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The ‘Digital’ Insurance Broker

3 minutes, 24 seconds read

The technological advancements brought forth by insurtech will soon become routine for brokerage offices within the next few years. Digital-first approaches have finally trickled down, turning ripe for adoption for this major distribution channel. However, broker adoption has still not caught pace with their agency counterparts.

According to a 2019 report surveying independent insurance brokers across the US, Canada & the UK, the average for digital technology adoption at an independent brokerage is only around 43%, even though nearly 96% of them (almost universally) use a broker management system for indispensable day-to-day operations. Interestingly, over 80% don’t offer any form of ‘mobile apps’ or ‘self-service portals’ for customers or staff. 

Today’s insurance customers are younger and prefer digital over traditional channels — leaving a lot of unmet gaps in the value chain. The report also identified key areas where adoption is growing — such as capabilities in workflow process management, document management, sales opportunities & prospect tracking, one system-one view visibility into all departments among others. For example, the downside to not outfitting your broker operation with employee mobility tools alone translates to over 30% reduction in staff productivity. 

Today’s insurance customers are younger and prefer digital over traditional channels

Meanwhile, brokers are facing a whole new set of challenges — Insurance is being built for digital and the audience is changing. Gen Z and Millennials will form the core of their target demographic. A fully online brokerage can benefit these potential customers through simple end-to-end policy administration and by fine-tuning the customer journey.

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Join our Webinar — AI for Data-driven Insurers: Challenges, Opportunities & the Way Forward hosted by our CEO, Parag Sharma as he addresses Insurance business leaders and decision-makers on April 14, 2020.

While brokers are not involved in the manufacture of insurance products or the evaluation of risk, several other value chain functions are being performed through brokers now — of which managing the customer relationship is pivotal. 

There is a lot of data across the lifecycle to look at, which necessitates the need for advanced analytics in order maximize the opportunities to up/cross-sell. At present, data analytics is widely under-utilized among most insurance brokers leaving them blindsided to customer needs.

The Case for a ‘Digital’ Brokerage

A digital broker business is built on these foundational blocks — robust broker management system, seamless mobility tools for employees, insurer connectedness, self-service portals, smart customer apps, advanced data analytics and the cloud. 

The case for digital brokerage

Taking the entire business model online requires the right business advisory and technical roadmap, without which the transformation can leave you with unwarranted gaps in the operating structure. This is where Artificial Intelligence can play a critical role in securing brokerages to be future-ready. The digital broker has to be outfitted with a staunch selection of AI-enabled tools that provide better business visibility, more unified workflows and eliminates time spent managing and updating divergent systems.  

Analysing big data (predictive analytics) and social media using AI can offer real-time insights for measuring risk, immediate demands and possible life changes for customers. For brokers, this translates to an enhanced ability to justify value to clients and ultimately retain those customers.

EY ‘The broker of the future report’

According to a recent EY report on the state of digital brokerages, ‘digital onboarding tools’ and ‘sales leads & application tools’ were identified as attributes with the lowest satisfaction among brokerages. There is a growing sense that these tools need to be a cut above the industry benchmarks — in order to improve the digital relationship with a customer or prospect.

The Digital Broker can also leverage automation to improve efficiency in agent productivity and document handling processes. For instance, enabling employees with remote digital tools empowers them to quickly take action – from quoting prospects to providing policy details and managing claims for existing customers — especially when they need it most. 

Brokers, just like insurers and agencies, need next-gen customer engagement solutions in order to maximize real customer lifetime value. Technologies like Artificial Intelligence have the potential to enhance several facets of the business from reducing back-office processing times and intelligent lead allocation to designing better customer facing products. Improvements achieved through the deployment of AI can create significant gains in operational efficiency and RPE (revenue per employee).

To learn how MantaLabs can help your brokerage begin its digital transformation journey, reach out to us on 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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