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AI and The Gen Z Experience

4 minutes read

IRDAI InsurTech Event titled- ‘InsurTech -Catalyst that inspires’ concluded on May 30th in Bengaluru. The event aimed to emphasize on InsurTech ecosystem and its benefit for insurers and saw participation from leading companies like Policybazaar, Shri Ram General Insurance, Reliance General Insurance, and Mantra Labs to name a few. IRDAI chairperson, Mr. Debasish Panda highlighted on the insurance and Insurtech partnerships and the significant role that InsurTechs can play in assisting Indian insurance sector to grow. Parag Sharma, CEO Mantra Labs, was invited as a guest speaker at the event to talk about AI and The Gen Z Experience. 

Parag Sharma, CEO Mantra Labs, at IRDAI InsurTech event.

Here are the key takeaways:

  1. Insurtech 3.0 is all about ‘Experience Economy’. With evolving customer expectations, the real challenge for the insurance industry is getting a product faster. Digital customers today want to buy an experience rather than just a product or a service. Partnering with Insurtechs would give insurers much-needed tech capabilities for product innovation. 
  1. Gen Z places importance on customer experience in various decision-making areas and their willingness to pay a premium for a better experience. In fact, CX is the deciding factor in the buying decision for Gen Z. 
PwC report on Future of Customer Experience Survey
  1. Leveraging technologies such as AI, computer vision, predictive analytics, NLP, OCR across the insurance life cycle to create a superior Gen Z experience.
How to create Value across customer lifecycle through AI & Analytics

Stage 1: Consider and Evaluate 

Data plays a key role in risk evaluation, decision-making process, and improving customer experience. Predictive behavioral analytics helps in identifying consumer patterns and the intent of those behaviors. Insurers need to forecast customer expectations based on historical pattern to improve satisfaction scores and boost revenue per customer.

The ‘Digital Behavioral Intelligence Tool’ by Formotiv helps insurers decipher user motivation and intent scores. They collect roughly 5,000-50,000 behavioral data points from 140+ different features on each individual application and provide personalized product recommendations

Stage 2: Buy and Experience

Speed is what the new customer segment wants. Insurers will need to leverage advanced AI and workflow management to improve onboarding experience for the customers. 

Leveraging advanced AI and workflow management to improve onboarding experience for the ‘want-it-now’ customers.

Stage 3: Improving underwriting through AI-Based Dynamic and Smart Decision making in real-time.

Artivatic has introduced a next-gen smart underwriting cloud–AUSIS which helps to connect, and integrate existing or third-party applications and APIs for end-to-end process.

Arivatic Insurtech & Healthtech Platform

Source: Artivatic Insurtech & Healthtech platform

Stage 4: Payment & Claims Management

Fraud Detection with AI and ML models. 

Anadolu Sigorta recently tested a predictive fraud detection system. This detection engine uses automated business rules, self-learning models, predictive analytics, text mining, image screening, device identification, and network analysis that deliver immediate, actionable insights. A.S. attributed over $5.7 million in savings from the AI system.

Claims processing through Computer Vision technology.

Tokio Marine uses an AI-based CV technology to expedite the motor claims process in Japan. AI image recognition allows insurers to evaluate the damage to a vehicle.

The app also shares repair method recommendations and guides the claim process to ensure each claim is processed and settled as quickly as possible.

  1. Every insurance provider must become a part of the insurance ecosystem.

We are in a world of growing connected devices. McKinsey report suggests there will be about a trillion devices by 2025 that will connect and share data with interoperable standards. 

Ecosystems that will enable this data sharing are already shaping up. 

One such upcoming ecosystem is NDHM, now called ABHA. Right now, the focus of this ecosystem is on seamless data exchange between health facilities, and it is just a matter of time when this will be extended to insurance as well.

Another ecosystem that is fast around the corner is that of connected devices (medical/non-medicals/cars, fitness trackers, smart home gadgets, etc.). Data collected from these devices not only will enable insurers to create innovative products but also help in processing claims without any friction. 

Creating a frictionless Gen Z experience will require insurers to be part of these or at least hook into these ecosystems. Technology will act as an enabler in doing so. 

Summing Up

Building a great Gen Z experience on the foundations of data will need long-term conviction, patience and continuous analysis of user behavior.

Moral of the story is: Smell the cheese often so you know when it is getting old.

We should not be expecting things to remain as they were in the past. A keen eye for the data will help us be nimble and be a step ahead in meeting customer expectations.

If you’re interested in learning about next-gen technologies and how your business can make use of AI, we would love to speak with you. You can reach out to us at hello@mantralabsglobal.com

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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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