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Cognitive Approach VS Digital Approach to Insurance

Digital transformation has gone from talk to action, with a momentum that shows no signs of slowing down. As cognitive capabilities have penetrated process, people, technology, things, augmented intelligence and decision making; the cognitive approach to insurance business is no longer considered a back-office ‘efficiency play’. 

A cognitive computing system replicates human intelligence and comes up with solutions for largely ambiguous and complex situations. Implementing this cognitive capability in Insurance enhances customer insights and deduce customer feel through interaction insights, sentiments and connectedness. 

In Insurance, where companies are constantly tweaking business models to improve profitability, the digital approach to insurance is falling short of industry expectations. The ‘Cognitive’ approach is a step ahead of the ‘Digital ‘approach to insurance, and Data is the key ingredient to going cognitive.

Cognitive Insurance a step ahead of Digital Insurance.

The word cognitive is often used interchangeably with the term Artificial Intelligence. However, there are subtle differences between the two, in terms of their purpose and application. Cognitive computing is a process used to describe AI systems that aim at implementing human thought processes such as real-time analysis of the environment, context and intent analysis; and the ability to solve problems. Where AI relies on algorithms to solve a problem, cognitive computing systems have higher goals of creating algorithms that mimic the human brain’s reasoning process to solve a number of problems with changing data and problems.

The purpose of going cognitive in insurance was created solely with the purpose of reducing human effort and refining the existing process across various insurance verticals. 

Examples of cognitive insurance use cases.

  • Traveller’s Insurance Group had sent a fleet of 65 drone surveillance operating-agents to Houston in order to assess the damage from Hurricane Harvey -the costliest tropical cyclone in recorded history
  • USAA had rolled out an Intelligent Personal Assistant, using Amazon Alexa and Clinc that has insurance industry-specific deep vocabulary and knowledge, that goes beyond the capabilities of traditional chatbots or digital solutions. 
  • Liberty Mutual introduced a new app to help drivers involved in car accidents, to quickly assess the damage to their car in real-time using a smartphone camera. The app provides damage-specific repair cost estimates. 
  • AXA Insurance implemented a Google Tensor Flow-based application by using deep analysis of customer profiles. The application can optimize pricing by predicting traffic accidents with nearly 78% accuracy. 
  • Fokoku Mutual, a large Japanese Insurance company, has replaced it’s 34 strong claims assessment workforce with an implementation of IBM Watson Explorer AI solution. The solution can analyze and interpret claim data including unstructured text, images, audio and video to decide policy payouts. 

In the past, insurance industry professionals made decisions based on experiences and historical data. A cognitive approach, to insurance business solutions, is at the helm of a new wave bringing innovation and transformation to insurance. These cognitive capabilities enable insurers to make strategic decisions based on a set of data which continuously updates in real-time, thereby leveraging AI to bring automated efficiency to insurers while delivering the best possible experience to the insured user.
  

 

 

References: 

https://www.mantralabsglobal.com/blogs/cognitive-automation-and-its-importance/ 

Use cases:
https://www.linkedin.com/pulse/cognitive-use-cases-insurance-sushil-pramanick-fca-pmp/  

https://www.lntinfotech.com/wp-content/uploads/2018/02/Moving-from-a-Digital-Insurance-Business-to-a-Cognitive-Insurance-Business.pdf  

https://searchenterpriseai.techtarget.com/definition/cognitive-computing

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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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