Real World Conversation AI Use Cases Industry-Wise

Conversation Intelligence

Just like mobile phones and other everyday gadgets, chatbots and virtual assistants have seamlessly become part of our lives. These tools continue to evolve, offering more value and convenience in our daily interactions.

This fast-paced evolution reflects itself in new technology adoption rates also. A PwC study saw that 86% of respondents viewed AI as a mainstream strategy, while nearly 97% of businesses reported customer satisfaction to be improved after intelligent digital assistants were used for their purposes. This marks another major shift: Conversational AI has evolved from merely cutting costs to fundamentally transforming business operations and customer support.

In this blog, weโ€™ll explore real-world examples of how conversational AI is making a difference across industries.

What is Conversational AI?

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Before diving into use cases, letโ€™s clear up a common misconception: Conversational AI and chatbots are not the same.

Conversational AI is an advanced technology designed to communicate naturally with humans. It can understand problems, provide solutions, or connect users to the right business representatives.

In contrast, classical chatbots are limited. They follow pre-written scripts and can only handle simple, menu-based queries. They may not adapt to complex situations, not to mention offer personalized answers, nor can they work out of their scripted boundaries.

How is Conversational AI Different from Generative AI?

While conversational AI and generative AI (GenAI) are related, they serve different purposes:

  • Generative AI creates content like images, text, and reports based on its training data. It works independently of real-time interaction.
  • Conversational AI focuses on human-like, real-time communication. It understands context and provides dynamic, two-way responses.

But these technologies can be utilized together by businesses. So for instance, GenAI can create content, whereas conversational AI engages customers to deliver this in a helpful way.

Benefits of Conversational AI

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Conversational AI brings transformative benefits to businesses, solving the right problems and delivering tangible outcomes like:

  • 24/7 Availability and Faster Response Times: Conversation AI runs 24/7, ensuring customers and clients have immediate support at any moment. For instance, a travel agency uses AI to supply real-time flight updates and handle same-day booking changes. That way, customers don’t experience waiting, even during holidays or off-peak hours.ย 
  • Scalable Customer Support: Businesses can manage an increasing number of customer interactions without increasing the cost of staff. For example, a telecom company uses Conversational AI to respond to thousands of billing inquiries and technical support requests at the same time, cutting down on wait times for customers during peak demand times.
  • Revenue Growth Through Upselling and Cross-Selling: Analyzing customer behavior and history of purchase will allow the Conversational AI to offer products or upgrades to a customer during interactions. An online retailer’s chatbot might recommend accessories or premium versions of a product at the time of checkout to increase average purchase value.
  • Increased Customer Retention: Conversational AI builds stronger customer relationships by delivering consistent and personalized experiences. For instance, a SaaS company uses AI to monitor user activity and proactively offer tutorials or solutions when it detects a user struggling, preventing churn and increasing renewal rates.
  • Operational Efficiency: Conversational AI automates tedious, time-consuming tasks, allowing employees to focus on higher-value work. For example, in a banking environment, AI handles account balance inquiries, password resets, and FAQs, freeing human agents to spend their time on resolving disputes or selling financial products.
  • Data-Driven Insights: AI gathers and analyzes conversational data to provide actionable insights into customer preferences and pain points. For instance, a healthcare provider uses this data to identify common patient concerns, optimizing communication strategies and service offerings.

Real-world applications of conversational AI across industries:

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  1. Conversational AI in Banking and Finance

The conversational AI is transforming the banking and financial services industry through the automation of routine tasks, including balance inquiries, loan applications, and fraud detection. This minimizes the need for in-person interactions and provides seamless instant support to customers.

Example: AI-powered assistants in banks help customers with loan processing and other tasks by offering a personalized experience based on financial data. This reduces customer wait times and enhances efficiency in managing requests.

Voice-Based Virtual Assistants: Banks like HSBC use AI assistants to help customers change PINs, check balances, report lost cards, and similar services.

  1. Health-care-related Conversational AI

Healthcare is undergoing massive transformations with conversational AI. Virtual assistants can assist patients in scheduling appointments, remind them to take medication, and answer frequent medical questions, allowing healthcare professionals to dedicate more time to crucial work.

Example: Hospitals uses include conversations where the conversational AI holds attention, acquires necessary data, and helps them book appointments or obtain new prescription renewals, thus lowering administrative loads and improving patients’ experiences at hospitals.

  1. Conversational AI in E-commerce

E-commerce companies use conversational AI to provide real-time, personalized shopping experiences. Virtual assistants assist customers with product inquiries, recommend items, and follow up on abandoned carts to boost sales.

Example: AI-powered chatbots guide customers through the buying process, suggesting products based on browsing behavior and answering queries. This improves the customer experience and increases conversion rates.

  1. Conversational AI in Retail

Retailers use conversational AI to give customers seamless shopping experiences both in-store and online. Virtual assistants assist customers in locating products, discovering promotions, and getting recommendations based on their interests.

Example: Retail chatbots suggest products and promotions based on shopping history, increasing customer engagement and establishing loyalty.

  1. Conversational AI in Telecom and Utilities

Telecom and utility companies have leveraged the use of conversational AI to provide support services to customers. Automated solutions for billing problems, service disconnections, and managing accounts allow handling voluminous customer requests more effectively.

Example: AI-powered virtual assistants can take up billing inquiries, inform customers about service interruptions, and connect them with support whenever needed. This reduces resolution time and alleviates the workload of human agents.

Conclusionย 

Conversational AI is not some far-off future trendโ€”it is the powerful tool transforming industries with automated tasks, better customer experience, and higher operational efficiency. Businesses across banking and healthcare to retail, e-commerce, and telecom use AI-powered solutions to simplify communications and deliver exceptional value to customers.

While conversational AI has transformed how businesses automate tasks and engage with customers, modern challenges demand more advanced solutions. Traditional conversational AI often falls short in addressing important needs such as analysing communication data, improving CSAT scores, and providing actionable insights from conversations.

This is where conversation intelligence comes in. Platforms like Mihup.ai go beyond basic conversational AI by offering tools to analyze, interpret, and optimize conversations with conversation Intelligence. Whether it’s enhancing sales efficiency, unlocking insights from customer interactions, or improving decision-making, Mihup empowers businesses to achieve measurable results.

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