to the unprecedented challenges over the last few years. The coronavirus pandemic and subsequent semiconductor chip shortage forced manufacturers to cut 11.3 million vehicles from production in 2021.

In addition to supply chain challenges, automotive manufacturers have contended with labor shortages, shifts in consumer demand, and pressures to create a sustainable work environment.

But, like any resilient industry, the automotive sector has leaned into these new challenges and has begun to address them proactively. Let’s take a closer look at what these hurdles entail and, more importantly, how automotive businesses overcome them via technology’s strategic implementation.

Challenges and Trends Reshaping the Automotive Industry

While many challenges and trends prompt the automotive industry to evolve, three stand out above the rest. These roadblocks include:

1. Ongoing Worker Shortages

Like many other business verticals, the automotive industry has been plagued by worker shortages. Manufacturers need help to fill vacancies at every level of the organization, including line-level staff, decision-makers, and engineers.

This worker shortage has made it nearly impossible to rebuild supply and catch up to runaway consumer demand for new vehicles.

2. Supply Chain Disruptions

Various legs of the automotive supply chain have faced disruptions over the last few years. Of these, the shortfall of semiconductor chips had the most significant impact on production and vehicle inventory.

Unfortunately, many experts predict the shortage will continue well into 2023, if not beyond. It is too late for automakers to prepare for this extended chip shortage. All they can do now is adjust manufacturing strategies to align with consumer demand and cut back production on less popular vehicles.

3. The EV Revolution

Despite these other concerns, the electric vehicle (EV) market continues to grow. By Q4 of 2022, EV sales represented 5.6% of all auto transactions. This percentage doubled from the year prior when EV sales made up just 2.7% of the total auto market.

This statistic demonstrates that consumers are becoming more environmentally conscious and are interested in decreasing their impact on natural resources. Government incentives and tax credits are further contributing to the surging popularity of electric vehicles.

But what does all this have to do with the future of work in the automotive industry? It means that automakers will need to implement new and more sophisticated production processes and hire better talent if they hope to push the envelope in the EV space.

The New Industry Focus: Creating a Sustainable Work Environment 

One of the biggest drivers of change in the automotive industry is a global push toward creating a sustainable work environment.

Historically, the automotive sector has been anything but sustainable. Traditional assembly line-based production strategies focus on efficiency at the expense of almost anything else. These tactics result in the consumption of excessive amounts of power and often produce an unnecessary amount of resource waste.

However, the next-generation automotive industry will likely be unrecognizable to the pioneers of the last century. Modern manufacturers are reimagining every aspect of the supply chain, from material sourcing to assembly and distribution. Visionaries and thought leaders are also encouraging a shift away from old-school engineering and development processes in favor of AI-powered practices prioritizing efficiency.

Even the retail sales aspect of the automotive industry is changing. Many dealers are shifting toward online transactions, and some are transitioning increasingly to a made-to-order sales model. The end result is a more agile and less wasteful automotive supply chain.

Technologies that Can Fuel the Auto Sector’s Metamorphosis 

The future of work in the automotive industry will focus on sustainability, resilience, and agility while prioritizing efficiency. To realize their aspirations of a sustainable work environment,

industry executives, managers, and workers must embrace leading-edge technologies, including:

1. Predictive Analytics Software

Predictive analytics software will influence numerous aspects of the automotive industry. Organizations interested in forging sustainable work environments can use these analytics tools to identify production waste and increase operational efficiency. Additionally, they can leverage these solutions to create more energy-efficient vehicles that produce fewer greenhouse gasses.

Predictive analytics technologies will also assist with demand forecasting — organizational leaders can use these insights to prioritize in-demand vehicles as they contend with ongoing chip shortages.

2. Automation Tools

Automation tools will prove invaluable amid labor and talent shortages. Businesses in the automotive industry can use automation software to streamline redundant back-office processes and improve communication across the entire supply chain.

Manufacturers can also use automation tools to ramp up production while conserving energy and reducing waste.

3. Machine Learning and AI Solutions 

Machine learning and artificial intelligence technologies can transform every link in the automotive industry supply chain. Businesses can use these complementary technologies to optimize raw material sourcing, vehicle distribution, and production.

Because they allow for a more data-driven approach to manufacturing and sales, these technologies can reduce waste while simultaneously creating more agile and resilient supply chains. In turn, this will help keep the costs of vehicles manageable, thereby increasing accessibility to energy-efficient automobiles and EVs.

Read more: AI and ML for Faster and Accurate Project Cost Estimation

Accelerate Your Transformation with Fingent

When your business is in the automotive industry, creating a sustainable work environment should be one of your top priorities. Doing so will help you attract and retain top talent, meet consumer demand for more efficient vehicles, and align your business model with the latest regulations and compliance frameworks.

To achieve these goals, you will need access to purpose-built technologies designed for your business’s unique needs. That’s where Fingent top custom software development company, can help.

Our development experts can create dynamic software for your business. From customer-facing applications to internal solutions that empower your staff to be more productive, we build the software you need to thrive.

To learn more about our wide range of technology development services, connect with Fingent today.

How the insurance industry delivers service has evolved significantly in the last decade.

Regardless of what form of insurance sales or policy management your organization is engaged in, you can attest that face-to-face interactions are no longer routine and are, in fact, an oddity.

As the insurance industry’s new normal, more and more interactions between customers, industry experts, other organizations, and adjustments claims occur digitally. Though phone-based communications will continue to be a part of the customer service process for the foreseeable future, customers, care providers, other insurers, and virtually anyone else with whom an insurance company interacts have come to expect a largely digitized experience.

For any organization to thrive in the insurance industry of tomorrow, it must take steps to evolve its processes today. That means creating a cohesive modernization strategy and investing in leading-edge technology solutions.

Read more: Answering the Burning Questions of Business Leaders on Digital Transformation!

Top Challenges Facing the Insurance Industry

To understand what a modernized strategy looks like in the insurance industry, it’s vital to examine some of the top challenges businesses will face in the coming years.

1. Staffing Shortages

Historically, the insurance sector has contended with turnover rates somewhere in the range of 8-9%, according to Insurance Business America, but that span climbed to 12-15% by September 2022.

That additional turnover significantly impacts business continuity and diminishes the customer experience. It can also negatively influence insurers’ ability to replace members of leadership that are retiring or stepping away from the industry.

2. Skyrocketing Costs

Inflation and numerous other factors have contributed to rising costs of everything from healthcare to vehicles higher than ever before. Naturally, some of these cost increases are passed onto insurers and their customers, so insurance companies must find ways to absorb some of these expenses while mitigating rate increases for their clients.

Insurers should also explore ways to reduce their operating costs to keep coverage prices lower. Otherwise, businesses may find it challenging to retain customer accounts, particularly in sectors like automotive insurance, where consumers can freely shop around and change policies in six-month intervals.

3. Antiquated Legacy Systems

Some legacy systems hinder the ability of many businesses to embrace digital transformation. These aging platforms can make it challenging to comply with relevant regulatory requirements and increase an organization’s overall operating costs.

The longer that insurance companies cling to antiquated systems, the harder it will be for them to streamline traditionally tedious practices, such as claim management. Therefore, insurance companies must replace these inefficient, disjointed platforms with modern, unified alternatives.

The Role of Digital Transformation in Solving These Challenges

Digital transformation can bring modern technologies to any business process to improve its operation. Fast-growing digital transformation technologies include machine learning, artificial intelligence (like ChatGPT), customer relationship management platforms, and intelligent document processing software.

Digital transformation holds the key to solving the insurance industry’s most significant problems, and it appears that many in the industry realize this, as recent projections estimate that insurance technology spending will increase by 25% between 2022 and 2026 in the US and UK.

A cohesive digital transformation strategy will lay out a roadmap for replacing aging technologies with modern alternatives, and once these technologies have been replaced, the cost savings are almost immediate.

In one example of how a digital transformation strategy led to practical innovation, Fingent joined forces with the California law firm of Sapra & Navarra, LLP to develop Ambit, an AI and ML program that simplifies and enhances the management of workers’ compensation claims. Claims may include hundreds of pages consisting of a variety of letters, affidavits, forms, and other documents from claimants, doctors, lawyers, investigators, employers, and witnesses, among others. Utilizing both artificial intelligence and machine learning, the Ambit system streamlines the claims management process, reducing claim costs, and helps break the old practices of:

• Taking too long to assess claims
• Treating similar claims inconsistently
• Not equipping claim adjusters with modern tools

Instead, Ambit improves the efficiency of all parties — insurance carriers, self-insured companies, lawyers, and claim adjusters — while reducing costs for insurers by 57%.

The Ambit solution was designed to:

• Easily ingest the many documents in the claims process
• Quickly identify missing, processed & corrupted pages
• Review structured and unstructured documents automatically
• Identify areas of concern
• Suggest potential legal defenses
• Automate calculations and reminders for important legal deadlines
• Generate case summaries, with action plans

These automation capabilities not only make life easier for claims managers but enable organizational leaders to offset productivity issues created by ongoing labor shortages by reducing onboarding time for new hires. These capabilities result in more uniform handling of the claims while speeding their resolution and lowering their overall costs.

In general, automation technologies, such as those implemented during a digital transformation initiative, will also decrease operating costs, enabling insurance companies to increase their profitability and offer their customers more competitive premiums.

Read more: How AI Drives Digital Transformation In The Insurance Industry

The Essential Components of Digital Transformation

The technology trend in insurance is clearly moving from the strictly paper-based methods of the past to the digital. Beyond static websites to mobile apps. Beyond email to text and chat. Beyond processes driven by people to more and more intelligent automation that speeds up and uniformly handles all kinds of processes from marketing, and operations, to customer service.

Every organization’s digital transformation roadmap should be as unique as the business itself, but every digital transformation strategy must include a few core elements:

• Clear objectives
• An integrated plan
• A leadership-driven approach
• Investments in the right technology

When creating your organization’s digital transformation strategy, you should start by defining your “why.” In other words, you must identify the reasons you are undertaking this initiative in the first place.

From there, work with a digital transformation partner who can help you create an integrated plan that includes everyone from executive members to line-level employees.

Digital transformation efforts — even small ones — require the active support of top management. Change is the hardest thing to achieve in the organization and without the sponsorship of the corporate leaders, the effort is unlikely to succeed.

Finally, you will need to replace outdated, inefficient technology with modern, robust solutions. When appropriate,

partner with a custom software development firm that can provide you with a purpose-built solution you need for your business. They are equipped with the personnel and experience to generate a solution in the minimum timeframe and without the need to increase in-house headcounts.

If your organization has been exploring ways to improve the customer service experience, increase productivity, improve profitability, and streamline its operations, it is more than ready to embrace digital transformation.

Successfully facilitating digital transformation requires a cohesive strategy, some cutting-edge technologies, a commitment to doing things better, and the right development approach.

Read more: Digital Twin Improving Predictability and Risk Management in Insurance!

How Fingent Can Accelerate Your Process

Naturally, the cornerstone of any digital transformation initiative is technology choices. These may be an off-the-shelf system for standard processes, the integration of existing systems or, your transformation may demand a custom solution that can accommodate your business needs unlike systems available to anyone else.

At Fingent, we specialize in creating resilient custom software solutions that are able to change and adapt according to your requirements. We work with insurance industry clients to help them streamline mission-critical business processes, and – as in all our projects – we accomplish this by providing dynamic, unique software that incorporates the most appropriate technology, such as the latest in machine learning and artificial intelligence technologies.

Connect with Fingent today to accelerate your digital transformation with the help of an experienced software development partner.

No longer the stuff of science fiction, artificial intelligence (AI) and machine learning (ML) are revolutionizing the way customers interact with brands. Businesses that have embraced these technologies can reshape the customer experience, curate one-of-a-kind buyer journeys, and strengthen bonds with their target audiences.

As your organization works to remain competitive in the modern business ecosystem, it must tap into the power of AI and ML technologies to provide a superior customer experience.

How Are AI and ML Enhancing Customer Experience?

Artificial intelligence and machine learning solutions can profoundly impact every facet of the customer experience. By leveraging these technologies, your business can:

1. Facilitate Hyper-Personalization

Customers who interact with your brand are looking for a personalized experience. As such, brands that put their products and services at the center of attention instead of prioritizing experience will miss the mark. Likewise, blasting your customers with generic advertising content or sending them broad, basic messages simply won’t cut it anymore. Instead, you must personalize every interaction to deliver timely and relevant content to each user.

Artificial intelligence and machine learning technologies facilitate a level of hyper-personalization that was thought to be unachievable just a few years ago. In a 2022 Salesforce survey, 88% of consumers reported that an experience provided by a company is almost as important as the product. Using AI and ML technologies, you can personalize customer experiences by utilizing real-time data, like their browsing history, purchasing habits, etc.

Artificial intelligence and machine learning solutions can also eliminate friction from the customer journey. For instance, AI- and ML-powered chatbots can leverage information from past interactions to create personalized messages for each consumer. This will minimize customer frustration by reducing how often consumers are asked to repeat information they have previously provided.

2. Allow Customers to Stay Connected 24/7

Customers expect access to timely and relevant support around the clock. However, staffing your customer support department 24/7 is financially infeasible. So how do you bridge the gap between customer expectations and the fiscal limitations of your business? AI and ML solutions are the clear answer.

With artificial intelligence and machine learning technologies, you can provide your customers with access to automated support like chatbots. These bots can respond immediately to customers and resolve many basic product- or service-related issues without tying up your customer support staff. This capability will not only allow you to reduce the workload on your team but also help you provide more timely and omnichannel service to customers, no matter when they reach out for assistance.

3. Conduct Predictive Behavior Analyses

The sooner you can identify consumer behavior trends, the better your chances of capitalizing on emerging opportunities. Unfortunately, traditional analytics solutions do not facilitate real-time decision-making because they often rely on data that is days (or even weeks) old.

The good news is that artificial intelligence and machine learning technologies enable you to conduct predictive behavioral analyses using real-time data, guiding your decision-making processes and enabling you to adapt to emerging trends like never before.

4. Enhance Your Understanding of Target Audiences

Artificial intelligence and machine learning technologies allow you to step into your target audience’s mind. You can use these newfound insights to guide your digital marketing strategies, refine products and services, and enhance the customer experience.

Due to how AI and ML learn and evolve, these technologies will only become more effective over time as they get access to more data, better helping you anticipate how your target audiences are likely to behave in the future. This enables you to proactively eliminate friction points from the buyer’s journey and paves the way for increased sales and better profitability.

Read more: Is AI-powered mobile app what you need for your business now?

Use Cases: Major Industries that Have Embraced AI and ML

Artificial intelligence and machine learning technologies are going mainstream, and many industries are taking advantage of these powerful tools for both B2C and B2B interactions. Business leaders in these sectors understand that these technologies will significantly impact their organizations’ ability to compete, both now and in the future.

Some of the industries that are using AI and ML technologies on a broad scale include:

• Software development
• Language processing and transcription
• Retail
• Customer service
• Marketing
• Manufacturing
• Finance
• Agriculture
• Logistics and transportation
• Healthcare

The healthcare and logistics sectors were some of the earliest adopters of artificial intelligence and machine learning technologies, whether by predicting the likelihood of patients developing certain diseases or by providing customers with more accurate shipping estimates. These industries (and every other on this list) utilize AI and ML technologies to enhance the customer experience.

These technologies also provide meaningful insights into the efficiency of business operations. Organizational leaders can use the information gleaned from these technologies to proactively address critical organizational growth hurdles and promote business continuity.

How Your Business Can Optimize Customer Experience with AI and ML

Artificial intelligence and machine learning technologies will empower your business to revolutionize the customer experience along every meaningful touchpoint. First and foremost, these technologies will help your business truly understand the customer journey and its impact on organizational profitability. And once you understand the state of your business and how well it is currently managing the customer experience, you can begin using your AI and ML tools to refine the customer experience.

If you want to maximize your return on investment, consider incorporating artificial intelligence and machine learning technologies into as many business processes as possible. You can use these solutions to automate redundant processes, hyper-personalize advertising content, and refine the customer experience from top to bottom.

Read more: Use cases and business benefits of deploying Machine Learning!

Tap into the Power of AI and ML with Fingent 

Are you ready to harness the power of artificial intelligence and machine learning so that you can provide your clients with the experience they deserve? If so, then it is time to explore a partnership with Fingent.

At Fingent top custom software development company, we provide customized artificial intelligence applications and machine learning solutions. Cumulatively, these technologies will differentiate your brand in the competitive digital marketplace and enable you to modernize the customer experience.

To learn more about Fingent’s suite of services and solutions, contact our team today. Together, we can reshape your customer experience and set the stage for the growth of your business.

We currently live in the eon of Artificial Intelligence. Whether we like to admit it or not, AI has suffused its way into every industry in all of its beautiful ingenuity.

Did You Know?

“The global artificial intelligence market size was valued at USD 93.5 billion in 2021.” – Grand View Research

“AI could contribute up to $15.7 trillion1 to the global economy in 2030.” – Sizing the Prize, PwC Report

What is Artificial Intelligence? 

Artificial intelligence (AI) is a simulation of human intelligence processed by electronic gadgets that enables the execution of an array of advanced functions, like seeing, understanding, and translating spoken and written language, data analysis, and many more.

From robots that can navigate a warehouse by themselves to virtual assistants that understand what people are saying and act upon that information, we can see Artificial Intelligence in play everywhere.

Read more: Reimagine Your Business with AI. Here’s How!

Artificial Intelligence-Based Code Generation Tools 

Let’s take a look at code-generation tools that are based on AI technologies. This article will discuss three such tools – Codex, Co-pilot, and ChatGPT.

1. Codex

As announced by the Artificial Intelligence Research Company OpenAI, the Codex model series is a successor of the GPT-3 series and is trained with both natural language and billions of lines of code. It is most competent in Python and is proficient in many more languages, including C#, JavaScript, Ruby, Swift, TypeScript, SQL, and even Shell.

Due to its understanding of many languages, Codex can transcribe simple commands in natural language and execute them according to the user’s preference. This makes building a natural language interface into existing applications possible. It also helps speed up the work of professional programmers and helps amateurs get started with coding.

2. Copilot 

GitHub Copilot, fabricated by GitHub and OpenAI, is a cloud-based AI tool that assists users of Visual Studio Code, Visual Studio, Neovim, and JetBrains integrated development environments (IDEs) with auto-completing code.

GitHub Copilot is trained on billions of lines of code and uses this knowledge to turn natural language prompts into deft coding suggestions. It is famous for evaluating and suggesting improvements for social media profiles, facilitating online presence across various digital channels.

Copilot uses AI technology to engage with potential leads through messages and categorizes them based on responses. It is trending with a whopping 4.67-star rating and is widely praised for its enormous support.

3. ChatGPT

OpenAI released yet another ingenious model called ChatGPT. It is a long-form question-answering AI that addresses complex questions conversationally. This is a revolutionary technology because it not only understands human language but is also trained to learn what humans mean when they ask a question.

The New York Times headlined, “ChatGPT and other chatbots is a ‘code red’ for Google search engine.”

While The Indian Express, in an article, stated that “When it was introduced, ChatGPT’s ability to break down complex problems and explain everything in a human-like manner led many to proclaim that Google’s days as the numero uno search engine are numbered.”

ChatGPT is undeniably a hot topic, and its reasons stand strong. Its dialogue format makes it possible to provide answers to any follow-up questions, accept its mistakes, challenge incorrect premises, and reject inappropriate requests.

Its specifically trained ability to understand the human intent behind every question and provide helpful, harmless answers while discarding parts of the question that do not make sense only adds to its special nature.

Read more: Is AI-powered Mobile App What  Your Business Needs Now?

Benefits Of These AI Tools

1. Codex –

“You just ask the computer to do something, and it just does it,” said OpenAI CTO Greg Brockman in the video demo of Codex.

Codex is good at co-referencing resolutions. It also links nouns in the prompt/input to their proper variables and functions in the code. Codex can also execute mundane tasks, like rendering web pages, launching web servers, and sending emails.

As AI technology takes over all the tedious parts, the programming process is prone to become more efficient. OpenAI shows Codex has a 37% accuracy rate in effectuating coding tasks.

2. Copilot –

A new study by GitHub revealed that Copilot works as an AI code programming assistant, significantly increasing developer productivity and happiness.

This particular AI-based code generation tool stands out because of its simplicity. You can describe the task you desire, outcome, or suggestion in the comments, and Copilot can come up with what it thinks are the proper lines of code. On the other hand, you can infer just your intentions with an incomplete prompt, and Co-pilot will do the code generation according to the same prompts.

3. ChatGPT –

Firstly, it reflects its efficiency by handling large volumes of conversation without needing breaks, which is undoubtedly helpful for customer service or other applications with a high demand for conversation. It also personalizes these conversations allowing them to feel unique for different users.

Using ChatGPT is highly cost-effective because it eradicates the need to hire human employees to handle conversation tasks. It is also available 24 hours a day throughout the week and has a great language support system.

How It Enables Reduced Costs 

Embracing Artificial Intelligence is a deft, cost-effective decision that most businesses and industries need to make. AI helps companies progress on many fronts, but the most imperative is its impact on the company’s pocket.

Implementing AI-based code generation tools such as Codex, Copilot, and ChatGPT reduces the need to hire miscellaneous employees to perform repetitive, tedious tasks. This, in turn, reduces the chances of any mishaps that may cost the company money to fix. Using these tools as assistants also greatly helps employees with their workload.

Using a more personalized, accurate, and compactable AI technology in your business can attract many potential clients and customers. This ultimately creates a profit for your business while also helping you establish your roots in the industry.

35% of consumers feel the desire to see more companies using chatbots. This is the perfect time to build the software you “ever needed” at a reduced cost.

Read more: Artificial Intelligence and Machine Learning for Faster and Accurate Project Cost Estimation

Myths Around The Use Of AI Tools 

The long-standing fear of technology taking over mankind has always had its chokehold on innovation. It is time to debunk the myths that surround AI and let technology progress.

Myth #1 – AI Is Going To Take Over Every Job Sector

One thing to remember is that no matter what, Artificial Intelligence tools will not replace the developers but increase developer productivity. It is reasonable to believe that AI has the potential to disrupt labor, but to compare labor from humans to machines directly is an unnecessary simplification. AI tools exist solely to enable humans to work in a newer and smarter way.

Myth #2 – AI Is Magic

The idea that AI tools can magically make sense of any and all of your messy data is completely erroneous. AI does not work on the principle of “load and go,” and the quality of input data is more important than the AI algorithm. This implies that the data being prompted has to be relevant to the problem being solved and specific to a set of use cases and a domain of knowledge.

What The Future Holds For The Industry With AI Tools

AI has consistently altered the course of the world multiple times and will continue to do so in the future. Although it is not a mainstream technology, billions of dollars are spent annually on AI research and development.

Did You Know?

As of the latest 2022 data, the global AI market is worth $136.6 billion. By 2030, the global AI market is expected to reach $1.81 trillion.

Some other industries that are largely affected by AI tools include –

• Software Development Companies
• Information Technology
• Finance
• Manufacturing
• Customer Service
• Education

Get Future-Ready With The Best of AI 

Using AI-based code generation tools can give you the upper hand you have been waiting for. Unlock your business’s potential with Fingent, the top custom software development company. Get in touch with our experts for a power boost and to get ahead of the competition.

The strategic significance of advanced technologies as a critical business component is recognized by enterprises like never before. Besides business modernization and cost reduction, advanced technologies allow you to compensate for labor shortages, improve brand value and competency, and expedite research and innovation processes. However, several companies jump onto the bandwagon without properly understanding the practical applications and benefits of advanced technologies. The World Economic Forum indicates that only 23% of small and medium-sized enterprises (SMEs) worldwide can invest in and grow with new digital tools. This data proves why businesses should crucially analyze advanced technologies before adopting digital tools.

To streamline things, here’s a quick rundown of five advanced technologies we believe will help you cope with the new business and economic environment.

• Simplifying Workflows With Cloud
• Low-code Applications
• Robotic Process Automation (RPA)
• Document Data Extraction
• AI Assistants

As these technologies become more affordable and handy, businesses are ardently pursuing them to automate customer service, streamline workflows, differentiate products and services, and reach new markets. Depending on your budget, implementation timeline, priorities, and unique business requirements, our team at Fingent helps you build the roadmap for technology adoption.

Read more: How to gain maximum value from your technology investments?

Let’s take a closer look at the five inevitable technologies for business transformation today:

1. Simplifying Workflows with Cloud

Workflow management is a highly overlooked enterprise strategy that directly impacts productivity. Managing different stakeholders, heaps of confidential data, and a series of preset and conditional tasks manually can lead to several errors, such as employees missing key steps, policy violations, compliance issues, and monetary losses. By taking your workflows online, cloud-based workflow management applications increase your productivity.

Cloud-powered workflows or workflow management tools:

• Are scalable, centralized, customizable to your needs, easy to integrate, secure, reliable, and hassle-free.
• Offer a seamless and unified collaboration interface by preventing users from toggling between different messaging apps or communication channels.
• Reduce your dependency on the in-house IT team by passing on the software maintenance responsibilities to the third-party software vendor.
• Can be accessed via any authorized network (with approved access credentials), on any device, from anywhere, 24/7. This has been a huge game-changer for several companies that switched to remote operations during the pandemic.

Example of a Cloud-based Workflow Tool

Finding a cloud workflow management tool that can be customized to your company’s requirements is daunting. The platform should integrate well with your organizational processes without disrupting your workflow. This is where digital workplace applications like InfinCE make the difference.

With InfinCE Digital Workplace, Fingent has improved its productivity by 20% through real-time, effective, and easy collaboration. Data-powered dashboards, dedicated servers, collaboration apps, productivity tools, virtual desktops, private mobile apps, and a host of exceptional business management features enabled us to achieve a significant operational breakthrough in streamlining workflows.

Read the full case study here.

2. Low-code Applications

Gartner estimates that by 2025, 70% of enterprise applications will use low-code or no-code technologies. Digital business transformation requires pushing custom software solutions to the market at lightning speed. This demand has given rise to low-code applications that will break the technological and organizational silos of application development, automation, integration, and governance. Low-code development enables business users to bring innovative ideas to life by dragging and dropping low-code elements through a graphical user interface.

Simply put, low-code development enables “citizen” developers or non-tech users (such as business analysts or marketers) to build dashboards and survey or contact forms faster. On the other hand, professional developers can leverage low-code techniques to perform more efficient tasks, such as legacy application modernization or back-end integrations, with improved agility and velocity.

Use Cases for Low-code Applications

• Customer engagement applications and portals
• Mission-critical applications such as ERP software, payments manager, etc.
• Data analysis applications, BI dashboards, and data management software
• Mobile apps for customer engagement
• Order processing, inventory, order fulfillment, supply chain, and accounting apps

Salesforce Lightning, Microsoft Power Apps, and Zoho Creator are some of the leading low-code applications today. SAP users can leverage the unified low-code/no-code (LCNC) solutions on the SAP Business Technology Platform (BTP) to rapidly build and extend applications and automate tasks and processes.

Read more: Low Code/No Code Development with SAP BTP: How It Is Turning the Future of Enterprise Resilience

3. Robotic Process Automation (RPA)

Robotic Process Automation (RPA), often called software robotics, is an easy-to-use software technology that allows anyone to automate digital tasks within their business processes. RPA allows users to create software robots or “bots” to learn, emulate, and execute rules-based business processes. According to Forrester Research, RPA software revenue is expected to reach $6.5 billion by 2025, while RPA-related services revenue could hit $16 billion in the same year.

Potential Use Cases for RPA 

We offer free proof of concepts to help you understand how RPA can improve your business efficiency and customer experience. Some of our top use cases include:

• Automating discharge protocols and data management to increase HR productivity in healthcare.
• Daily retail processes automation, such as order processing, inventory and warehouse management, etc., to save time and resources.
• Reducing customer wait times through RPA-enabled chatbots that answer customer queries in real time.
• Error-free, automated billing and invoices to keep your financial systems and reports up-to-date.
• HR teams can automate personnel data and records maintenance, streamline onboarding, and seamlessly manage payroll.

4. Document Data Extraction

Extracting quality data from unstructured or poorly structured data sources and documents for further processing, migration, and storing has been the biggest obstacle in automating back-office operations. If you enter structured invoices into a robust ERP tool like SAP, your payments can be automated, and system records can be generated automatically. Due to the high costs of data extraction, several businesses extract only critical information fields, for example, the payment field within an invoice. Businesses are compelled to manually extract data from other important fields, such as validating the invoice’s compliance with VAT.

AI-integrated OCR Software for Document Extraction

Optical Character Recognition (OCR) is an affordable, game-changing technology that automatically extracts data from the digital images (photos) of large files, scanned documents, and sub-titles or captions superimposed on an image. It reduces the time spent in manual data entry and extraction by automatically converting typed, handwritten, or printed text into machine-readable text. AI-powered automated data extraction tools like DocuSign, Docsumo, Kofax Capture, and Amazon Textract leverage OCR technology to reduce the chaos involved in document data extraction and enable businesses to create an efficient workplace.

Our team helps customize document data extraction software that can save you time and money by eliminating transcription and transposing mistakes.

5. AI Assistants

One of the most common examples of small business automation today is using AI-powered virtual assistants. They can save your employees’ productivity by automating the most repeatable customer interactions, such as technical support, appointment scheduling, lead qualification, and order management. AI virtual assistants like Google Assistant and Alexa can understand and act according to your voice commands and customize responses to your queries. Understanding customer intent through natural language processing and recognition allows AI assistants to maintain a human-like conversation.

Chatbots are a popular category of AI assistants designed specifically for text-based channels like SMS, email, and live chat. Recent years have witnessed a rise in chatbot adoption among several business verticals, product and service lines, websites, mobile apps, customer portals, etc. Data shows that 58% of B2B companies and 42% of B2C websites use chatbots to make their websites and mobile apps more interactive. More than 56% of businesses believe chatbots to be driving digital disruption in their industry.

Case Study: AI Virtual Assistant for HR     

Fingent’s HR team was pressed to transform their service delivery model as routine, transactional tasks affected their performance and efficiency. To solve their struggle, Fingent developed MUSA, an AI-powered virtual assistant (a chatbot), and integrated it with Fingent Hub, Fingent’s internal employee management system. MUSA is short for Multi Utility Assistant. Employees can ask MUSA any queries related to HR and IT DevOps processes at Fingent, and they’ll get answered instantly. MUSA has improved our HR team’s response time by minimizing their workload and allowing them to focus on areas requiring more attention.

Business and Technology Are Inseparable!

Gartner writes that businesses with technology employ advanced tech to boost customer experience and revenue growth, clearly understand their priorities, goals, and strategies, and invest in solutions tailored to their needs. Technology allows businesses to lower the walls within and between their organizations, customers, providers, suppliers, etc. Organizations perceiving technology as a key business consideration will be able to match the pace of business change and stay relevant and competitive.

How can your business embrace growth in a new era of transformation and technology trends?

If you’re getting caught in the technology maze, take a quick break to contact us. Our consultants can simplify your technology adoption strategy based on your priorities, customer needs, financial resources, and technical requirements.

Machine learning is changing the face of everyday life, science, and business. It is revolutionizing all industries, from advancing medicine to powering various cutting-edge technologies. Though Machine learning (ML) was a part of AI’s evolution until the 1970s, it evolved independently. It has become a chief response tool for cloud computing and eCommerce.

The goal of machine learning in business is to adapt to new data independently and make decisions and recommendations based on thousands of analyses. Machine learning enables systems to learn, identify patterns and make informed decisions with minimal human intervention.

Today, ML is a necessary aspect of modern business. It uses algorithms and neural network models to improve the performance of computer systems. Machine learning in business and manufacturing is enabling organizations to achieve notable strides. These strides include increased performance and efficiencies, improved processes, and enhanced security.

This article will discuss the benefits of machine learning in business and its use cases.

Remarkable Benefits of Machine Learning for Businesses 

According to Fortune Business Insights, the global market size for machine learning in business is expected to grow to USD 209.91 billion by 2029, exhibiting a CAGR of 38.8% during the forecast period. ML has been and continues to scale operations tremendously. Across industries, ML has led to a boom in affordable data storage and faster and more reliable computational processing.

Here are six remarkable benefits of machine learning in business:

1. Automation for better decision-making 

Most businesses find themselves wasting precious time sorting through duplicate and inaccurate data. Such businesses benefit from using the predictive modeling algorithms of ML in their processes. Such a process will understand duplicate inaccurate data and distinguish the anomalies. It enables the organization to avoid inaccurate reporting that can result in poor customer retention.

Instead, this will allow businesses to use their accurate database to detect wasted costs, missed opportunities for sales, and revenue capital. In addition, organizations can overcome challenges and risks that arise due to miscommunication or poor performance metrics. Thus, businesses can streamline their operations and improve decision-making which could be translated into better ROI.

2. Increased scalability with minimum expense

Semi-supervised machine learning algorithms can help organizations leverage useful insights from customer profiles and enable them to view their brands from customers’ perspectives. Doing so will equip organizations with relevant insights to build their brand by improving their products and services.

3. Predictive maintenance

Predictive maintenance that ML aids manufacturing firms’ power to follow best practices that lead to efficient and cost-effective operations. The historical and real-time data predict problems and stipulate strategies to solve those problems. Plus, workflow visualization tools can eliminate issues and unwanted expenses incurred due to those issues.

4. Financial analysis

ML can greatly assist as it gathers and analyzes large volumes of quantitative and accurate historical data. It is used for portfolio management, loan underwriting, fraud detection, and more.

5. Personalization 

Using machine learning in business will allow organizations to know their customers better and provide them with a more personalized customer experience. Organizations no longer need to rely on guesswork because ML models can process different types of information collected from numerous sources and provide relevant data about their customers.

6. Cybersecurity

ML technologies can improve cybersecurity to solve cyberattacks once and for all. Empowered by ML, intelligent security programs can gather and process data about cyber threats and respond to them in real time. ML models can detect the slightest deviations in patterns and flag them. Or destroy an attack in its nascent stage.

Read more: Can Machine Learning Predict And Prevent Fraudsters?

Top Use Cases

Machine Language has made its mark across industries and found a place in many different applications. Here are some top use cases:

1. Enhanced social media features 

Businesses can use machine learning algorithms to create attractive and effective social media features. For example, ML algorithms in Facebook enable it to identify and record a person’s activities. These activities include records of chats and the amount of time that person spends on each post. It uses this data to determine what kind of friends and topics may interest that person and accordingly make suggestions.

Read more: Why Time Series Forecasting Is A Crucial Part Of Machine Learning

2. Product recommendation

Product recommendation is an advanced application of machine learning techniques. It has been the most popular application of almost every eCommerce website today. This technique allows websites to track a consumer’s behavior based on their previous purchases, search patterns, and cart history. It enables the website to make apt product recommendations to that consumer.

3. Recognition

Image recognition is one of the most significant and notable ML and AI techniques. It is adopted further for pattern recognition, face detection, and face recognition.

4. Sentiment analysis

Sentiment analysis is a real-time ML application. It determines the emotion or opinion of the speaker or the writer. For example, a sentiment analyzer can detect the thought and tone of a written review or an email. It can analyze the review-based website, decision-making applications, and more.

5. Access control

Most large businesses are actively implementing ML models to determine the level of access an employee should be granted. This application of machine learning can ensure the security of the organization.

6. Bank Domain

Banks are using ML to prevent fraud and protect accounts from hackers. Machine learning algorithms determine what factors to consider in creating a filter to prevent an attack.

Read more: Machine Learning – Deciphering the most Disruptive Innovation

How Fingent Can Help with Deploying the Best of ML

Leveraging the capabilities of machine learning in business can open the door to many opportunities. It is wise for any organization to take advantage of ML rather than lag behind competitors. However, we understand if you have questions. That’s why Fingent software development experts are here to help you. We can deploy the best machine-learning models efficiently and smoothly.

As a partner, Fingent can work with your team as you take on digital initiatives for sustainable business growth. We enable our clients to make data-driven decisions by efficiently deploying machine learning in business. Our cost-effective services will save you a considerable amount of time and money.

Furthermore, we do not follow a one-size-fits-all strategy. We provide custom software development services that cater to your needs. Therefore, look no further if you are looking for a reliable, efficient IT partner to deploy the best machine-learning models.

Contact our experts today!

From the mundane to breathtaking, AI is disrupting virtually every business process in all sectors. People are ceasing to associate Artificial Intelligence with science-fiction dystopias as Artificial Intelligence (AI) is taking more commonplace in our daily lives.  While such acceptance in mainstream society is a new phenomenon, it is not a new concept in business. Today, AI has become imperative to maintain a competitive edge.

This guide will help business owners who are serious about maintaining a competitive edge in their business sector by adopting AI.

Rising Need for Adopting AI In Business

Did you know that 52% of companies accelerated their AI adoption plans after the pandemic? Why?

Artificial Intelligence in business is seen as a supporting tool. It is adept at processing and analyzing a trove of data much faster and more efficiently than a human brain can. Since AI can synthesize courses of action and present them to the human user, businesses can use AI to help investigate the probable consequences of each action. That way, businesses can streamline the decision-making process. This is what makes AI valuable throughout many industries.

Artificial Intelligence is a form of software that can make decisions independently. It can act even in situations not foreseen by programmers. AI has a wider latitude of decision-making capabilities than traditional software – whether it is simply helping visitors or performing a task as complex as monitoring a wind turbine to predict its maintenance.

Read more: Conversational AI: Reimagining Customer Experiences

How To Identify If Your Business Needs AI?

AI software and tools can make business processes much simpler and more effective. Besides, implementing AI in business ensures cybersecurity defense, powers customer service, and more. But how do you know when you must adopt AI in business? Here are a few scenarios:

Scenario 1: Do you need to enhance your customer experience? 

Are you struggling to provide your consumers with quick, easy, and personalized solutions? AI-powered digital assistants can help your business resolve customer queries by imitating human conversation. Chatbots are among the most promising trends in customer engagement and customer experience. Perhaps most business owners realize how imperative this AI technology is to their business. Perhaps that is why the chatbot market is set to reach 1.25 billion USD by 2025.

Scenario 2: You know the value of sentimental analysis but do not know how to leverage it.

Businesses use sentimental analysis to monitor and analyze customers’ opinions and emotions from various texts on a website, social media, and product or service comments. Skimming through large amounts of data to churn out customers’ sentiments can be daunting. All thanks to AI-assisted sentiment analysis, you can now quickly understand how your customers feel about your services or products.

Scenario 3: Your business has suffered due to inaccurate forecasting.

Accurate sales forecasting helps businesses predict future sales for long-term business growth. It can also enable the detection of potential problems to avoid them. Implementing AI-based CRM software can help detect how each data element relates to sales performance.

Scenario 4: You have a great online presence but an awful in-store experience.

If that describes your business, it is time to adopt AI to provide the next level of a personalized in-store experience. AI can enable instant access to products or services and contribute to smarter buying decisions.

A Quick Guide to Implementing AI For Your Business

AI applications can be used in many ways depending on organizational needs and the business intelligence (BI) insights derived from the data collected. Here are some tips to explain the steps businesses can take to ensure their implementation is a success:

1. Know your options.

Find out your options and what AI can and cannot do. This will help you decide if you want to add specific AI technology or change the entire app.

2. What is your business goal?

Working on an ‘end-first’ process will help refine the list to select specific features or capabilities that best suit your business goals.

3. Find out how AI can benefit the end-users

This is crucial as it gives you the two main objectives for a successful implementation. Then, choose the software and hardware you need to make this process a reality.

4. Evaluate your internal capabilities

You need to consider if you have enough skilled employees in-house who can manage the process and if you have the budget to outsource it.

5. Choose between building or integrating the system

Remember building an AI system from scratch can take several months. On the other hand, if you choose to use a premade system, your AI partner will help install the software app, train your staff, and fulfill your business needs.

6. Test system

Testing the system for a predetermined time will help you understand if the clients are more satisfied, and if the employees work more efficiently.

7. Choose the right partner 

A good AI partner will be clear about the offer, value, and terms of cooperation.

8. Make refinements

After you gather a reasonable amount of data evidencing the success of an AI solution, you can start making refinement changes to the solution.

Watch more: How Artificial Intelligence Can Enhance Your Customer Experience!

Avoid 4 Common Mistakes While Implementing AI

A well-considered plan can lead to success, but a mistake can cost you considerably in terms of time and resources. Here are four common mistakes to watch out for when implementing AI:

• Not applying AI to the right use cases: If AI is incongruous with your business goals, your time and resources will be wasted

• Not diligent in hiring the right talent: Hiring the right AI team is like putting together the right football team that can win. Hire candidates with specialized skill sets and experience that match your business needs.

• Ignoring data: Ensure all teams are responsible for organizing, vetting, and maintaining data.

• Inadequate intervention: Inadequate intervention could result in AI recommendations that hinder business objectives. Hence, ensure interventions are scalable and repeatable.

How Fingent Can Help You With Personalized AI Software Development 

Artificial Intelligence is for every future-oriented business. How exactly you will use AI depends on your business goal and how well it was implemented. At Fingent top custom software development company, the AI developers are equipped to design intelligent solutions to help solve your business problems, automate tasks, and improve customer experience.

Our suite of AI solutions includes data capture and processing. Our AI developers are also proficient in analytics, multi-platform integration, and ML solutions.

Let us help you reach your business goal with intelligent AI-driven solutions. Give us a call today.