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Upcoming Trends in Global Insurance Market

Ever since the Pandemic hit, the Insurance industry is upgrading at a fast pace. The main focus hovers on pandemic rehab and customer experience by developing data-driven ecosystems and hyper-personalization models.

According to a Gartner research, the long-term spending for insurance is forecast to grow at a CAGR of 7.5% to $311.8 billion in 2025 driven by IT services and software growing at a CAGR of 9.2% and 12.3%, respectively. These increased investments in data, AI, and digital twin technologies resulted in the emergence of a new generation of business and intelligence in the insurance industry.

But there have been several obstacles that the insurance business has faced.

The challenges of the current or traditional insurance industry

  1. Shortage of speed to deliver new services into the market: Because insurance businesses’ digital implementation timescales are lengthier, customers may feel their insurer is slow and unable to cater to their demands.
  1. High IT run time expense before migrating to digitally improved systems: When trying to get rid of legacy systems and introduce new sales methods that are incompatible with their current legacy technology, becomes substantially more expensive and time-consuming.
  1. Interpreting a considerable volume of client data: With the vast amount of data available for customers and employees in one system, there comes the challenge of ensuring the shared information is comprehensive and accurate. Any discrepancy in handling or interpretation of data may lead to the approval of the incorrect type of insurance claim, causing further delays for clients.

5 upcoming trends in insurance to look forward to:

Let’s take a look at how these insurance trends are transforming and automating core business procedures, improving claims processing, and providing better insurance products.

Low-code

Professionals and non-professionals alike can use modern low-code platforms to create software tailored to their organizations’ specific needs.

By replacing or lowering the need to write code with a graphical interface, low/no-code platforms democratize and speed up the software development process. Insurers may now deploy digital applications with little or no computer programming, allowing them to quickly react to changing conditions, thanks to the growth of low-code and no-code platforms.

Using low-code platforms, insurance companies can increase their operational efficiency by removing the unfavorable consequences of skill gaps among their staff.

Gartner estimated that low-code platforms will make up 65% of application development activity by 2024. 

Some of the well-known Low-code platforms are Zoho Creator, Salesforce Lightning, Mendix, Appian, Microsoft PowerApps, and Google App Maker, which are making the code development process faster and reducing the complexity of the application development process.

Conversational AI

According to a Mantra Labs report, 64% of insurers plan to allow chatbots to do increasingly advanced customer-facing tasks in the next five years.

Many of these employee assistance queries may be automatically fielded and resolved by conversational AI platforms, minimizing the need for human engagement and saving enterprises significant time and money.

Insurance chatbots enabled by advanced conversational AI might deliver omnichannel, round-the-clock, and multilingual support, to name a few obvious advantages. They can also help you create one-of-a-kind, high-quality client experiences. Chatbots can also be used to detect and track fraud signs, informing the insurer as well as the customer.

Smart contracts: Blockchain technology in insurance

According to Verified Market Research, the Smart Contracts Market was worth USD 144.95 million in 2020 and is predicted to reach USD 770.52 million by 2028, growing at a CAGR of 24.55 percent from 2021 to 2028. 

In the past, uncontested claims may take months to process, but thanks to Blockchain and smart contracts, insurers can now automate the execution of insurance products agreements without the use of mediators, making them more transparent and less manipulable. The insurer’s administrative costs are decreased when claim processing speeds up. As a result, companies may reduce rates, increasing market share. 

Neither party can lose information regarding the arrangement. Both the insurer and the insured cannot lose since smart contracts are traceable and irrevocable.

There are several Blockchain use cases in insurance, which you can read here: https://www.mantralabsglobal.com/blog/blockchain-use-cases-in-insurance-industry/

Extended reality (XR) insurance technology

According to an Accenture study, 85% of insurance executives agree that it’s critical to use XR insurance technology to bridge the physical distance gap between personnel and customers.

Some insurers are employing XR technology to improve and enhance certain portions of their business, including training customer service representatives on how to communicate with customers and guide them through the purchasing process using virtual customers. To hunt for risks in constructions, underwriters utilize on-site pictures and other images to create XR simulations. Using augmented imagery, insurers may engage and connect with their consumers remotely.

National Roads and Motorists’ Association Insurance in Australia and Liberty Mutual Insurance in the United States are using AR and VR technologies for car crashes and breakdown simulations. Zurich Insurance is using the same technology to improve staff training, and AXA Insurance uses VR for advertising.

Drones and Robotic insurance technology

IMARC Group expects the market to reach US$ 43.4 Billion by 2027, exhibiting a CAGR of 12.56% from 2022 to 2027.

Drones and robotics are currently being used by many insurers in their risk management and claims management techniques. Drones are a low-cost way to collect data, conduct surveys, and design mitigation plans. The system allows for more proactive and predictive fraud detection and reaction. 

Robotics are being employed in their claims management operations to help forecast the result of a claim and recommend the best strategy based on that prediction (for example, recommending an early settlement on cases where the data suggests a high potential for long-term litigation). Robotics may even aid in the detection of discrepancies between internal policy terms and those offered by brokers. When a policy is originally issued, this allows insurers to spot plans that may result in future losses.

According to a report by McKinsey, programmable, autonomous drones; autonomous farming equipment; and enhanced surgical robots will all be commercially viable in the next decade.

Reasons behind insurance tech trends’ massive adoption

The majority of human workers can be removed from warehouse operations with AI-enabled infrastructure, changing the nature and purpose of workers’ compensation coverage. Wearables and artificial intelligence (AI) are transforming the way insurers use data to produce predictive insights and inform a variety of interactions with policyholders by providing real-time feedback on the impact of physical activity on personal wellness.

Many insurers are still updating their technology stacks and are at the beginning of their digitalization journey, making them vulnerable to being surpassed by more agile competitors.

Conclusion

According to a PwC survey, 65% of insurance agencies believe that AI investments in customer experience (CX) have lived up to expectations. 49% believe that improvements in internal decision-making have likewise met expectations, and 45% say the same about innovation in products and services.

While these technologies possess great opportunities for insurers, many are struggling to adapt. In fact, 53% of carriers struggle to understand blockchain and its use cases, 43% have other insurance technology taking priority, and 38% are concerned with its data security. 

All of this emphasizes the significance of modernizing business operations by investing in training and implementation methodologies. This not only speeds up digital transformation but also improves organizational change readiness.

Other technology trends such as Automated Underwriting, Machine Learning, Cloud Computing, Telematics, Predictive Analytics for Competitive Benchmarking and Modeling, Open APIs, Proactive Risk Management, Embedded Insurance, and Machine Vision are also being researched as well as utilized aggressively to find their applications in the insurance market.

As a result of the convergence of these technological trends, insurers will be able to cover individuals in a more dynamic and responsive manner.

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Smart Machines & Smarter Humans: AI in the Manufacturing Industry

We have all witnessed Industrial Revolutions reshape manufacturing, not just once, but multiple times throughout history. Yet perhaps “revolution” isn’t quite the right word. These were transitions, careful orchestrations of human adaptation, and technological advancement. From hand production to machine tools, from steam power to assembly lines, each transition proved something remarkable: as machines evolved, human capabilities expanded rather than diminished.

Take the First Industrial Revolution, where the shift from manual production to machinery didn’t replace craftsmen, it transformed them into skilled machine operators. The steam engine didn’t eliminate jobs; it created entirely new categories of work. When chemical manufacturing processes emerged, they didn’t displace workers; they birthed manufacturing job roles. With each advancement, the workforce didn’t shrink—it evolved, adapted, and ultimately thrived.

Today, we’re witnessing another manufacturing transformation on factory floors worldwide. But unlike the mechanical transformations of the past, this one is digital, driven by artificial intelligence(AI) working alongside human expertise. Just as our predecessors didn’t simply survive the mechanical revolution but mastered it, today’s workforce isn’t being replaced by AI in manufacturing,  they’re becoming AI conductors, orchestrating a symphony of smart machines, industrial IoT (IIoT), and intelligent automation that amplify human productivity in ways the steam engine’s inventors could never have imagined.

Let’s explore how this new breed of human-AI collaboration is reshaping manufacturing, making work not just smarter, but fundamentally more human. 

Tools and Techniques Enhancing Workforce Productivity

1. Augmented Reality: Bringing Instructions to Life

AI-powered augmented reality (AR) is revolutionizing assembly lines, equipment, and maintenance on factory floors. Imagine a technician troubleshooting complex machinery while wearing AR glasses that overlay real-time instructions. Microsoft HoloLens merges physical environments with AI-driven digital overlays, providing immersive step-by-step guidance. Meanwhile, PTC Vuforia’s AR solutions offer comprehensive real-time guidance and expert support by visualizing machine components and manufacturing processes. Ford’s AI-driven AR applications of HoloLens have cut design errors and improved assembly efficiency, making smart manufacturing more precise and faster.

2. Vision-Based Quality Control: Flawless Production Lines

Identifying minute defects on fast-moving production lines is nearly impossible for the human eye, but AI-driven computer vision systems are revolutionizing quality control in manufacturing. Landing AI customizes AI defect detection models to identify irregularities unique to a factory’s production environment, while Cognex’s high-speed image recognition solutions achieve up to 99.9% defect detection accuracy. With these AI-powered quality control tools, manufacturers have reduced inspection time by 70%, improving the overall product quality without halting production lines.

3. Digital Twins: Simulating the Factory in Real Time

Digital twins—virtual replicas of physical assets are transforming real-time monitoring and operational efficiency. Siemens MindSphere provides a cloud-based AI platform that connects factory equipment for real-time data analytics and actionable insights. GE Digital’s Predix enables predictive maintenance by simulating different scenarios to identify potential failures before they happen. By leveraging AI-driven digital twins, industries have reported a 20% reduction in downtime, with the global digital twin market projected to grow at a CAGR of 61.3% by 2028

4. Human-Machine Interfaces: Intuitive Control Panels

Traditional control panels are being replaced by intuitive AI-powered human-machine interfaces (HMIs) which simplify machine operations and predictive maintenance. Rockwell Automation’s FactoryTalk uses AI analytics to provide real-time performance analytics, allowing operators to anticipate machine malfunctions and optimize operations. Schneider Electric’s EcoStruxure incorporates predictive analytics to simplify maintenance schedules and improve decision-making.

5. Generative AI: Crafting Smarter Factory Layouts

Generative AI is transforming factory layout planning by turning it into a data-driven process. Autodesk Fusion 360 Generative Design evaluates thousands of layout configurations to determine the best possible arrangement based on production constraints. This allows manufacturers to visualize and select the most efficient setup, which has led to a 40% improvement in space utilization and a 25% reduction in material waste. By simulating layouts, manufacturers can boost productivity, efficiency and worker safety.

6. Wearable AI Devices: Hands-Free Assistance

Wearable AI devices are becoming essential tools for enhancing worker safety and efficiency on the factory floor. DAQRI smart helmets provide workers with real-time information and alerts, while RealWear HMT-1 offers voice-controlled access to data and maintenance instructions. These AI-integrated wearable devices are transforming the way workers interact with machinery, boosting productivity by 20% and reducing machine downtime by 25%.

7. Conversational AI: Simplifying Operations with Voice Commands

Conversational AI is simplifying factory operations with natural language processing (NLP), allowing workers to request updates, check machine status, and adjust schedules using voice commands. IBM Watson Assistant and AWS AI services make these interactions seamless by providing real-time insights. Factories have seen a reduction in response time for operational queries thanks to these tools, with IBM Watson helping streamline machine monitoring and decision-making processes.

Conclusion: The Future of Manufacturing Is Here

Every industrial revolution has sparked the same fear, machines will take over. But history tells a different story. With every technological leap, humans haven’t been replaced; they’ve adapted, evolved, and found new ways to work smarter. AI is no different. It’s not here to take over; it’s here to assist, making factories faster, safer, and more productive than ever.

From AR-powered guidance to AI-driven quality control, the factory floor is no longer just about machinery, it’s about collaboration between human expertise and intelligent systems. And at Mantra Labs, we’re diving deep into this transformation, helping businesses unlock the true potential of AI in manufacturing.

Want to see how AI-powered Augmented Reality is revolutionizing the manufacturing industry? Stay tuned for our next blog, where we’ll explore how AI in AR is reshaping assembly, troubleshooting, and worker training—one digital overlay at a time.

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