The Property and Casualty (P&C) insurance market has seen considerable and rapid change in recent years. The established industry paradigms are evolving as a result of the convergence of data analytics, technological improvements, and increasing customer expectations. The challenge facing insurers today is to use digital technologies to build a more customer-centric and operationally efficient environment in addition to reacting to them. The emergence of new age Insurance firms, the incorporation of AI and ML, intelligent automation in P&C insurance, and the growing importance of data-driven decision-making are changing the way P&C insurance is conducted. This dynamic environment necessitates a forward-thinking strategy that values adaptability, innovation, and a thorough grasp of new risks. As a result, insurers must rethink their approaches, offerings, and interactions in a world that is changing quickly.

The Role of Claims Processing in Customer Satisfaction and Operational Efficiency

In the world of insurance, the delicate balance between client happiness and operational effectiveness is delicately balanced through claims processing experience. A smooth and clear claims process is frequently the deciding factor for policyholders’ commitment to an insurance provider. Customers’ perceptions of an insurer’s dedication to their financial security and well-being can be greatly influenced by how quickly and accurately claims are handled. A smooth claims procedure not only reassures customers in difficult circumstances, but also establishes a foundation of trust and loyalty, which may lead to repeat business and favourable word-of-mouth recommendations.

Effective claims processing is the key to simplifying internal processes and cost control from an operational standpoint. Manual, labour-intensive procedures can create bottlenecks, which can cause settlement delays, increased administrative costs, and potential mistakes. Intelligent automation and digitalization of claims workflows can speed up communication between departments engaged in the claim’s lifecycle, cut down on errors, and significantly reduce processing times. This not only expedites claim settlements but also optimizes resource use, freeing insurers to concentrate more on long-term goals.

Understanding Intelligent Automation in P&C

Intelligent automation is a ground-breaking method for streamlining procedures and improving client experiences in the context of Property and Casualty (P&C) insurance. It results from the fusion of three potent technical pillars: robotic process automation (RPA), machine learning, and artificial intelligence (AI).

This covers handling claims, underwriting, managing policies, interacting with customers, and more. The objective is to accelerate labor-intensive, complicated procedures while improving decision-making skills through cognitive analysis of data.

Challenges in Traditional Claims Processing

In the insurance sector, traditional claim processing techniques frequently face a number of serious difficulties that limit effectiveness and client satisfaction. These difficulties result from reliance on manual processes, which are prone to mistakes, holdups, and irate clients.

1. Manual Processes and Their Limitations:

Traditional claims processing has a number of drawbacks because it mainly relies on manual data entry, paperwork, and communication:

Human Errors:

When data is entered manually, there is a higher chance that it will contain typographical errors, inaccurate information, and inconsistent data, all of which might influence how claims are handled incorrectly.

Data Redundancy:

Repeated data entering into different systems leads to wasted effort and inconsistent data.

Lack of Scalability: Manual processes struggle to keep up with rising claim volumes, resulting in bottlenecks and resource limitations.

2. Inefficiencies, Delays, and Customer Frustration:

For both customers and insurers, manual claims processing frequently creates inefficiencies that lead to frustrating experiences:

Long Processing Times:

Manual tasks take longer, which adds to the delays in claim approvals, verifications, and settlements. These delays might cause consumer annoyance.

Limited Transparency:

Customers are left in the dark about the progress of their claims in real time, which causes uncertainty and dissatisfaction.

High Administrative Overhead:

The labor-intensive nature of manual processes necessitates sizable personnel for data entry, verification, and communication, which raises the cost of operations.

Addressing these challenges through intelligent automation can not only improve operational efficiency but also enhance customer experiences by reducing delays, errors, and the associated frustrations of traditional claims processing methods.

How Intelligent Automation helps in P&C Insurance?

1. Streamlining Manual Processes:

Automated Data Entry:

Intelligent automation can automate data entry tasks, eliminating the risk of human errors and ensuring accurate and consistent information across systems.

Document Processing:

AI-powered systems can extract relevant information from documents and forms, significantly reducing manual effort and accelerating the claims validation process.

2. Enhancing Efficiency and Speed:

Automated Workflows:

RPA can orchestrate end-to-end claims processing workflows, seamlessly transitioning tasks from one stage to another without manual intervention, reducing processing times.

Decision Support: AI and ML algorithms can analyze claim data and historical patterns to assist claims adjusters in making faster and more informed decisions.

3. Improving Transparency and Customer Experience:

Real-time Updates: Intelligent automation enables real-time tracking of claims, offering customers and insurers immediate visibility into the status of each claim, enhancing transparency and reducing customer frustration.

Automated Communication: Automated communication tools can provide timely updates to claimants, keeping them informed throughout the claims process and enhancing customer satisfaction.

4. Reducing Administrative Overhead:

Task Offloading:

RPA can handle routine and repetitive tasks, freeing up human resources to focus on more complex and strategic aspects of claims management.

Efficient Resource Allocation:

By automating manual tasks, insurers can optimize resource allocation, reducing the need for large administrative teams.

5. Data-Driven Insights and Continuous Improvement:

Predictive Analytics:

Machine learning algorithms can analyze historical claims data to identify patterns and trends, helping insurers identify fraud, assess risks, and optimize processes.

Continuous Learning:

Intelligent automation systems can learn from past interactions, improving their accuracy, decision-making capabilities, and overall efficiency over time.

By harnessing the capabilities of intelligent automation, insurers can mitigate the challenges associated with manual claims processing, leading to faster claims settlements, reduced errors, improved customer satisfaction, and a more agile and competitive operation.

Use Cases of Intelligent Automation in P&C Insurance

The P&C insurance sector has always been characterized by its vast data sets, intricate processes, and the need for accurate decision-making. Today, because of intelligent automation, there’s an opportunity to streamline operations, reduce costs, and enhance customer experiences. Let’s dive into some compelling use cases of IA in P&C insurance:

Claims Processing:

One of the most critical processes in insurance is claims processing. Insurers can automate data entry, validate claims with historical data, and quickly identify potential frauds by leveraging IA. This leads to faster claim resolutions, reduced human errors, and increased customer satisfaction.

Policy Administration and Underwriting:

By analyzing vast amounts of data, IA can assist underwriters in determining policy prices, endorsements, and renewals. Automated data extraction and processing facilitate a quicker and more accurate risk assessment, crucial for determining policy premiums.

Customer Service:

Intelligent chatbots and virtual assistants are now standard in P&C insurance. These bots can answer policy-related questions, guide customers through the claims process, and even assist in purchasing new policies. This 24/7 availability enhances the customer experience and reduces operational costs.

Fraud Detection:

IA can cross-reference claims against thousands of data points to pinpoint inconsistencies. Machine learning algorithms can detect patterns that might indicate fraudulent activities, saving the industry billions annually.

Regulatory Compliance:

With ever-changing regulations, insurers must remain compliant. IA can be programmed to understand these regulations and monitor transactions and operations to ensure they meet the necessary standards.

Predictive Analysis:

IA’s ability to sift through and analyze vast amounts of data means it can forecast future trends. This can help P&C insurers anticipate market shifts, understand emerging risks, and tailor their products accordingly.

Key Applications of Intelligent Automation in Claims Processing

The incorporation of intelligent automation is ushering in a new era of efficiency and precision within claims processing in the constantly changing insurance industry. Insurers are gaining access to a variety of game-changing solutions that expedite processes, improve client interactions, and support fraud detection by leveraging the capabilities of artificial intelligence, machine learning, and robotic process automation.

Automated Data Extraction and Validation:

Intelligent automation is excellent at automating claims processing’s data-intensive processes. Relevant data is accurately extracted and digitized from documents, forms, and other sources via automated data extraction. This data is checked against established criteria by machine learning algorithms, which saves time and guarantees data accuracy. This tool streamlines the claims intake process, reduces errors, and creates a more rational decision-making environment.

Cognitive Chatbots for Customer Interaction:

A significant improvement in consumer involvement during claims processing is provided by cognitive chatbots. These AI-powered bots provide policyholders with round-the-clock support, assisting them with the claims reporting process, responding to their questions, and giving them real-time updates. Insurance companies can improve customer satisfaction by automating common interactions. This improves client experiences, decreases wait times, and frees up human agents to handle more difficult situations.

Predictive Analytics for Fraud Detection:

The ability of intelligent automation’s predictive analytics to combat insurance fraud is crucial. Machine learning algorithms can find patterns in past claim data to indicate possibly fraudulent claims for additional investigation. By concentrating resources on legitimate cases, this proactive approach to fraud detection not only protects insurers from financial losses but also speeds up the processing of legitimate claims.

The deployment of these intelligent automation applications showcases how insurers can leverage technology to streamline claims processes, engage customers effectively, and ensure the integrity of their operations. By embracing these innovations, the insurance industry is poised to create a future where claims processing is faster, more accurate, and aligned with evolving customer expectations.

Conclusion

The integration of intelligent automation within the realm of insurance claims processing heralds a transformative shift in operational efficiency, customer engagement, and fraud prevention. This dynamic fusion of artificial intelligence, machine learning, and robotic process automation is reshaping how insurers approach claims management, addressing long-standing challenges and capitalizing on new opportunities.

By automating data extraction and validation, insurers are streamlining processes and reducing errors, leading to faster and more accurate claims assessments. The advent of cognitive chatbots introduces a new level of customer-centric interaction, ensuring round-the-clock support and enhancing overall satisfaction. Furthermore, predictive analytics empower insurers to proactively identify potential instances of fraud, safeguarding financial resources and maintaining the integrity of the claim’s ecosystem.

How Can TestingXperts help you with the Power of Intelligent Automation in P&C Insurance?

TestingXperts stands as a strategic partner poised to unlock the full potential of intelligent automation within the dynamic landscape of Property and Casualty (P&C) insurance. With a proven track record in software testing and quality assurance, TestingXperts offers comprehensive support in harnessing the power of intelligent automation.

From formulating tailored test strategies that leverage AI, machine learning, and robotic process automation, to designing and implementing cutting-edge frameworks, our expert team ensures seamless integration of automation into P&C insurance workflows. Through meticulous automated testing execution, including predictive analytics and cognitive chatbot evaluation, we accelerate testing cycles while maintaining precision. Moreover, our proficiency extends to performance testing, security validation, and ongoing maintenance, ensuring that your intelligent automation systems function optimally.

With TestingXperts as your guide, you can confidently embrace the transformative potential of intelligent automation, enhancing claims processing efficiency, customer experiences, and the overall success of your P&C insurance endeavors.

The post How is Intelligent Automation Revolutionizing Claims Processing in P&C Insurance? first appeared on TestingXperts.

Today’s businesses leverage technologies like Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Robotic Process Automation (RPA) for automating their tasks and other business processes. Though these next-gen technologies have helped businesses achieve their goals, as we advance, companies need to upgrade themselves by adopting Intelligent Automation(IA), which typically combines the power of AI, ML, RPA, and other advanced technologies.

Content 1. An overview of Intelligent Automation 2. Differences of Intelligent Automation with RPA and Hyperautomation 3. Why should businesses leverage Intelligent Automation? 4. How Intelligent Automation is transforming the BFSI industry? 5. An overview of Intelligent Automation Testing types 6. Conclusion

An overview of Intelligent Automation

Intelligent Automation, also known as cognitive automation combines advanced technologies like: – RPA, – BPM, – AI, – ML, – Analytics, – OCR, – ICR, – Process mining to create end-to-end business processes that think, learn, and adapt on their own. Moreover, this intelligent automation accelerates digital transformation, automates repetitive tasks, ensures freeing up resources, improves operational efficiency, and effectively simplifies various business processes.

Differences of Intelligent Automation with RPA and Hyperautomation

Why should businesses leverage Intelligent Automation?

Streamlines back-office processes and increases efficiency:

Intelligent automation can speed up business processes and streamline tasks per business needs, ultimately increasing process efficiency.

Improves customer service:

This technology helps businesses get real-time access to customer information, accelerate the resolution of customer requests, and help identify additional product/service needs.

Frees-up employees for higher-value work:

Improves governance and fraud detection:

Interprets big data:

Helps in decision-making:

Reduces cost & saves time:

How Intelligent Automation is transforming the BFSI industry?

Intelligent automation is now leveraged across industries and impacts the BFSI sector significantly. Since the BFSI sector plays a vital role in the economy, there is constant pressure on BFSI institutions to improve business performance and lower operational costs. Due to the complexities of data, increased regulatory scrutiny, back-office inefficiencies, and outdated legacy systems, the BFSI sector faces many challenges. The BFSI sector needs to leverage intelligent automation testing to overcome these challenges. This technology helps BFSI institutions reduce costs, boost overall business performance, and deliver a great experience to employees and customers.

1. Banking Sector:

• Frees up banking team for higher-value work: Employees in banks have to regularly deal with repetitive and time-consuming tasks such as entering customer details, KYC process, etc. But, with the help of IA, various tasks can be automated and completed with much accuracy and at a faster pace. This frees up employees and allows them to focus on other high-value tasks.

• Allows customers to open a bank account remotely: Gone are the days when customers need to visit the bank to open bank accounts. But, now, with IA in place, customers can open their accounts remotely. Customers need to complete online KYC, submit required documents, fill in the necessary details and open their accounts in no time.

• Eases general ledger: Banking employees have to regularly maintain and update the ledger daily, a time-consuming and critical task. With the help of IA, banks can collect, update and validate large amounts of information from multiple sources faster and more effectively.

2. Finance Sector:

• Eases the application validation process: Employees working in the finance department have to manually validate applications that consume a lot of time and effort. But with IA technologies such as OCR, NLP, Intelligent Document Processing (IDP), etc., documents can be automatically processed easily in no time.

• Helps in detecting fraudulent activities: IA solutions can continuously monitor real-time transactions and can analyze the patterns of these transactions that help in detecting fraudulent activities such as anti-money laundering, frequent deposits of large amounts, frequent withdrawals, etc. It can also alert the concerned party and help prevent financial fraud in Fintech businesses.

• Eases financial audits: Finance audits are very complex and involve evaluating financial statements, tax calculations, checking amounts payable, and more. With IA, these tasks can be effectively automated, and chances of human-prone errors can be removed.

3. Insurance Sector:

• Makes credit risk assessment accurate and reliable: IA in the insurance sector plays an important role. This technology can intelligently screen prospective borrowers and assign them a risk score based on their ability to repay loan amounts. This process further helps various institutions to make an informed decision regarding credit/loan approval/rejection.

• Ensures faster claim processing: Claim processing is a complex and time-consuming task. Typically, insurance agents need several days to gather data and process claims. But with the help of IA, claim processing and even settlements can be done faster and more effectively without any risk or manual errors.

• Provides intelligent insights: IA tracks and records customer journey and makes insightful recommendations to suggest policies suitable to customer needs based on these recommendations. This further helps customers to manage their insurance money better and ultimately enhances the customer experience (CX)

Other industries where Intelligent Automation is making an impact

1. eCommerce:

• IA utilizes the power of AI technology that records the customer data and their shopping journey and makes recommendations each time customers visit the site for shopping.

• It helps businesses to make decisions about procurement by predicting demand and supply.

• It also enables seamless checkout with their shopping carts while smart algorithms calculate the amount to be charged and ensure seamless transactions to users.

2. Manufacturing:

• Physical and digital robots driven by IA are used to perform various tasks and replace/supplement humans in the manufacturing sector.

• Digital bots help manufacturers process a large amount of data and streamline the ordering process, procurement, appointment scheduling, and alerting.

• It also enables predictive analytics, utilizes machine vision technology, and enables quality inspection that is much more reliable and detailed than humans.

3. Logistics and Transportation

• IA helps truck drivers find the fastest and most cost-efficient routes by utilizing the power of analytics and predictive insights.

• IA has made the concept of self-driving cars into reality, and even drone delivery has been made possible due to the AI technology behind IA.

4. Healthcare

• The healthcare industry is rapidly using AI and RPA technology that goes behind IA to provide better patient outcomes and services.

• AI-powered chatbots are used to make appointments with doctors and provide online consultations.

• Intelligent bots are used to perform surgeries on the head, neck, eye, etc.

• Advanced AI technologies are being leveraged to enable accurate analysis of medical images, such as CT scans, MRIs, and X-rays, which significantly reduce the chances of human error.

5. Telecom

• The Telecom sector has always been data-intensive, and IA helps manage large amounts of data effectively.

• Automated call centers powered by advanced technologies reduce wait time for customers, accelerate the customer query resolution process and enhance the CX.

• IA also helps telecom service providers improve the quality of their network operations by automating the testing, addressing, remediation, and maintenance procedures.

• Intelligent Automation plays a major role across industries and AI-powered apps and solutions must be properly tested to ensure greater outcomes for businesses.

An overview of Intelligent Automation Testing types

UiPath Test Suite based Test Automation:

AI Testing:

AI-Based testing:

RPA Testing:

Conclusion

Intelligent Automation driven by cognitive and digital capabilities is changing the future of all industries, especially for the banking, financial, and insurance sectors. This technology is one of the significant drivers accelerating business growth and ensures a great customer experience. The combination of AI and RPA’s strength in the form of Intelligent Automation is helping businesses improve the quality, speed, and productivity of processes. While some businesses have already realized its importance, others need to adopt it. If you are an enterprise looking for intelligent automation testing, TestingXperts (Tx) can be your one-stop solution.

Tx is a proud partner of UiPath and has been providing UiPath process automation leveraging various UiPath tools to speed up the testing process. Our teams have hands-on experience with the UiPath test suite and provide next-gen intelligent automation testing services to clients across industry domains. We also have an in-house AI-enabled comprehensive platform – Tx-SmarTest that systematically caters to faster releases enabled with DevOps CI/CD implementation. This platform significantly helps boost the software quality through production, which is enabled by combining AI, ML, Deep Learning, and Neural network algorithms.

The post How Intelligent Automation Is Transforming The BFSI Industry first appeared on TestingXperts.

Automation and Artificial Intelligence (AI) have revolutionized how businesses work across industries. Today, businesses continue to deploy AI technologies within their operations to improve operational efficiency and reap tangible benefits. Rapid advancements in technologies and automation have built wider advancement with the integration/collaboration of both AI and automation named Intelligent Automation. This new advanced technology is simply the outcome of AI and automation coupled with human intelligence. It is now widely used across industries, and its usage is expected to rise manifold in the coming years.

Content 1. What is Intelligent Automation? 2. What is the Significance of Intelligent Automation for Businesses? 3. What are the top Trends in Intelligent Automation for 2022? 4. Intelligent Automation Predictions for 2022 5. Conclusion

What is Intelligent Automation?

Intelligent Automation, also known as cognitive automation is a combination of next-gen technologies like Artificial Intelligence (AI), Business Process Management (BPM), and Robotic Process Automation (RPA). Along with these technologies, Intelligent Automation also utilizes some more intelligent technologies like Analytics, Optical Character Recognition (OCR), Intelligent Character Recognition (ICR), Machine Learning (ML), Deep Learning (DL), Natural Language Processing, Process Mining, etc. Together, these technologies enable end-to-end business process automation, accelerate digital transformation for businesses, and streamline their decision-making process across the organization to improve operational efficiency.

According to Analyticsinsight, “With digital transformation, intelligent automation has gained immense importance mainly for process management to orchestrate users, tasks, systems, and robots (RPA) depending on the business needs at each moment. Intelligent Automation contemplates the use of analytics and AI (especially machine learning) to make automated and intelligent decisions, and case management to provide processes with enough flexibility for end-to-end case management success.”

What is the Significance of Intelligent Automation for Businesses?

1. Increases process efficiency:

Intelligent Automation reduces human prone errors, increases processing speed, regularizes outputs, and ensures accuracy.

2. Ensures service continuity & greater CX:

Robots can work 24/7 without manual intervention; thus, Intelligent Automation ensures continuity of services under all situations and delivers a more excellent customer experience (CX).

3. Enables effective monitoring and fraud detection:

Intelligent systems can easily detect suspicious activities such as frauds and alert users to prevent the same.

4. Frees up employees from repetitive tasks:

Leveraging Intelligent Automation frees employees from repetitive tasks and helps them focus on other high-priority tasks.

5. Helps to save costs and time:

By leveraging intelligent technologies and systems, businesses can reduce their team size, achieve operational efficiency, and save time and cost significantly.

6. Ensures traceability of data:

Cognitive automation helps businesses achieve full traceability of their data and processes from start to finish. It can also improve analytics and help business leaders during financial audits.

What are the top Trends in Intelligent Automation for 2022?

1. Adoption of collaborative bots:

Collaborative robots or cobots are the types of robots intended to interact with humans in a shared workplace physically. From lifting heavy weights in warehouses to intelligently removing obstacles from assembly lines, these cobots assist humans in smart factories. These bots are greatly helping small businesses as they do not require large floor space and high personnel assistance to program and maintain them, unlike large robots. Industries are rapidly using the robots to help address the lack of labor resources, automate repetitive tasks, maintain quality, etc. In the coming years, it is expected that the adoption rate of robots will significantly increase across industries.

According to MarketsandMarkets, the collaborative robot market size is expected to grow from USD 1.2 billion in 2021 to USD 10.5 billion by 2027 at a CAGR of 43.4% from 2021 to 2027.

2. More adoption of RPA across industries:

RPA is a technology that enables software bots to replicate human actions and perform a task more effectively. This technology is leveraged by almost every industry, such as insurance, banking, finance, healthcare, and telecommunications. RPA has been significantly helping businesses in achieving operational efficiency, reducing time-to-market, and ensuring high security. Thus, the usage of RPA, which is one of the essential components of Intelligent automation, is expected to rise more in the coming years.

According to Grand View Research, the global RPA market size was valued at USD 1.89 billion in 2021 and is expected to reach USD 13.74 billion in 2028 growing at a CAGR of 32.8% from 2021 to 2028.

3. Low code/no-code automation to gain traction:

The low code/ no-code automation trend is rapidly gaining traction and is expected to rise more in the coming years. The low-code/no-code automation platforms are software programs that require little to no coding knowledge. It offers predesigned workflow templates and a user-friendly drag-and-drop interface for customizing workflows that people can use without back-end computer programming knowledge. These platforms are gaining much attention due to various benefits to businesses, such as faster time to market, scalability, self-service capability, etc.

According to GlobeNewswire, the global low-code development platform market is predicted to generate a revenue of $187.0 billion by 2030, rising from $10.3 billion in 2019, and is expected to grow at a CAGR of 31.1% during the forecast period 2020-2030.

4. Generative AI to come into more force:

Another cognitive automation trend that is coming to market is generative AI. Generative AI is based on AI algorithms and machine learning methods that learn from the existing data such as text, audio files, images and create completely new and original content. Generative AI can be used for a variety of activities such as making software codes, processing images, facilitating drug development, providing better customer service, speeding up check-ins, targeted marketing, etc. It is expected that there will be more usage of generative AI in the future.

According to a leading research analyst, it is expected that by 2025 generative AI will account for 10% of all data produced, up from less than 1% today.

5. Hyperautomation to dominate and make an impact:

Hyperautomation is the use of advanced technologies like AI, ML, and RPA to automate as many tasks and IT processes as possible. Hyperautomation is the future of intelligent automation as it brings all advanced technologies under one roof and helps businesses reap the real-time benefits of all technologies together. Hyperautomation not only automates tasks but also automates the processing of any form of structured or unstructured content that helps businesses in a large way. In the coming years, it is expected that this trend will continue to positively impact businesses.

According to Verified Market Research, the Hyperautomation market size was valued at USD 581 Million in 2020 and is projected to reach USD 2216 Million by 2028, growing at a CAGR of 18.25% from 2021 to 2028.

6. Autonomic systems to be leveraged more:

Autonomic systems are self-managed software/platforms that learn from the environment, make decisions independently without any external intervention, and automatically adapt themselves to the changes in the environment. The four basic principles of an autonomic platform are self-configuration, self-healed, self-optimization, and self-protection. These self-managed systems are expected to be useful in large data sets and complex analytical solutions. In the forthcoming years, the autonomic platform market is expected to grow as it can address challenges enterprises face in managing data, making appropriate decisions, and handling unexpected complexity in a dynamic environment.

According to Verified Market Research, the autonomous data platform market size was valued at USD 989 Million in 2020 and is projected to reach USD 4885 Million by 2028, growing at a CAGR of 22.1 % from 2021 to 2028.

7. Continuous testing to become an integral part of DevOps CI/CD automation:

Today, almost every business needs to adopt DevOps as it enables continuous integration and delivery (CI/CD) of high-quality software to customers. In DevOps CI/CD, the continuous automated testing of the software at each stage of the software development is done with automated tools. In this way, bugs are found and fixed well before the release. As a result, the test cycles become faster, and software is continuously tested and released. This continuous automated testing of the software is a kind of intelligent automation and is expected to become a trend in coming years as more businesses will continue to adopt DevOps.

According to ordor Intelligence, the continuous testing market was valued at USD 1.48 billion in 2020 and is expected to reach USD 3.45 billion by 2026, at a CAGR of 15.24% over the forecast period 2021 – 2026

8. Augmented intelligence adoption to increase:

Another trend that is expected to rise in the coming years is the increasing usage of augmented intelligence. Augmented intelligence is nothing but AI with a twist. It involves robots and humans working together to improve cognitive performance. Platforms that utilize augmented intelligence can collect all sorts of data, both structured and unstructured, from multiple sources and can show that data to human workers in a way that gives a 360-degree view of each customer. This intelligence allows businesses to deliver better services and make informed decisions. Financial services, healthcare, retail, travel, manufacturing are one of the major industries where augmented intelligence is becoming more prevalent.

According to Allied Market Research, the global augmented intelligence market size was valued at $11.73 billion in 2020 and is expected to reach $121.5 billion by 2030, growing at a CAGR of 26.4% from 2021 to 2030.

Intelligent Automation Predictions for 2022

• According to Statista, In 2022, it is projected that the most common application for new shipments of collaborative robots (cobots) will be material handling. Some 7,000 cobot units shipped in 2022 are expected to be used for assembly and around 4,000 units are forecast to be used for pick and place.

• According to Forrester, Intelligent Automation (RPA plus AI) will release $134 billion in labor value in 2022.

• According to IDC’s research, 40% of the G2000 will double the use of intelligent automation in knowledge retention, dissemination, and information synthesis by 2026, filling the skills vacuum in the data to insights life cycle.

• IDC According to a recent IBM report titled “Automation and the future of work,” 79% of executives whose organizations are scaling intelligent automation expect their organization to outperform the competition in revenue growth within the next three years.

• According to Verified Market Research, the Intelligent Process Automation Market size was valued at USD 8.52 Billion in 2020 and is projected to reach USD 21.63 Billion by 2028, growing at a CAGR of 12.37% from 2021 to 2028.

• According to an article published by InformationWeek titled ‘AI, Automation Predictions for 2022: More Big Changes Ahead,’ some of the predictions include, one in five organizations will double-down on “AI inside” to boost real-time readiness, advancing automation will push 15% of enterprises to monitor employee psychology, and creative AI systems will win dozens of patents.

Conclusion:

In the upcoming years, many analysts predict the breakout for intelligent automation across leading industries. It is expected that the adoption rate for intelligent automation will rise more as it is a way forward for businesses to accelerate their digital transformation and automation journey to become autonomous enterprises. By leveraging the combination of advanced technologies (AI, ML, RPA, BPM, etc.) in cognitive automation, businesses can ensure process efficiency, operational efficiency, save considerable time and cost, and deliver a great experience to customers and employees. Leverage next-gen testing services from an independent QA and software testing services provider for next-gen testing services to get high-quality products that are bound to deliver a more excellent experience to your customers.

The post Top Intelligent Automation Trends and Predictions for 2022 first appeared on TestingXperts.