The conversational AI market is estimated to grow at a CAGR of 33.26% during the forecast period.
Conversational AI is a kind of man-made reasoning that empowers PCs to grasp, process, and create human language.Conversational AI combines NLP and ML with traditional interactive technologies like chatbots to enable computers to understand, process, and generate human language. NLP and ML are used to enable chatbots to respond to users in a way that mimics human interaction. Conversational AI chatbots are typically rules-based, and their conversations are guided by predefined answers that lead users to specific information. figuring out (NLU) and AI (ML) to hold human-like discussions with clients.NLP permits PCs to appreciate discourse and text so they can speak with people.Conversational computer-based intelligence has limits in its capacity to recreate a genuine human discussion and isn't intended to trick somebody.However, there are ethical concerns associated with conversational AI, including bias, lack of privacy and security, and plagiarism.Introduction:
Conversational AI (CAI) is a fast-growing field that uses natural language processing (NLP) and machine learning (ML) to allow computers to understand, process, and generate human language.. CAI has primarily manifested as chatbots, rules-based programs with conversation flows based on predefined answers designed to guide users through particular information. However, CAI raises ethical concerns such as bias, privacy and security gaps, and plagiarism. Despite these concerns, the CAI market is anticipated to continue expanding as businesses and organizations adopt chatbots and other CAI technologies to enhance customer service and engagement.Drivers:
- Need for personalized customer service:Conversational AI enables businesses to provide personalized customer service by understanding and responding to customer queries in real-time.
- Reduced churn:Conversational AI can help reduce customer churn by providing quick and efficient solutions to customer problems.This can help businesses retain customers and reduce the cost of acquiring new ones.
- Reducing operational costs:Conversational AI can reduce operational costs by automating repetitive tasks in customer service and support.
- Mapping and analyzing customer behavior:Conversational AI can help businesses map and analyze customer behavior by collecting and analyzing data from customer interactions.This can assist organizations with distinguishing patterns and open doors for development.
- Growing focus on customer engagement and retention:Conversational AI, also known as conversational computing, is a rapidly growing field that is transforming the way businesses interact with their customers. By giving customized and productive client support, organizations can further develop consumer loyalty and reliability.
Products offered by key companies:
- Google offers Vertex AI which is a platform that accelerates ML model and AI development for developers and data scientists. and more efficiently. Google Cloud ML Platform is a powerful and efficient machine learning platform that provides a complete set of tools and services for all stages of the ML lifecycle., from data preparation and feature engineering to model training, deployment, and monitoring.
- Microsoft offers Microsoft Power Virtual Agents which is a low-code/no-code platform for building and deploying conversational AI bots. Microsoft Power Apps is a low-code application development platform within the Microsoft Power Platform that enables organizations to create custom business applications without writing code.
- AWS offers Lex Conversational AI Fully managed conversational AI service for developers. It is powered by the same technology that powers Amazon Alexa.
Prominent growth in the Natural Language Processing (NLP) segment within the conversational AI market:
The Natural Language Processing (NLP) segment within the conversational AI market has seen prominent growth due to several factors. Natural language processing (NLP) is mainly a field of artificial intelligence that enables computers to understand human language, both spoken and written. This has a wide range of applications, including personal assistants, customer support chatbots, and sentiment analysis.NLP is driven by the rising digital transformation, as businesses seek to transform their business models and improve customer service and engagement. However, there are still challenges associated with NLP, such as the difficulty of syntactic and semantic analysis, and the need for deep learning techniques. Despite these challenges, NLP is expected to continue to grow in popularity as businesses increasingly adopt chatbots and other conversational AI technologies.The Asia Pacific region is expected to hold a significant share of the conversational AI market:
The Asia Pacific region is expected to hold a significant share of the conversational AI market due to various factors. These factors include a large population, expanding smartphone penetration, and more digitalization across industries, which are promoting the adoption of conversational AI in countries such as South Korea, China, Japan, and India.Additionally, large IT companies in China are significantly investing in conversational AI, and the sector is seeing tremendous advancements in chatbots and voice assistants.The region also offers prospects for conversational AI applications in industries including banking, healthcare, and e-commerce. Because of associations' developing information on state-of-the-art client assistance administrations and advances, the Asia Pacific might have critical development.However, the conversational AI market is expected to grow globally, with North America and Europe also holding significant shares of the market.Key developments:
- In March 2023, Google released Bard, a large language model that can generate text, translate languages, write different kinds of creative content, and answer questions in an informative way.
- In July 2023, Conversica launched Conversica Answers v2, with human-like AI improvements that will allow the company's Revenue Digital Assistants (RDAs) to engage every lead, prospect, and customer in unscripted conversations through computer-based intelligence-created web-based visit, SMS, and email.
Segments
By Component
- Solutions
- Managed Services
- Professional Services
- Training & Consulting
- System Integration & Implementation
- Support & Maintenance
By Deployment
- On-premises
- Cloud
By Type
- Chatbots
- Intelligent Virtual Assistant (IVA)
By Technology
- Natural Language Processing (NLP)
- ML and Deep Learning
- Automatic Speech Recognition (ASR)
By End-user
- BFSI
- Media & Entertainment
- Retail
- IT & Telecommunication
- Healthcare
- Automotive
- Travel and Tourism
- Food & Beverages
- Others
By Geography
- North America
- United States
- Canada
- Mexico
- South America
- Brazil
- Argentina
- Others
- Europe
- United Kingdom
- Germany
- France
- Spain
- Others
- Middle East and Africa
- Saudi Arabia
- UAE
- Israel
- Others
- Asia Pacific
- Japan
- China
- India
- South Korea
- Indonesia
- Thailand
- Others
Table of Contents
1. INTRODUCTION
2. RESEARCH METHODOLOGY
3. EXECUTIVE SUMMARY
4. MARKET DYNAMICS
5. CONVERSATIONAL AI MARKET, BY COMPONENT
6. CONVERSATIONAL AI MARKET, BY DEPLOYMENT
7. CONVERSATIONAL AI MARKET, BY TYPE
8. CONVERSATIONAL AI MARKET, BY TECHNOLOGY
9. CONVERSATIONAL AI MARKET, BY END-USER
10. CONVERSATIONAL AI MARKET, BY GEOGRAPHY
11. COMPETITIVE ENVIRONMENT AND ANALYSIS
12. COMPANY PROFILES
Companies Mentioned
- Microsoft
- Amazon Web Services, Inc.
- IBM
- Oracle
- Nuance Communications, Inc.
- FIS
- SAP SE
- Kore.ai, Inc
Methodology
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