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Disruption Vs Innovation in Insurance

3 minutes, 11 seconds read

People concerned with insurance have been using the terms- ‘innovation’ and ‘disruption’ interchangeably, perhaps because both correspond to building something ‘new’. However, there is a fine line between the two. All disruptors are innovators whereas, not all innovators are disruptors. Let’s delve deep into the difference between disruption and innovation in insurance.

Who are the ‘Disruptors’ in Insurance?

Disruptors drastically alter prevalent businesses, services, or products. They tend to be more creative, useful, impactful, inexpensive, time-savvy, and most importantly – scalable. 

As an example, Lemonade took in $57 million in premium revenue from 4,25,000 customers in 2018. This four-year-old startup was able to sell premiums to millennials- 90% of whom were purchasing insurance for the first time.

Reason- instead of an all-encompassing insurance package, Lemonade is keen on distributing micro policies as low as $5, which the customer perceives as useful. They’ve simplified the claim settlement process and within 3 minutes, a customer can get his refund credited to his account. While Lemonade sells its insurance policies through chatbot Maya, chatbot Jim handles claim settlement. Such AI-powered bots can handle multiple customer requests just as human agents and are better in detecting fraud. 

The disruptors are prone to adapt to changing customer preferences, which the traditional insurers are reluctant to because of the fear of losing existing customers. Disruption in insurance can break the barrier of the lower market penetration rate.

What’s Innovation in Insurance? 

Innovation is independent of drastic changes in businesses. It focuses more on bringing positive business development by delivering convenience to the customer and improving operational efficiency.

Innovation is not always about introducing new technology. It is also about harnessing existing technologies to build innovative solutions. For instance, blockchain technology has been there for decades; but the insurance industry has recently utilized it for algorithmic trading, smart contracts, policy distribution, and claim settlements.

For example, AXA Fizzy provides paperless flight insurance based on blockchain technology. Every user interaction is recorded and executed in the ledgers- from buying a policy to claim settlement without any human intervention. 

Other examples of innovation in insurance include Robo-advice, NLP (Natural Language Processing) to understand customer queries, insurance for IoT devices, AI-powered underwriting, automating insurance workflows, and Machine Learning technologies.

Also, read – Innovative insurance products of 2109

However, according to McKinsey’s report on Digital insurance in 2018, most of the P&C, health, and life insurance innovations revolve around marketing and less towards product development and claims. This gives an idea of the scope of innovation in insurance.

Where insurtechs are focusing

What’s Next in Insurance: Disruption or Innovation?

The traditional insurance business is known to be resilient to technological advancements and innovations in terms of consumer-centric products. To stay relevant and competitive, insurers should shift focus from digitization to strategic disruption according to the changing market dynamics.

In fact, Insurers are willing to fund insurance startups to gain a first-mover advantage in terms of technology and innovations. These investments illustrate a clear goal of improving customer experiences and supporting their existing operations at the startups’ risk. 

For instance, “Axa provided seed funding for five European start-ups under a fund set up in France in 2013, before launching Axa Strategic Ventures in 2015. The €200 million ($223.47 million) venture capital fund has the mandate to invest in innovations in insurance..”. (OECD (2017), Technology and innovation in the insurance sector)

Innovation from Insurtechs has the potential to contribute to the insurance value chain; however, managing disruption is still quite a challenge. Disruption alters the business and behaviours in such a short span that most of the outcomes remain unanticipated. While innovation takes time to catch the stream, disruption can make or kill a business. The best is to blend incumbents’ years of experience with innovation from startups to bring an accountable disruption.

We’ve been solving critical front & back-office insurtech challenges through innovative technological solutions. Drop us a ‘hi’ at hello@mantralabsglobal.com to know more.

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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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