The Benefits of Intelligent Data Capture

What is Intelligent Data Capture?  

Technically, Intelligent Data Capture (IDC) is an automated process that detects and extracts crucial data from incoming paper and electronic documents with no external intervention.  

In general terms, IDC avoids manual data entry with the use of technology. Intelligent data capture helps your organization to save time, money, and resources with no need to extract and organize data manually from your documents. This extracted data, when integrated with content management or business process automation software, can be used by organizations for digital routing and delivering significant documents.   

Intelligent data capture is mostly associated with automation. An automated solution is responsible for automating an entire task based on the requirements of your organization. It allows you to detect the gaps and identify the right solutions to fill them. To better understand the advantages of automated solutions in your organization, it is essential to get an idea about their working/functioning.  

How does Intelligent Data Capture function?  

When any kind of information reaches your business, it has to be properly captured, processed, and accessed in the right information system. Intelligent Data Capture (IDC) is the process of extracting information from any format like paper, email, or fax, whether it is a structured or unstructured document, and converting it to machine-readable digital format. Intelligent Data Capture solutions also help in sorting, extracting, and validating information automatically and sharing with digital workflows or ERP systems. 

IDC can also organize different types of documents you input such as an invoice and an order slip, then derive relevant details from each document, verify it, and then capture the data to your database and ERP software or any other system you choose. This is totally a different process from conventional OCR (Optical Character Recognition). Previous generations of intelligent data capture solutions had comparatively poor accuracy rates and needed significant investment for configuration.  

Intelligent data capture is very precise as well as simple to set up and arrange. Instead of spending too much time on configuration, the special self-learning capabilities of the Intelligent Data Capture tool enable you to submit a sample of the generally used document types. Because intelligent data capture is flexible enough to adapt to the needs of your organization. Invoice detection and data lifting, automated arrangement of data (automatically sorting different document types), and exporting to any accounting or business application line are some of the attractive features of intelligent data capture.  

Benefits of Intelligent Data Capture  

Intelligent data capture is mainly designed to avoid entering data manually from each incoming paper you receive, which consists of any invoice, bills, order slips, or any other type of document you use to finish your everyday task. This allows your organization to assign valuable tasks for your employees to focus on and reduce the number of people working in your organization instead of wasting hours on finishing manual data entry. Here are some of the major benefits of intelligent data capture:  

Reduce headcount and increase efficiency

Intelligent data capture reduces the number of human headcounts as it takes away the task of entering data manually from human laborers. This in turn increases the efficiency of the organization as the IDC tool takes care of the data entry part.   

24/7 Availability

Businesses that function globally have to be available for their customers irrespective of the time zones. Likewise, there are many industries like healthcare, hospitality, and shipping that need the availability of data at all times to maintain business efficiency. Intelligent data capturing ensures the availability of every data even during non-working hours and with no geographical barriers. 

Augmented security

Intelligent capture makes sure that content is redirected to the right directories as quickly as possible and that only those who have been given permission to access the content can access it. It also offers a more stable and rapid implementation of security procedures across all content, protecting from expensive data loss and security infringements.  

Simplified compliance

The content is linked to an audit trail by intelligent data capture that maintains compliance with government regulations and accurate retention of documents and other crucial data.  

Eliminate human errors

When human employees extract data, there are chances for mistakes. Even if an employee reads something incorrectly or misspells the data, the repercussions can be negative and huge. IDC reduces the risk to near zero.  

Reduce operational costs

All businesses incur operating expenses such as inventory, rent, salary, etc. Manual data maintenance requires huge costs along with the possibility of human error. Intelligent data capture helps in reducing additional costs and eliminating human errors by automatically updating the data wherever needed.  

Data storage and data security

Storing files and folders physically takes more space and can lead to damage of paper documents. Moreover, confidential papers must be kept separate with restricted access. Intelligent data capture removes all these restrictions and data is encrypted to protect data from unauthorized access. It consumes less disk space and there is a backup option to prevent data loss. 

Better customer experience

Customer experience is important for any business. Intelligent data capture ensures error-free and high-quality data to offer a better experience to customers according to their requirements. By ensuring good revenue, the business can deliver better offers, attract more clients, and improve customer satisfaction – all together with the help of IDC. 

Wrap up  

When it comes to high-volume, transactional business processes that rely on a variety of business documents, Businesses need an automation solution that can eliminate manual jobs that are inefficient and cost a lot of money such as document management and data entry, especially when it comes to many high-volume business processes that rely on various business documents. This is the exact point where intelligent data capture technology enters. Intelligent capture includes the application of machine learning and optical character recognition (OCR) technologies to convert print documents, electronic images, and other digital documents into sensible data.   

Artificial Intelligence in Manufacturing 

Behind every operation that takes place in the manufacturing industry, artificial intelligence plays a major role. AI has the ability to receive different types of data not just from people, but also from machines, sensors, etc., and use it with specifically designed algorithms in order to optimize operations. If we consider the use of artificial intelligence in manufacturing, AI offers multiple ways to improve industrial value. Machine Learning or ML is the most commonly used subset of AI in manufacturing. The process manufacturing industry is one of the highly combative industries with rapidly transforming markets and complex systems. Therefore, the process plants need every single benefit that AI and ML can offer to spur innovation and maximize profits. 

Let us go through this article to know more about the different applications of artificial intelligence in the manufacturing industry. 

Benefits of using AI in the Manufacturing Industry

Implementing Artificial Intelligence has many for the manufacturing industry.  Let us start with the key advantages or benefits AI offers in this area of operation: 

Faster decision making 

With the integration of IIOT (Industrial Internet of Things) with VR OR AR and cloud computing, companies will be able to share simulations, talk about production activities, and pass on live crucial or relevant information no matter wherever their location is. Moreover, the data collected from sensors and beacons help decide customer performance, enable businesses to foresee future requirements, make quick decisions on production, as well as accelerate transfers between manufacturers and suppliers. 

24/7 production  

The working hours of human employees are divided into 3 shifts to ensure smoothness and continuity in production. On the other hand, there are AI-induced robots that work 24/7 without any intervals or breaks. They are designed to enhance productivity and increase business while meeting the demands of customers around the world. 

Safe environment  

Human workers can make mistakes knowingly or unknowingly. Such mistakes may result in uncompromising errors or accidents in the organization. Though AI cannot eliminate the risk factors completely, it can at least minimize or reduce the intensity of errors. The availability of remote access controls eliminates the need for human interventions. Also, ultra-modern sensors allied with IIoT (Industrial Internet of Things) equipment assist in the efficient installation of defense and security guards. 

Opportunity for human employees  

As AI takes up the manual jobs done by human employees, it lifts the weight of time-consuming, tiring, and repetitive work from manual workers. Human employees now have the time to focus more on creative and challenging tasks that actually require their intelligence to drive the business in the right direction. 

Less operational cost  

It is true that setting up AI in industrial businesses requires a huge capital investment but the ROI (return on investment) you can expect from AI is significantly higher. Once intelligent machines start to deal with day-to-day operations, businesses will be able to save lots of functional costs. 

Use Cases of AI in the Manufacturing Industry

As we have discussed the benefits of AI in the manufacturing industry, let us move to its use cases. The use cases of artificial intelligence in manufacturing include: 

Predictive maintenance   

Analyzing sensor data allows manufacturers to detect possible errors and downtime, anticipate the time when machines stop working, and schedule repairs before errors occur. This results in increased efficiency because the functions do not have to be stopped, and minimizes the cost of repairing and replacing failed machines.  


As large amounts of data are produced in security logs due to the manufacturing industry environment, filtering doubtful ones during everyday operations is a big task. Artificial intelligence is capable of identifying fraud, infiltrators, malware, and more on its own, enabling it to deal with modern cybersecurity threats and challenges more rapidly and precisely than a human worker. 

Edge analytics  

Edge analytics gathers data from AI-driven devices and sensors, thus providing decentralized and quick statistics from those datasets. The data gathered by Edge, after analysis, can be converted into statistics which then can be used to optimize operations. Edge analytics can also be used to: 

  • Monitor the health and safety of employees 
  • Enhance production quality and outcome  
  • Identify the early stages of performance impairment and risk failure. 


No other technology is as efficient as robotics to automate business operations, reduce workload, increase production, and minimize errors. Robots reduce the workload of employees and allow them to spend more time on much more complex tasks. With AI being added to robotics, they not only monitor their actions but also train themselves to work more efficiently and improve their performances every day.  

Quality checks 

This is one of the most important use cases of artificial intelligence in the manufacturing sector. Sometimes detecting the internal malfunctions of equipment becomes difficult to even though experts are not able to monitor the performance of the products and find out their shortcomings. But this task can be easily completed with the help of Artificial Intelligence (AI) and Machine Learning (ML) as AI tools and applications can effectively detect minor bugs in machinery.  Therefore, it is clear that artificial intelligence ensures quality checks and control in manufacturing. Smart AI solutions track machine productivity and performance, enhance productivity, detect faults, and eliminate costs of maintenance as well.  

Customer management  

Smart AI chatbots not only help in increasing sales, productivity, and performance but also helps in improving customer service. This reduces the waiting time of customer, gives instant replies to them, build customer relation using CRM tools, and use consumer data to make informed decisions.  

Wrap Up 

AI and industrial automation have achieved extensive and significant progress in recent years. The development of machine learning techniques, the most sophisticated robotic technology, the increase in the growth of computer power, and ultra-modern sensors – all have contributed to the emergence of AI as a superpower in the modern era. The deep learning and speech recognition skills enabled AI to collect and extract data, identify patterns, learn, and improve day-by-day. All these factors made AI highly adaptable to the human environment. The implementation of Artificial Intelligence (AI) in the manufacturing industry not only supports the manufacturers but also assists technology developers in improving the quality of their ideas, bringing out ‘outside the box’ digital technology solutions, and building them into reality with expert assistance. 

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Use Cases of Blockchain Technology

Blockchain is known to play a major role in cryptocurrency systems like Bitcoin to maintain safe and decentralized transaction records. Bitcoin is a major reason why blockchain has gained popularity in the last decade. It has emerged as a game-changing terminology for various industries including supply chain, health, education, IoT, and many more. The popularity and industrial applications of blockchain are booming because of its inherent advantages – a ledger that is decentralized and distributed is unchangeable and fully transparent. A blockchain network does not require a centralized authority to handle it. The information saved in the blockchain ledger can be cross-checked by anyone in the network. The bottom line is safe, reliable, and offensive to attackers. 

Blockchain Use Cases 

Blockchain is a powerful technology that offers many advantages to various industries. Here are some of the major use cases of blockchain: 

Smart contracts  

Smart contracts are similar to normal agreements. The only difference is that the contract guidelines are implemented on a blockchain in real time. This not only eliminates the need for intermediaries but also increases the level of liability for all the parties involved, which is impossible in traditional contracts. This is also cost-effective, saves time, and ensures compliance from all the parties involved. With the discovery of benefits offered by contract-based blockchain in different sectors, there has been an increase in its popularity. Some of the examples include BurstlQ in healthcare and Propy in real estate. 

Internet of Things (IoT)  

The next reasonable rise in blockchain applications takes place in the Internet of Things (IoT). IoT has a lot of applications and numerous security concerns and the proliferation of IoT products gives the greatest opportunity for hackers to loot your data on everything from Google’s Nest to a smart thermostat. Such data breaches can be avoided using blockchain-infused IoT that offers a great extent of security with the transparency of technology and virtual integrity to maintain things “smart”. Filament, HYPR, and XAGE security are some of the US companies that use blockchain in IoT to make it smarter and more secure. 

Personal identity security  

As per the reports, around 14.4 million Americans have been subjected to identity theft in a year, which indicates that 1 out of every 15 people is becoming the victim of identity fraud. This type of fraud can range from the forgery of documents to personal file hacking. The government can see a significant reduction in identity theft claims by storing sensitive data like social security numbers, certificates of birth, PAN, etc. in a decentralized and fixed blockchain ledger. Some blockchain-based initiatives at the forefront of identity security include Ligero, Illinois blockchain initiative, and Civic. 


Blockchain in health care has played a significant role in managing patient data and security. With a huge number of data breaches and leaks, protecting personal data has become a serious concern for patients and hospitals. The transparency blockchain has offered gave assurance that changes in the information are clearly visible and cannot be meddled with. This way, blockchain technology has enabled the quick and secure provision of sensitive healthcare information to providers and patients, while giving privacy and transparency through encryption and sophisticated security codes. It also makes patient-provider communication efficient because of its decentralized nature. Since information is stored in multiple nodes, any change made in them will be updated in every node connected, thus helping to deliver updated information to doctors as well as patients.  


The use of blockchain in logistics systems and distribution networks allows easy tracking of goods. Though companies try to invest in tracking technology, the safety of the technology remains questionable as they lack a secure authentication process. This may give way to cyber criminals making use of network information. Blockchain guarantees you an appropriate authentication channel with verification. Plus, it facilitates live tracking of all your deliveries, thus ensuring a better customer experience. Moreover, it is also helpful in improving the national as well as international delivery processes while increasing their cargo capacity and their processing efficiency. If used properly, it will withstand a lot of adverse conditions that provide better transparency in logistics. This also builds reliability and trust between companies. With better transparency, invoice disputes will be reduced, labor exploitation will be reduced, and better auditing costs will be incurred. 


We have already mentioned the use of blockchain ledgers to secure crucial and sensitive data. But blockchains in the government sector have other uses as well. As reported by New York Times, blockchain can play a major role in enhancing the functional efficiency of bureaucracy, and accountability, and reducing large financial liabilities. Blockchain is also capable of cutting down millions of hours of red tape each year, using smart contracts to keep public officials responsible, and recording all activities to provide transparency. Moreover, blockchain-based voting can enhance the engagement of the public in elections as it provides the security and scrupulousness that enables voting from mobile devices. Voatz, the State of Delaware, and Follow My Vote are some of the companies and government agencies that use blockchain applications to improve government. 


The majority of prevailing issues in the media are related to intellectual property rights, data privacy, and royalty payments. As per the study conducted by Deloitte, media digitization is the triggering factor behind the widespread sharing of copyright-infringing content. According to Deloitte, blockchain can offer the media industry the facelift it needs in terms of copyrights, payments, and piracy. The power of blockchain in the media industry lies in its ability to block the presence of digital assets in different locations, such as mp3 files. It facilitates sharing the file while maintaining ownership as it is not possible to make piracy virtually with a transparent ledger system. In addition, blockchain enables advertisement agencies to aim at the target audience and musicians to gain appropriate royalty, thus maintaining data integrity. The companies that utilize blockchain in the media industry are MadHive, Steem, and Open Music initiative. 

Money Transfer  

The two best technology use cases of blockchain are money transfer and payment processing. Bitcoin-initiated, cryptocurrency transfer applications have gained much popularity in recent years. Blockchain technology enables transactions at a greater speech in real-time, thus saving time and money as it does not charge any transaction fee like most banks or financial institutions. It also supports faster and more secure cross-border payments (payments made between people in different countries), enables verify transactions that offer extra security, avoids any kind of intermediaries or third person between the payee and the payer, etc.  

Wrap Up 

Here we have discussed some major sectors that utilize blockchain in different ways. It has been proven that the advantages or uses of blockchain applications are not limited to cryptocurrency and bitcoin. The transparency and reliability it offers have impressed a lot of businesses that saved time and resources using blockchain technology. It is clear that blockchain is going to dominate the economy at some point in the future. 

Artificial Intelligence in Logistics 

Companies that develop artificial intelligence solutions is something that is gaining more attention from businesses and organizations these days. AI has emerged as a huge trend in many industries. The logistics industry is one where artificial intelligence can serve many of its purposes. Transportation, delivery, and product supply are also part of logistics where AI makes a difference.  

AI applications in logistics 

Though there are different ways of implementing artificial intelligence in the logistics industry, there are some major AI applications or use cases which are explained below: 


Planning for a logistics industry has many aspects. Effective and feasible approaches to planning are very much necessary for coherent coordination and proper use of resources, both financially and humanely. The use of live data along with the smart solutions of artificial intelligence facilitates more precise forecasting optimization and has only a few errors when compared to conventional prediction methods. This enables the manufacturers to manage human resources and other resources in the most efficient and cost-effective way, thus minimizing the holding cost which can lead to costly production. 

Automated warehousing  

An automated warehousing system is a relevant area where we can employ artificial intelligence. Many businesses are relying on warehouse robots to enhance the management of the supply chain in businesses. The value of warehouse robots with the capabilities of AI in the market was $2.28 billion as per the records of 2016 and is expected to show a growth rate of 11.8%. Since they are driven by artificial intelligence technology, performing tasks like arranging, packaging, and transporting goods and services becomes easy and effortless. Amazon Robotics is one of the best examples of warehouse robots.  

Autonomous devices and services  

Modern artificial intelligence technology is driving most of the autonomous vehicle systems such as drones, self-driving cars, robots, etc., that offer a helping hand in labor-intensive works at logistics and factories. Artificial intelligence is ideal for these tasks as it does not need analytical skills. Moreover, self-driving cars can significantly reduce the reliance on human drivers. Such technologies aim at supporting the health and safety of the driver by minimizing fuel consumption and excessive emission of carbon from vehicles.  


The computer vision technology enabled in AI helps in detecting malfunctions by identifying the type and intensity of the damage. This allows the manufacturer to avoid or minimize any further damage and work on the same as it analyzes the live data gathered from sensors installed in the machines. Machine Learning (ML) technology enables analytics tools that improve forecast analysis, and technicians to recognize patterns from sensor data. Hence, allows the manufacturers to take appropriate actions to make the situation better before something goes wrong with the machinery. 

Back-end operations  

Automation is not just limited to heavy tasks that require a great amount of human effort. It can lift the weight of many silly and repetitive tasks from the worker’s shoulder. AI also contributes to improving the automation of unskilled and hand-operated office work such as billing of products and services, generating reports, email processing, organizing and tracking transportation of goods, employee management, etc. Artificial Intelligence can also improve sales and marketing departments by generating more accurate market analytics, lead scoring, and email marketing. 

Conversational agents   

Customer service is another important area of logistics on the verge of automation. As AI-driven conversational bots can acquire a significant position in customer service, it is time for the logistics industry to go beyond conventional voice-based picking. Artificial intelligence boosts the use of advanced conversational solutions throughout the logistic platforms from regular consumer interactive platforms to warehouse interactions. Moreover, new innovations in NLP (natural language processing) algorithms expand the scope of conversation AI through: 

  • Feed in, store, and extract product information. 
  • Activate an automated picking system in voice-input-assisted warehouses. 
  • Use voice input to guide drivers. 

Sales and marketing optimizations  

Many giant automobile companies such as Tesla, Benz, etc., are investing a good share in automated vehicles or autonomous vehicles. As per BCG figures, 25% of the miles covered by private vehicles will be replaced by shared autonomous electric vehicles (SAEVs) in 2030. Drones are also getting much popularity in logistics industries as they are considered a reliable, and safe option for the delivery of various products to different locations, especially products with less shelf life. These delivery drones play a major role not just in eliminating unnecessary costs like delivery charges but also in freight management. 

Better demand prediction 

It is essential for the successful running of a company to predict the number of goods and supplies required for the future. Any failure to make accurate forecasts and inability to meet the demand because of the low quantity of goods results in financial loss, which is the last thing any company would want to face. When the predictions are not accurate, you will lose inventory and sales. AI algorithms are very good at predicting these trends. In fact, they can predict far better than human specialists, after analyzing the previous transaction history.  

Wrap Up 

With digitization hitting almost all global logistics companies, steps are being taken to disrupt the Artificial Intelligence (AI) industry. In order to remain competitive and dynamic, international logistics giants like DHL are taking advantage of AI’s machine learning technologies and Robotic Process Automation to efficiently automate crucial business processes. After considering all advantages and benefits it could offer, incorporating Artificial Intelligence technology into the logistics industry is very important to outperform rivals and to bring in a reasonable and positive revolution in the current business world.  

Artificial intelligence not only drives the process faster but also gives emphasis to precision and workload reduction in the industry. There are many applications of AI that have proved to be cost-effective, efficient, and useful at the same time. It enables the use of human resources in tasks in addition to people who do not need skills. All these qualities make AI the best option for the logistics industry.  

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Artificial Intelligence in Cyber Security 

Conventional security measures in the cyber world depend on antivirus programming such as firewalls. There are many tools to identify and prevent security vulnerabilities in cyberspace. Even with the advancement of technology, cybercrime continues to grow and become more complex every day. Cybercriminals carry out innovative attacks that endanger modern security systems. Companies opt for Artificial Intelligence (AI) to improve the capability of their system to identify vulnerabilities and cope with rising cyber-attacks. Artificial intelligence in cyber security helps companies not only to protect their defense systems but also to help them in analyzing crimes. Meanwhile, AI utilizes machine learning (ML), deep learning, natural language processing (NLP), etc. in order to make it difficult for cybercriminals to access servers, as well as other relevant data stored inside the system. 

Impact of Artificial Intelligence on Cyber Security 

The application of artificial intelligence has a great impact on cyberspace, especially when it comes to matters that concern the security of a system or network. Other than offering aid to experts in identifying cyber threats or attacks, artificial intelligence has the following impacts: 

Phishing Detection and Prevention Control  

Phishing is one of the most extensively used fraudulent activities in which attackers send emails pretending to be from reputed firms in order to lure individuals and companies to obtain crucial information. One out of 99 messages are phishing messages and that makes a phishing attack a common one. Fortunately, AI-ML may have a significant role to play in preventing and diverting phishing attacks. Computer-based Machine Learning can identify and track over 10,000 dynamic phishing resources and enables us to respond to and solve them faster than people can. In addition, AI-ML works in coordination to percolate phishing attacks from around the world. AI has also made it possible to distinguish between a fake site and a real site quickly.  

Secure Authentication  

Passwords are always extraordinarily sensitive when it comes to security. In fact, they are borderline between cyber attackers and our data/records. AI uses various components to recognize an individual using physically identifiable biometrics like facial features, fingerprint, and voice recognition that acts as the primary means of safe and secure verification. For instance, a cell phone verifies the unique finger impression and facial features to allow you to sign in. This process consists of a program that checks basic information, focusing on your face and fingers to identify if a login is valid. In addition, AI can look for various other elements to determine if any client is authorized to sign in to any specific device. The technology analyzes factors such as your voice, how you enter keys, typing error rate, and composing speed.  

Quick Detection and Response Time  

Artificial intelligence can cross-reference cautions and security information sources instantaneously in order to speed up the detection of authentic issues. This even helps the experts in digital security to approach each security issue that needs to be taken care of. Anyhow, it has the backing of AI frameworks that continuously suggest plans to improve responses. 

Better Endpoint Protection 

With the increase in the number of remotely operating devices, AI plays a major role in protecting all endpoints. Though malware and ransomware attacks can be prevented using antivirus solutions and VPNs, they operate on the basis of signatures. This indicates that signature definitions need to be updated in order to remain safe from newly emerging threats. If a new type of malware attack occurs, antivirus solutions and VPNs may not be able to protect against it. But in the case of AI-driven endpoint protection, if something unusual happens, the AI points it out and takes necessary action by either notifying the technician or returning it to a secure condition after a ransomware attack. Instead of waiting for signature updates, it gives active protection against threats. 

No Zero-day Vulnerabilities  

Any new threat a security expert has to deal with and does not have a patch or remedy to fix is considered a zero-day vulnerability. Zero-Day indicates that the experts have zero days to solve the problem, and an attacker may have already taken advantage of them. Mostly these threats are seen in IoT devices that are not secured. AI’s machine learning algorithms analyze inaccuracies in network traffic, detect zero-day threats and eliminate security vulnerabilities and prevent patch exploitation. 

Automating Security Tasks  

Machine Learning (ML) and Robotic Process Automation (RPA) play an important role in reducing monotonous and time-consuming security tasks, which in turn help human workers to focus more on other relevant tasks that require human attention intelligence. AI algorithms monitor the functioning of the system throughout and are capable of identifying malicious activities or threats like ransomware. Once the threat is identified, it destroys the threat and prevents it before it starts attacking the system. Machine learning can also be used to automate repetitive tasks such as checking network traffic, eliminating viruses, and analyzing network logs. 

Behavioral Analytics  

One of the important uses of AI in the cyber security department is its capability and efficiency in analyzing behavioral patterns. This indicates that ML calculations can study and exemplify human behavior by distinguishing the way humans use gadgets and online platforms. AI calculations watch any kind of unusual activities or any conduct that is different from your standard examples. It can identify it as performed by a suspicious client. AI calculations can perform various exercises ranging from huge online buys transported to addresses different from yours, an abrupt spike in report downloads from your documented envelopes, or an unforeseen variation in your composing speed. 

Preventing Online Frauds  

Organizations should have the option to detect a digital attack in advance. This is an option to thwart what the enemy is trying to do. Artificial Intelligence has proven to be of amazing value in identifying cyber-attacks and identifying risks before the threats take advantage of the vulnerabilities in your data frameworks. When it comes to fraud prevention AI redefines itself by taking past experience into account and in light of new behaviors, and trends in transaction irregularities. AI provides fraud analysts with real-time risk scores and more information about threshold score settings to increase sales and reduce fraud losses. 

Wrap up 

The application of Artificial Intelligence (AI) in cyber security will emerge as the basic mechanism for developing and controlling security systems. Cyber security professionals will get more response time to combat these malicious attacks because AI can detect many threats before they create damage. AI can also detect cyber security vulnerabilities and give recommendations to specialists in order to take appropriate action.  

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Artificial Intelligence in Fintech 

With technological advancements, FinTech companies (Financial Technology) have witnessed revolutionary changes during the last two decades. AI is on track to become a key player in financial services in the short term. Banks and financial institutions are implementing AI solutions to utilize information and statistics stored in unstructured documents and to automate and speed up conventional banking processes at a faster pace. AI and machine learning have always been a great advantage to banks and FinTech because they can process large amounts of customer data, which are then used to gain insights about the preferences of choices of goods and services the customers would want. This helps in building effective customer relationships. 

Artificial Intelligence in Fintech 

Here are some of the major applications of artificial intelligence in fintech that show what makes AI so relevant in financial technology. 

Digital finance advisor  

Automated or digital assistants are used in finance to provide advisory services to customers and to assist customers in making financial decisions. AI can transform fintech with Robo and Bionic advisory often referred to as “robot advisors”, that allow customers to track changes in price trends, and events, and manage their expenses and savings. Robo is a part of financial services that provide relevant advice or assistance in e-investment management without human intervention. Meanwhile, Bionic Advisory offers customized services to companies and organizations in the financial world and promises in-depth investment research and methods to use cutting-edge investment technology. This way such digital finance assistants help users to make financial decisions based on suggestions given by the assistant. Transactional bots are the best example of automated financial advisors because the use of transactional bots has grown rapidly and has become one of the most popular use cases of AI in all industries. 

Insurance management  

Implementation of AI in fintech helps in automating the process of insurance management and giving more precise or relevant data. Automated chatbots in the insurance sector can accelerate the process and help customers in pointing out the insurance requirements by linking multiple data sets. Additionally, this technology also explains levels of risk depending on user activity. Thus, the application of artificial intelligence in Insurance Management helps in identifying any type of risks or problems. It also helps to minimize functional costs and drive the process of decision-making faster.  

Customer support  

Every business and financial institution gives special attention to customer experience and providing services online is one way of making the process smooth and efficient. The application of AI allows you to have direct communication with the customers and to gain real-time access to in-depth customer information within no time. Financial institutions can make use of AI-driven chatbots to provide customers with information about their transaction history, current balance, and other related data. This way AI not only reduces costs but also improves customer satisfaction as well. Moreover, AI-driven automated chatbots can deliver a more positive or interactive communication experience with customers than ‘artificial’ conversations. 

Asset management  

Investment funds leaned on intricate algorithms for a long time to generate predictions and simulations. Due to this, the asset and wealth management industry has to reorganize a number of processes and provide pristine services like wealth management tools. Fintech companies paid attention to this and are integrating these solutions within their applications so that customers can take advantage of them. They started using AI algorithms to forecast future Fintech trends. With AI algorithms, fund managers became capable of successfully monitoring the market, which is a breakthrough development. AI not only automates the process but also helps to perform intelligent operations. App users can now access their bank statements and make critical transactions from any device, which in turn eliminated the need for intermediaries.  


Disruptive technologies like Artificial Intelligence and Machine Learning (ML) are capable of processing a large volume of data and translating it into simple results in their own way. They also can do the work at a low cost while maintaining the quality of the data, which in turn allows the customers to monitor their expenses and gain personalized financial insights. Data extraction and data mining can be used by companies to detect patterns and forecast the future using this big data and with proper assistance from analysts. Finally, it can lead us to predict the trends and choices of customers during the purchase. 


Insurance companies offer underwriting services mainly for loans and investments. An AI-driven model can assess or evaluate the credit risk of a client in real-time, thus enabling advisors to build the best deal possible. The application of Artificial Intelligence (AI) in underwriting services enhances the efficacy of proposals and customer experience by fast-tracking the process and time taken to perform such operations. 

Security and fraud detection  

The fintech industry needs a lot of security to protect crucial data and other information from fraud. Studies have proven that financial institutions are highly vulnerable to cybercrimes and fraud.  AI algorithms are capable of detecting suspicious behavior and informing customers about any unusual activity that takes place in the network. As these technologies can constantly monitor abnormal patterns 24/7, there is no need to stay alert all the time. This helps companies to keep an eye on what is happening behind their backs while being calm that their assets are safe. AI algorithms can also detect other illegal activities such as money laundering.  

Wrap Up 

Artificial Intelligence (AI) solutions in FinTech has the potential to assist businesses in attaining their development goals, achieving competitive advantages, minimizing operating expenses, making internal processes more efficient, and becoming the best choice for their customers. It also benefits users to handle their personal finances. Moreover, artificial intelligence enables the creation of precise statistics related to customers and clients. Eventually, this reduces the time it takes to analyze a large volume of data. AI in Fintech is designed and programmed to manage day-to-day financial services. We have also discussed many other applications of AI in fintech which have proven to survive the times in many conditions. 

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Artificial Intelligence in Transportation 

Transportation, the process of relocating people and goods from one location to another, has now undergone numerous studies, investigations, experiments, and refinements to reach the position where it stands now. Artificial Intelligence (AI) is the leading technology that backs the working of the transportation industry in many ways and has proven to be the technology that is capable of bringing tremendous revolutionary changes in the industry.

Apart from the fact that AI changes our life easier, it helps in making human transportation safer and more efficient through all modes. With AI being implemented, the industry has seen great progress at such a level that transportation is taking place without human intervention or assistance. AI has the capacity to enhance traffic efficiency, relieve traffic congestion, free up driver time, make convenient parking facilities, and boost ride-sharing features. The application of AI in transportation can also eliminate unnecessary fuel consumption caused by non-moving vehicles, as well as improve air quality by enabling traffic flow.  

Why AI in transportation? 

The benefits and uses offered by artificial intelligence services in the transportation industry will explain why it is important or what makes AI important in the industry. Here are some points that prove the importance of AI in transportation: 

Driverless cars preventing accidents  

It is already clear that AI aims to replace human intervention and thereby results in errors in the transportation industry. Self-driving cars that operate without human drivers are one of the best examples of AI use in the industry. Driverless vehicles are designed to follow traffic regulations with the help of sensors, prevent accidents by stopping or slowing down the vehicles whenever an object or person is detected, drive carefully while taking turns, etc. The auto-pilot car launched by Tesla shows the successful implementation of AI in the automobile and transportation industry. Companies like Toyota and Hyundai are also planning to introduce self-driving cars in the near future. 

Parking management  

Hassle-free parking is something every driver looks for and never gets most of the time. AI has put an end to the struggle with parking vehicles. Sensors have been installed to identify the parking space in vacant lots and they can calculate the space occupied by a vehicle parked in one place. Since sensors alone cannot scan license plates, it operates in coordination with cameras, parking meters, and computer vision. The cameras utilize computer vision to detect meterless spots. With the help of automatic number plate technology, they can locate parked vehicles and measure the time they are parked, thus assisting the computer vision to give live updates regarding all the available spaces. This technology also helps drivers to spot all the parking slots which are free using the map on their smartphones. 

Road condition monitoring  

Drivers in the United States spend almost $3,000,000,000 a year as a result of pothole damage, which is a primary concern of the citizens. AI-enables computer vision allows the transportation industry not only to detect damages but also to identify any change in asphalt and concrete to evaluate the surrounding infrastructure. These AI-driven algorithms can detect potholes and the intensity of road damage around the area, thereby helping relevant authorities to initiate actions for road maintenance. The algorithms function by taking the image data before moving to generate automatic crack detection and classification systems. 

Ensure safety  

Safety is a main concern in the transportation industry and it is not just limited to drivers or passengers. The safety of every road user including passengers, pedestrians, and drivers has always been paramount in the transportation industry. Implementation of AI technology is much more than reducing the number of accidental errors made by humans; transportation analytics helps reduce the impact of driving accidents, especially in congested urban areas while keeping an eye on compliance with safety regulations and reports on vehicle maintenance. 

Forecast and monitor traffic  

What would be the most difficult obstacle during transportation? The answer is traffic that causes delays, over-consumption of energy for no reason, wastage of fuel, accidents, etc. However, forecasting techniques help you to predict traffic conditions and automatically find alternative routes using information from traffic monitoring data that can spot events or any construction that causes traffic in the city. Traffic monitoring data provides a smooth and efficient transportation experience for the passengers and drivers, other than saving a lot of time and fuel. 

Efficient planning and schedule  

Issues of intermodal logistics have always been significant to businesses with a large fleet, intricate infrastructure, and multiple links in the cooperative network. Only cutting-edge technology can solve these issues and enhance performance: optimal route scheduling with minimal waiting time, real-time traffic detection to adjust route-setting, and timely controls. Combining AI data analytics with logistics gives an idea of routes, driver behavior, updated transportation planning process, reduced resource wastage, and enhanced security, based on the data. 

Reduced waiting time  

Nowadays the use of online taxis and rides has increased to a greater extent. Passengers are no longer patient enough to wait for hours to get a transportation service. You can simply book a taxi from your location and it will take you to any location you have entered. Transport service providers can use the route map on their phones to locate the customer and reach the location without any hassle. This automatically reduces the waiting time of customers. All these are made possible with AI algorithms and computer vision that helped the service providers to make data-driven decisions. 

Wrap Up 

Artificial Intelligence (AI) in transportation utilizes relevant cutting-edge technologies like machine learning and big data to ensure better safety and greater efficiency, thereby reducing the number of road accidents, and improving compliance with law and order in cities, towns, and as well as in smart cities. If AI can deal with important issues in the transportation industry like a large number of unwanted deaths, interruptions, and damaged roads, it can automatically improve safety and efficiency. Then addressing the second level of problems like human errors, carelessness, over speed, etc. will become easier. 

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Artificial Intelligence in Insurance 

The insurance industry relies primarily on solving the risks associated with a business or an individual. Therefore, insurance companies need a systematic and smooth way to deal with any risk in order to gain more revenue. The advent of Artificial Intelligence (AI) can transform the insurance industry from a ‘detection and repair’ to a ‘predictive and preventive model.  The implementation of Artificial Intelligence with the help of an AI development company in the insurance sector has helped many insurance players to reap a lot of benefits such as efficient claim management, less fraud, and more. Now let us take a close look into the uses or applications of artificial intelligence in the insurance sector. 

Applications of AI in Insurance 

Insurance claim management and investigation 

For insurance companies, claims management is one of the crucial operations. Insurance companies can make use of AI tools to make their claim evaluation and settlement process efficient. AI controls every process in the insurance industry such as claims generation, data capturing, approvals, payment tracking, etc.  It can also perform these tasks with less time and minimal effort. When AI is integrated with other applications like fraud detection, it enables companies to run an efficient, data-based, and automated end-to-end claims processing environment free from human errors. 

Fraud detection and prevention  

There is a loss of USD 40 billion each year due to insurance fraud alone in the United States. This figure gets multiplied when it comes to global scenarios. The traditional investigation method used to recognize and locate suspicious claims involves a great deal of voluntary effort and time. Claimants of suspicious activity need to be closely monitored and pursued. Due to the lack of time to complete the job, this approach is not welcomed in such a competitive industry as insurance. 

Many surveys have shown that a significant number of insurance providers are depending on technology to a greater extent in order to identify and prevent such fraudulent activities. AI can play a vital role in detecting patterns in past data, helping to detect fraud early and prevent it from occurring. As a result, insurance businesses can make a comprehensive risk evaluation before providing their services. 

Better loss estimation for low claims leakage  

The introduction of most modern technologies such as AI, deep learning, and image recognition systems have helped transform the insurance industry. With the help of machine learning capabilities, insurers can evaluate and predict the damage from a photo of the object, thus proving to be the best technology to be used in claim management. It helps to assess possible damage and recommends parts that have to be replaced. This makes the loss calculation process faster and more efficient. 

Claims Reporting  

Insurers can report, track, sort, and assign claims with or without human mediation, depending on the advanced AI systems they use. Chatbots in the insurance sector can effectually deal with the First Notice of Loss (FNOL) reporting process when combined with Natural Language Processing (NLP) and Automatic Speech Recognition technology (Conversational AI). This makes the process simple and boosts productivity. Moreover, there are several benefits of leveraging conversational AI in insurance companies. Automated chatbots can streamline the claim reporting process efficiently and can be used by customers to report incidents from anywhere, anytime. The AI-powered chatbot can then spread the information to the person involved for further processing. 

Benefits of using AI in insurance 

So far, we have covered the application of AI in the insurance industry. Now let us talk about the benefits AI offers to the insurance industry. 

Usage-based insurance  

AI played an important role in bringing up the idea of behavioral policy pricing. The conventional method of reaching insurance premiums on the basis of statistical records has changed with the introduction of AI and resulted in using analytical and personal data to determine the exact premium.  

Better customer experience  

Consumers are not looking for technical jargon, they need simple information that adds value. AI-driven chatbots are useful in providing simple solutions to the intricate questions of a customer. Chatbots have come a long way from giving automated answers to frequently asked questions to recognizing customers’ faces and giving them personalized policies. AI-driven chatbots can improve customer service and minimize the costs of delivering different services to various customers. Companies are utilizing AI to give customized experiences not just to the customers but also to the business clients in order to create more consistent engagement with clients for higher sales, and greater loyalty, and also to evaluate more data from different sources to make better predictions. 

Efficient underwriting  

AI tops in performing data analysis than human analysis especially when it comes to huge amounts of data. AI applications facilitate the underwriter to give more focus on strategy and portfolio management rather than manually checking data. AI’s algorithms are capable of performing monotonous underwriting tasks efficiently.  

Building trust  

Trust and loyalty are the two most relevant factors that play a significant role during an insurance process. Essentially, policyholders want a faster claim process. Two important criteria by which a customer rates an insurance company are the time it takes to settle a claim, and an effortless claim settlement is the important one. Once the claim is settled, the customer will assess the performance of an insurance company.  

Faster claims settlement 

AI helps in automating labor-intensive tasks related to inspections because it has especially proved its worth in times of pandemic through remote inspection. If a vehicle meets with an accident, the insurance provider can assess damages remotely through image sensing. It helps save time and costs during the entire assessment process. 

Wrap Up 

Artificial Intelligence has grown enough to shake the insurance industry from top to bottom. Customers can have a smooth and easygoing experience at affordable rates. The possibilities AI offers are limitless – insurance will become more personalized as insurers will be able to understand the needs of customers using AI technology. AI will also pave the way to gain new revenue in the future while helping insurers to save costs by accelerating workflows. 

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Examples of Artificial Intelligence in Everyday Life

The applications of artificial intelligence (AI) are numerous because this area is continuously evolving day by day. Artificial intelligence refers to technology that educates machines to think, analyze, and learn from data in order to make intelligent decisions. It dominates the world of technology with the promise of bringing many impossibilities more realistic every day.  

Although the engineering and medical fields rely on AI to a greater extent, it has been used widely even in our day-to-day activities directly or indirectly. Here we are going to discuss several examples of artificial intelligence which are a part of our daily lives today. Let’s dive more into some of the best examples of artificial intelligence in everyday life. 

Examples of AI in everyday life 

Face recognition  

Most people use the face recognition feature in their Android or iPhone as it is one of the best safety features available on your device. Moreover, it is easy to use and does not ask for patterns or passcodes when you are in a hurry. This easy and smart feature is the result of artificial intelligence. Humans recognize their co-existing species with their face and voice biometrics, similarly, the AI facial recognition feature uses different types of biometrics to identify a person. This machine learning (ML) technology allows AI to study and save the facial coordinates of a human face from recognizing the user.  

Smart cars  

With the increase in the number of accident cases, many might have dreamt about cars that save drivers and passengers from getting killed. A car that drives on its own stops at traffic signals, takes turns and difficult roads carefully – all that we thought of as a dream has come to reality because of AI. Tesla has already laid its hands on self-driving cars and there are almost 500,000 – tesla automatic cars running in the United States, which is supposed to become double by the coming year. The machine learning capabilities of AI have made the idea of fully automated cars possible. These automated cars are programmed to stop at signals, slow down or stop whenever an obstacle is detected, control the speed limit, etc. 

Digital assistants  

Who wouldn’t want to have an assistant do certain tasks or activities that can be controlled using a fingertip? Digital assistants serve the purpose for you. Sometimes you may want to hear soothing music but you may not have the energy to find it and play from your playlist, then there are situations in which you don’t want to get up and turn the fan or air conditioner off or on. This is exactly what digital assistants can do. They will do all such things for you just with a command. You just need to tell them to switch on the fan or play music or turn off the light and they will simply follow your instructions. Amazon’s Alexa and Apple’s Siri are the two best examples of this far-fetched technology. They not only understand our commands but also respond to our queries or questions, make appointments, manage calls, send emails, set alarms, etc. They keep analyzing and learning from interactions in order to deliver improved customer experiences based on our preferences and search history. 

Entertainment and social apps  

Social media platforms are using AI to give a customized experience to users. One of the best examples is the friend suggestions we receive on Facebook, Instagram, Twitter, and other platforms. These apps show a list of people we might know or those who are on our contact list. How do apps get such information? How do they know that we know the people in the suggestions? Well, that is the magic of artificial intelligence. AI and ML evaluate your usage patterns and recognize your friends from photos and news feeds. Similarly, entertainment platforms like Netflix and Prime Video give many suggestions on what to watch next. This is done using an efficient content rating system that provides hundreds of metrics learning from the user’s previous monitoring history, this way the basic algorithms work well on the recommendation system. 


The banking sector has fully digitized with artificial intelligence. Today, we don’t have to stand in a long queue to withdraw money or transfer it to another account. Customers can initiate transactions without being present at the physical location as AI chatbots are automated to perform all the processes in digital banking. Banks seek the help of artificial intelligence chatbots to offer improved customer experience by enabling seamless and 24/7 customer interaction. From opening an account to making e-payments, the banking sector has become more convenient to users with the use of AI chatbots.  Banks implement different types of chatbots to assist with the middle-office functions in identifying and preventing fraud, improving the anti-money laundering (AML) process, and ensuring the Know Your Customer (KYC) regulatory checks process. This eliminates risk and facilitates a smooth banking experience for customers as well as for institutions. 

Google predictive search algorithm  

You might have noticed several suggestions automatically appearing on the screen before you finish typing what you are actually looking for. This is because of the autocomplete feature of google that predicts the search term by the characters you enter one by one. Google uses artificial intelligence, machine learning, and deep learning to run prediction algorithms in order to make the searches effective.  


Why do people nowadays shift to online sites or apps to make purchases? This is because we can filter out what exactly we want to purchase using certain keywords and filters. For example, if you are looking for a white shoe, the site will show a collection of white shoes of different ranges. You can still filter using a price or pattern you prefer. It takes seconds or minutes only to get a choice of your interest. But how is that possible? This is made possible by the basic AI algorithms that routinely classify product searches for efficient cataloging. 

Wrap Up 

Artificial intelligence services are found to imitate human actions and logic, but that is not the end of it. Today AI transcends human understanding and reason and proves that it is profitable for everyone. The efficiency of machines when integrated with AI is more precise and efficient. They complete the tasks assigned in minutes, which can take days if a man does. This is why the use of AI has been not limited to any particular area, instead, it is made accessible to every human. From personalized digital assistants to self-driving automated cars, AI has covered a long journey along with mankind. 

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