Chatbot Market

Updated on : Sept 29, 2024

Chatbot Market Size, Share & Trends Report

The global chatbot market size was valued at $4.7 billion in 2022. The market is projected to grow from $5.4 billion in 2023 to $15.5 billion in 2028, exhibiting a CAGR of 23.3 % during the forecast period.

The rising advent of generative models in chatbots to gain an advantage in the coming years as generative models can improve chatbots’ natural language processing (NLP) capabilities, enabling them to understand better and respond to human language. Moreover, Generative models, specifically neural network-based language models like GPT-4 can help chatbots to better understand the preferences and behaviors of individual users, enabling them to provide more personalized recommendations and support.

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Market Dynamics

Driver: Rising usage of generative models in chatbots

AI has witnessed significant advancements currently remarkably around generative AI and LLMs. These models, powered by deep learning techniques, are designed to generate new content based on patterns found in large datasets. For instance, ChatGPT, OpenAI’s chatbot based on GPT-3.5 large language model has amazed users with its ability to generate human-like text that understands every context. But beyond text-to-text, generative AI also includes text-to-image, text-to-video, text-to-3D, text-to-music, and others. Generative AI can transform businesses by allowing companies to create innovative ideas for products, services, and solutions more quickly and efficiently than ever before. Generative AI can authorize enterprises with the data-driven information essential for intelligent decision-making, truncated costs associated with development or marketing product cycles, and quickly identify alternative solutions to complex problems. With generative AI and its predictive capabilities in chatbots, businesses can harness the power of algorithms to make decisions faster and more accurately than before. By leveraging generative AI, companies can explore new possibilities and experiment with different ideas in a fraction of the time.

Restraint: Inability to recognize customer intent and respond effectively

Chatbot solution providers in the market are working toward developing a chatbot to meet user requirements. Software tools, such as APIs, are specifically developed to perform the generic use of chatbot solutions without integrating any specific functionality that fails to meet the specific user requirement and achieve the exact purpose of building a chatbot. Chatbots fed with specific data can assist customers only if posed with questions they are programmed to answer. Hence, if a customer poses a question that the chatbot has no information about, it will fail to understand the customer’s intent and demonstrate an inability to solve the posed query. The inability to recognize customer intent would be a restraining factor for market growth.

Opportunity: Initiatives toward development of self-learning chatbots to deliver human-like conversational experience

Chatbots can revise to changing conditions in the environment and  learn from their actions, experiences, and decisions. These chatbots can analyze data in minimal time and help customers find the exact information they are looking for conveniently by offering support in multiple languages. Self-learning bots, with data-driven behavior, are powered by NLP technology and self-learning capability (supervised ML) and can enable the delivery of more human-like and natural communication. They can also learn from their mistakes. Various plans are being undertaken for the development of self-learning chatbots. Self-learning chatbots can provide more personalized and relevant responses to users, improving the overall customer experience. As the chatbot continues to learn from user interactions, it can provide more accurate and contextually relevant information, leading to higher customer satisfaction.

Challenge: Complex and time-consuming setup and maintenance

A chatbot can be tricky to install, and set up may require high costs. It will need about two weeks to set up a chatbot in any system and learn all its functionalities. Chatbots also need frequent optimization and maintenance to work properly. Whenever there is a change in anything at the company, users must reflect that change in their bot’s answers to clients. Users should also frequently look through the chats to see what improvements they should implement to their bot. Setting up and maintaining chatbot solutions often requires technical expertise, including knowledge of programming languages, natural language processing (NLP), and machine learning (ML). This can be a barrier for businesses without in-house technical resources or budget to hire outside experts. In some industries, such as healthcare and finance, chatbots must comply with strict regulatory requirements. This can add additional complexity and cost to the set up and maintenance of chatbot solutions.

By bot communication, Audio/Voice to register at the highest CAGR during the forecast period

By bot communication, the chatbot market is segmented into text ,audio /voice and video. Audio /voice segment to register at the highest CAGR during the forecast period. Audio/voice bot, also known as a voice assistant or voicebot, is a computer program designed to simulate a conversation with human users through spoken language instead of text. Audio/voice bots use speech recognition and NLP techniques to understand user input and provide appropriate responses conversationally. These bots can be accessed through voice-enabled devices, such as smart speakers or virtual assistants on smartphones. Audio/voice bots can perform various tasks, from playing music and setting reminders to providing weather forecasts and answering questions. They can be useful for individuals who prefer hands-free and eyes-free interaction with technology, as well as for businesses looking to improve their customer service or sales through voice-based interactions.

North America to account for the largest market size during the forecast period

North America is expected to have the largest market share in the insight engine market. The major countries covered in North America are the US and Canada. The North American region, the primary adopter of AI technology, is the major revenue-generating region in the global chatbot market. North America secures the major share of the global chatbot market owing to the highest adoption of emerging technologies, such as natural language processing, voice recognition techniques, and chatbots. These factors are also responsible for adopting chatbot solutions across the region. Moreover, various industry verticals, such as IT and ITeS, telecom, healthcare, media and entertainment, retail, and BFSI, are adopting chatbot tools to resolve customers’ queries quickly.

Key Market Players

The chatbot market vendors have implemented various types of organic and inorganic growth strategies, such as new product launches, product upgradations, partnerships and agreements, business expansions, and mergers and acquisitions to strengthen their offerings in the market. Key players operating in the chatbot market include Google (US), Microsoft (US), IBM (US), AWS (US), Baidu (China), Oracle (US), SAP (Germany), OpenAI (US), Salesforce (US), Meta (US), Artificial Solutions (Sweden), ServiceNow (US), [24]7.ai (US), Kore.ai (US), Conversica (US), Inbenta (US), Creative Virtual (US), Avaamo (US), Haptik (India), Solvvy (US), Gupshup (US), Aivo (US), Personetics (US), LivePerson (US), Freshworks (India), Engati (US), Botsify (Pakistan), Yellow.ai (US), Drift (US), Intercom (US), Chatfuel (US), Landbot (Spain), Pandorabots (US), Customers.ai (US), Rasa (Germany), and BotsCrew (UK).

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Scope of the Report

This research report categorizes the chatbot market based on offering, type, business function, bot communication, channel integration, vertical, and region

By Offering:

• Solutions
  • Standalone
  • Web-based
  • Messaging-based
  • Other Solutions (Live chat and Videobots)
• Services
  • Managed Services
  • Professional Services
• Training and Consulting
• System Integration and Implementation
• Support and Maintenance

By Type:

• Menu-based 
• Linguistic-based
• Keyword Recognition-based
• Contextual
• Hybrid
• Voicebots

By Bot Communication:

• Text
• Audio/Voice
• Video

By Channel Integration:

• Email and Website
• Mobile Apps
• Messaging Apps
• Telephone/ IVR

By Business Function:

• Information Technology Service Management (ITSM)
• Sales and Marketing
• Contact Centers
• Finance and Accounting
• HR
• Operations and Supply Chain

By Vertical:

• Retail and eCommerce
• Telecom
• BFSI
• Healthcare and Life Sciences
• Media and Entertainment
• Travel and Hospitality
• IT and ITES
• Energy and Utilities
• Government and Defense
• Other Verticals (Manufacturing, construction & real estate, Automotive, and education)

By Region:

• North America
  • US
  • Canada
• Europe
  • UK
  • Germany
  • France
  • Italy
  • Spain
  • Rest of Europe
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • ANZ
  • ASEAN Countries
  • Rest of Asia Pacific
• Middle East & Africa
  • UAE
  • Saudi Arabia
  • Israel
  • South Africa
  • Egypt
  • Rest of Middle East & Africa
• Latin America
  • Brazil
  • Mexico
  • Argentina
  • Rest of Latin America

Recent Developments:

• In March 2023, Baidu announced that it would finish internal testing of a ChatGPT-style project called “ERNIE Bot” in March. ERNIE, short for “Enhanced Representation through Knowledge Integration,” is a sizable language model powered by AI.
• In March 2023, OpenAI introduced GPT-4 to scale up deep learning. GPT-4 is a sizable multimodal model that accepts image and text inputs and emits text outputs. GPT-4 performs at a human-level on academic and professional benchmarks despite being less capable than humans in many real-world scenarios.
• In February 2022, Google launched a new Chatbot service for testers named Bard. The company is firstly making it available using LaMDA’s lightweight variant.
• In February 2023, OpenAI introduced a chatbot called ChatGPT that can communicate with anyone, respond to follow-up inquiries, and correct tenuous assumptions.
• In January 2023, Microsoft launch of Azure OpenAI Service. It includes cutting-edge AI models such as GPT-3.5, Codex, and DALL•E 2. The companies to build cutting-edge applications owing to the infrastructure and enterprise-grade capabilities of Microsoft Azure.   

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