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Customer Engagement Strategies For Gen Zs in Insurance

Indian market is a multi-headed Hydra that confounds in more ways than one. Being the world’s largest democracy and the most diverse country has resulted in a level of stratification that most countries would be unable to fathom. The tiered expectations and a shift in customer demographic are pushing insurers to rework the Customer Engagement Strategies For Gen Zs.

Tier 1 customers hold businesses to an extremely high standard, often on par with global companies operating out of mature ecosystems like the UK, USA, et al.

Tier 2 customers on the other hand are more rustic in their ways of seeing but actively seek the kind of novelty and flair that their Tier 1 counterparts crave. This cohort also strikes a fine balance between modernity and tradition when it comes to customer engagement expectations, e.g. would prefer talking to a live agent instead of a bot.

Tier 3 customers continue to operate on a major time lag, i.e. fully digital touchpoints do not work and software can be a catalyst for change only insofar as they remain invisible in the interactions that Tier 2 customers have with businesses.

Use Cases:

Given the democratized access to generative AI technologies, insurers would do well to incorporate them in each and every facet of the customer experience, right from purchase, all the way to fraud detection. That being said, regional differences could be accounted for in the following ways:

Tier 1: Metro cities require a comprehensive customer experience approach that never rests. Highly personalized chatbots that operate on context, slick user interfaces that are built to minimize friction in service, and proactive communication (via reminders, automated calls, etc.) are strategies that insurance providers could start using.

Tier 2: Given the relatively less frenzied environment in Tier 2 cities, it would make more sense to devote a sizable portion of the budget towards a digitally-enabled physical office. Incorporating the usual technologies to extend reach, while also maintaining a team in these geographies would give it that added human touch that Tier 2 residents usually appreciate.

Tier 3:

For Tier 3 cities, technology ought to recede into the background and do all the legwork that humans did earlier. A more committed implementation of predictive analytics would be needed as Tier 3 residents don’t have as much of a digital footprint as their Tier 1 and Tier 2 counterparts do. 

Phygital v. Digital

Ensuring stickiness and retention amongst Tier 1 GenZ customers will require a domineering digital play. Establishing multiple touchpoints across popular and emerging platforms would be a non-negotiable strategy. 

Tier 2 customers on the other hand would do well with a digital play with a slight mix of physical touchpoints which could include a singular office in the arena, primarily for servicing and support activities. Customer engagement would require a localization effort, in terms of language as well as distribution.

Tier 3 GenZ members would require a full-fledged phygital strategy where the role of digital engagement would purely be limited to the realm of convenience, by way of sharing documents, essential information, etc. Establishing reasonably spacious offices, coupled with outdoor advertising would be the only way to be ‘taken seriously’ in such geographies.

Next-gen Engagement Models

Both AdTech and MarTech are evolving at a rapid pace, to the point where the cost of implementing experiential engagement strategies is decreasing with each passing year. Audiences in Tier 1 areas will be more receptive to AR/VR engagement that can allow Insurers to integrate physical locations with a slick, digital experience. 

The current ecosystem could even allow for engagement strategies built on the metaverse. These, however, will need to be restricted to upscale commercial/residential areas for maximum effectiveness.

Tier 2 and Tier 3 geographies, on the other hand, are not yet primed for such innovations. The balance between physical engagement strategies, i.e. having a team on the ground, hosting events, and actively reaching out to younger customers in collegiate environments ought to be in favor of the physical, with digital-only being an enabler.

There can be no one size fits all customer engagement strategies. The only way forward would be to carefully select an engagement mix and deploy it dynamically to get the attention of GenZ customers.

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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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