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7 Chatbot Trends in Insurance 2021

5 minutes read

The chatbot market was valued at USD 17.17 billion in 2020 and is projected to reach USD 102.29 billion by 2026, which, in other words, it is a 34.75% rise in CAGR over the forecast period (2021-2026). 

“According to some estimates, by 2025 95% of all customer interactions will be powered by chatbots”, reports DuckCreek technologies on their blog. 

“Utilizing AI and machine learning, chatbots can interact with customers seamlessly, saving everyone within an organization time – and ultimately saving insurance companies money. A bot can walk a customer through a policy application or claims process, reserving human intervention for more complex cases,” the blog continues. 

Source: www.mantralabsglobal.com

As chatbots help reduce operational costs and increase customer experience for global enterprises, their market size is likely to increase gradually, thus giving an impetus to Chatbot marketing, online payments, customer service, and similar segments. 

Source: chatbotsmagazine.com 

As we head to the second half of 2021, here’s a look at some of the chatbot trends we expect to see: 

  • Customer Intelligence: 

Predictive Analytics depends on a number of statistical techniques including data mining, predictive modeling, pattern matching, and machine learning. The efficient usage of relevant techniques and algorithms for bots helps to ensure not just premium customer experience but also meeting other business requirements. Integrating advanced behavioral analytics to chatbots is now common practice for companies either as standalone software or as a built-in feature, resulting in a better customer experience.

  • Faster claims handling:

Insurance chatbots are a swift way of arriving at a resolution especially when the query requires minimal support from a human, case in point, pulling up relevant data, answering a question and also, filing a claim. A customer can just ask the bot to help them file a claim and the chatbot gets to work by scanning and pulling up the customer’s policy from the insurer’s database or backend system, ask the customer for any additional details (including a security step), and then initiate the claims filing process. 

  • Conversational AI

Conversational AI will go a long way in helping bridge knowledge gaps and lend more clarity around insurance. An AI-based assistant is the first step in responding to a customer’s queries around plans and policies, benefits and coverage, pricing, payment plans and options, and more. For Care Health Insurance, Mantra Labs built Hitee, an emotionally intelligent chatbot, who works as an entry-level customer support specialist aiding Care Health Insurance with customer queries around insurance. 

  • Video Call Support: 

The COVID-19 pandemic saw a surge in phone calls and video calls as there was an increased need to stay home. On a video call, you can see the person you’re talking to, and read their facial expressions, which is almost as good as face-to-face interaction. However, in case of a video chatbot, you aren’t talking with a human but a chatbot with a digital human avatar. Suitably dubbed ‘artificial humans’, a video chatbot has the ability to help customers through its digitally rendered human face, body, and voice.

This newfound breed of digital humankind works on a mix of machine learning and neural networks which has thus far allowed these avatars to better mimic human emotion and behavior. 

  • Local Languages and Dialects

According to Indian Languages – Defining India’s Internet, a report by KPMG, “Chat applications cater to 170 million Indian language internet users. This is expected to grow to 400 million by 2021 at a CAGR of 19%.” 

Source: Indian Languages – Defining India’s Internet, KPMG 

A multilingual chatbot allows enterprises to connect and converse with consumers across language and cultural barriers helping to enhance engagement and conversions. However, building multilingual chatbots requires more than using a language translator to process text or dialogue from English to another language. 

To make multi-language communication effective and on point, a chatbot must be trained on an end user’s culture, history, and any regional nuances. Additionally, global enterprises are also building multichannel bots that connect multiple messaging platforms or voice channels to the same project. 

  • Emotional Awareness

Picture this: You have had a tough day at work and so you want to wind down and get ready for the weekend, stress-free. However, owing to the pandemic and a continued spate of work-from-home scenarios, the usual Friday night out with friends is a far-fetched dream. What’s the next thing you turn to? Fortunately, there’s an option available for that in the form of chatbots with high emotional intelligence that captures human sentiment, emotional states and elicits positive responses during a conversation, while making sure that the person on the other side of the screen feels safe speaking to a stranger, in this case, a machine. 

Wysa, rated as one of the most innovative mental health support apps, does exactly that. You can have a normal conversation, engage in exercises to help you through anxious phases, listen to sleep sounds that calm your nerves, and it also offers an option to speak to a therapist. Wysa’s EQ also ensures that she makes timely follow-ups to ask how you’re doing and sends weekly reports as a summation of your past conversations. 

A Pew Research Center study reports that by the year 2025, AI and robotics will permeate most aspects of one’s daily life. 

  • Personalized Marketing

Gartner had previously predicted that by the year 2020, people would have more conversations with chatbots than their spouses. The chatbots of the future are not just programmed to respond to questions, but to talk and draw relevant insights from knowledge graphs and eventually, forging emotional relationships with customers. 

Sephora’s Facebook Messenger bot is a popular use case when discussing chatbot personalization. The cosmetics company built and deployed a bot to allow customers to book an appointment for an in-store takeover which resulted in a whopping 11% higher conversion rate than any other booking channels Sephora used. 

Chatbots are constantly on the rise amid the need for customers to be online 24X7. Chatbot architecture and design are fast-evolving to the level that conversational AI will become a standard customer service practice. Noteworthy tech companies are pushing themselves forward in industries like retail, banking and finance, and healthcare sectors with the development of advanced chatbots powered by artificial intelligence and machine learning.

According to linchpin.seo, “Experts believe that AI will be a major investment in customer experience for a few years. 47% of organizations are expected to implement chatbots for customer support services, and 40% are expected to adopt virtual assistants. Predictions of consumer-based services suggest that chatbots will be programmed to match human behavior, offer similar services, and improve customer service.” 

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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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