The conversational AI market is expected to develop at a staggering 17.3% CAGR between 2023 and 2033. The market is expected to grow from US$ 9.6 billion in 2023 to US$ 47.6 billion in 2033.
The primary factors escalating the market growth of conversational AI include rising demand for AI-powered customer support services, omnichannel implementation, and lower chatbot development costs. The rise in demand for AI-based Gartner chatbot solutions boosts market growth throughout the projection period.
The conversational AI industry is predicted to grow rapidly in the future years. With the growing desire for personalized and engaging customer experiences, organizations across all industries are recognizing the potential of Conversational AI solutions. To improve customer engagement and streamline processes.
Innovation Catalysts: Factors Fostering Conversational AI Advancements
| Attribute | Details |
|---|---|
| Conversational AI Market CAGR (2023 to 2033) | 17.3% |
| Conversational AI Market HCAGR (2018 to 2022) | 15.2% |
| Conversational AI Market Size - 2023 | US$ 9.6 billion |
| Conversational AI Market Size - 2033 | US$ 47.6 billion |
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Increasing Customer Demand for Personalised Experiences
Businesses in a variety of industries are seeing the value of providing personalized and seamless consumer experiences. Conversational AI allows businesses to communicate with their customers in a more natural and personalized manner, resulting in greater adoption.
Natural Language Processing (NLP) and Machine Learning advancements
Breakthroughs in NLP algorithms and machine learning approaches have considerably increased conversational AI systems' ability. To interpret and respond to human language, boosting industry development.
Chatbots and Voice Assistants are Gaining Traction
Consumers are increasingly interested in voice assistants and chatbots. These conversational AI systems' simplicity and ease of use have accelerated their adoption in a variety of fields, including customer service, virtual assistants, and smart home devices.
Platforms for Messaging and Communication Expansion
Messaging apps and communication platforms like WhatsApp, Facebook Messenger, and Slack have become ingrained in people's daily lives. Integrating conversational AI capabilities into these platforms improves the user experience and offers up new avenues for businesses to communicate with customers.
Consumer Behaviour and Expectations are Changing
Customers are becoming more at ease interacting with AI-powered devices and have learned to demand personalized and efficient experiences. This shift in consumer behavior and expectations is leading businesses to employ conversational AI solutions to meet these demands.
Increasing Big Data and Cloud Computing Availability
Large amounts of data are now available, and advances in cloud computing infrastructure have laid a solid foundation for the development and deployment of conversational AI solutions. These technologies allow for the processing and analysis of massive amounts of data required for AI model training.
E-commerce Customization
By recognizing client preferences, offering product recommendations, and facilitating easy transactions, conversational AI allows personalized shopping experiences. There is a chance to develop AI-powered conversational interfaces that improve consumer engagement, conversion rates, and revenue growth.
Advisory Services in Finance
By providing personalized investment advice, budgeting assistance, and real-time financial information, conversational AI has the potential to disrupt the financial advisory profession. The market opportunity revolves around the development of AI-powered virtual advisors that cater to individual financial goals and deliver data-driven recommendations.
Assistance with Travel and Hospitality
Conversational AI has the potential to revolutionize the travel and hospitality industries by offering personalized suggestions, booking assistance, and real-time customer care. The market opportunity is to develop AI-powered travel concierges that improve client happiness, expedite bookings, and provide personalized travel experiences.
Virtual Assistants in Healthcare
Conversational AI can aid the healthcare business by adopting virtual assistants that can answer medical questions, book appointments, and provide basic healthcare counseling. The market opportunity is in creating HIPAA-compliant conversational AI technologies that improve patient care and streamline Administrative Processes.
Collaboration and Virtual meetings
With the advent of remote work comes an increased demand for AI-powered conversational interfaces that improve virtual meetings, simplify collaboration, and automate administrative tasks. The market opportunity entails developing intelligent virtual meeting assistants that help with communication, agenda management, and productivity.
Principal Consultant
Concerns about Data Privacy and Security
Conversational AI is based on collecting and analyzing massive volumes of user data, which creates privacy and security problems. Stricter rules and customer fear may impede the market growth.
Concerns about Ethics and Bias
Conversational AI systems may display biases or discriminatory behavior unwittingly, mirroring the biases contained in the training data. Addressing these ethical considerations and guaranteeing justice in AI systems represents a big industry challenge.
Adoption and Resistance by Users
Due to a lack of familiarity, fears about job displacement, or a preference for human connection, some consumers may be hesitant to adopt conversational AI. It can be difficult to persuade people of the benefits and utility of conversational AI.
Dependence on Internet Access
To work properly, many conversational AI applications require a stable internet connection. In some areas, limited or unreliable internet access can stymie user adoption and usage.
Natural Language Understanding (NLU) is lacking
Conversational AI systems are built to recognize and respond to human language. Accurate and contextually relevant responses, on the other hand, might be difficult to achieve, leading to user annoyance and discontent.
| Segment | Component |
|---|---|
| Segment Name | Solution |
| Segment Share | 59.3% |
| Segment | Type |
|---|---|
| Segment Name | Chatbots |
| Segment Share | 63.2% |
Services may account for a significant market share by component, with a CAGR of 16.6%. The functionality of conversational AI solutions depends heavily on the services sector. Solution and service providers handle these services, which is a necessary step in deploying technology solutions.
Due to the expanding demand for better customer service across key industries including BFSI, media and entertainment, and travel, conversational AI solutions are becoming more and more in demand internationally.
The chatbot sub-segment is anticipated to generate the most income by type over the projection period. The popularity of chatbots, which offer 24/7 customer support and enhance the customer experience, is a key factor in the sub-segment's quick growth.
Many industries, including finance, government, retail & eCommerce, travel & hospitality, and telecommunications, have shifted their focus to promptly responding to customer inquiries.
Large organizations and small and medium-sized enterprises (SMEs) are both in great demand in the conversational AI industry, albeit for different reasons. Large organizations, with their large resources and established customer bases, frequently seek advanced conversational AI solutions. To improve customer experience, automate operations, and boost operational efficiency. They have the resources to invest in strong and customized conversational AI systems.
SMEs are quickly recognizing the advantages of conversational AI in improving customer interactions, growing operations, and obtaining a competitive advantage. With more inexpensive and scalable solutions becoming available, SMEs are embracing Conversational AI to improve customer service, optimize sales processes, and expand their reach.
Overall, while large organizations may have a higher demand in terms of total numbers, SMEs are fast adopting conversational AI. Due to its potential to level the playing field and uncover new prospects for economic growth.
The deployment mode sector in the conversational AI market may be split into two groups: cloud and on-premises. The cloud deployment technique is currently in great demand and is flourishing on the market. Numerous benefits, including scalability, flexibility, ease of installation, and cost-effectiveness, are provided by cloud-based conversational AI solutions.
They do away with the requirement for complex infrastructure setup and upkeep, enabling organizations to benefit from conversational AI without making significant upfront investments. A simplified and interconnected ecosystem is made possible by cloud deployment's seamless connectivity with other cloud-based apps and services. The market for conversational AI is expanding as a result of the growing acceptance of the cloud deployment strategy.
The Banking, Finance Services, and Insurance (BFSI) industry has a strong demand for conversational AI solutions among the verticals mentioned in the Conversational AI market. This industry has a high demand for quick customer service, and personalized financial advice, and secures transactional processes.
Conversational AI technology allows virtual assistants and chatbots to address client inquiries, provide real-time financial analytics, help with account management, and provide personalized suggestions. With rising client expectations for seamless digital experiences and around-the-clock help, the BFSI sector recognizes the importance of conversational AI. In improving customer engagement, operational efficiency, and overall customer happiness.
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| Countries | 2023 Value Share in Global Market |
|---|---|
| North America | 30.5% |
| Europe | 24.3% |
| Countries | 2023 Value Share in Global Market |
|---|---|
| United States | 21.1% |
| Germany | 10.4% |
| Japan | 7.5% |
| Australia | 2.6% |
| Countries | CAGR |
|---|---|
| China | 16.5% |
| India | 19.2% |
| United Kingdom | 18.2% |
When it comes to the adoption of conversational AI, North America is at the forefront. Key technology businesses, widespread internet use, and sophisticated infrastructure all support market expansion. In particular, conversational AI has been widely adopted across industries in the United States. The area is known for its dedication to innovation, with numerous businesses and academic institutions spearheading developments in conversational AI technology.
Another important region in the conversational AI business in Europe. Adoption is rising significantly in nations like the United Kingdom, Germany, France, and the Nordic nations. In the region, conversational AI is widely employed to improve customer experience and streamline operations in customer-centric industries including retail, banking, and telecoms. Governments in Europe have supported the advancement of AI technology, creating a favorable climate for the market for conversational AI to expand.
The conversational AI market is expanding quickly in the Asia Pacific area. Key contributors to this expansion include South Korea, China, Japan, India, and other nations. A big population, expanding smartphone penetration, and more digitalization across industries are factors promoting adoption. For instance, large IT companies in China are significantly investing in conversational AI, and the sector is seeing tremendous advancements in chatbots and voice assistants. Additionally, the region offers prospects for conversational AI applications in industries including banking, healthcare, and e-commerce.
With a sizable conversational AI market share, these firms are concentrating on growing their consumer base in new countries. These businesses are making use of strategic collaboration initiatives to grow their market share and profits.
Mid-size and smaller businesses, on the other hand, are expanding their market presence. By gaining new contracts and entering new markets, thanks to technical developments and product innovations.
Recent Advancements:
| Date | March 2021 |
|---|---|
| Company | Google Cloud |
| Details | Google Cloud announced the general availability of Vertex AI, a managed machine learning (ML) platform that allows companies to accelerate the deployment and maintenance of artificial intelligence (AI) models. |
| Date | April 2021 |
|---|---|
| Company | Microsoft |
| Details | Microsoft announced the acquisition of an AI-based technology company, Nuance Communications, for US$ 19.7 billion in an all-cash transaction. The acquisition of Nuance expand Microsoft’s capabilities in voice recognition and transcription technology |
| Date | September 202 |
|---|---|
| Company | Astro |
| Details | Astro is a new and different kind of robot, one that’s designed to help customers with a range of tasks such as home monitoring and keeping in touch with family. |
| Date | January 2020 |
|---|---|
| Company | AWS |
| Details | AWS made Amazon Lex chatbot integration available in Amazon Connect in the Asia Pacific (Sydney) AWS region. Amazon Lex chatbots can assist users in changing passwords, bringing up requested account balances, and scheduling an appointment by vocalizing a prompt. |
The market in 2023 is valued at US$ 9.6 billion.
The market secured a 15.2% CAGR from 2018 to 2022.
Chatbots remain the most preferred.
By 2033, the United States is estimated to reach US$ 47.6 billion in 2033.
Google, Microsoft, and IBM are the leading industry players.
1. Executive Summary 1.1. Global Market Outlook 1.2. Demand-side Trends 1.3. Supply-side Trends 1.4. Technology Roadmap Analysis 1.5. Analysis and Recommendations 2. Market Overview 2.1. Market Coverage / Taxonomy 2.2. Market Definition / Scope / Limitations 3. Market Background 3.1. Market Dynamics 3.1.1. Drivers 3.1.2. Restraints 3.1.3. Opportunity 3.1.4. Trends 3.2. Scenario Forecast 3.2.1. Demand in Optimistic Scenario 3.2.2. Demand in Likely Scenario 3.2.3. Demand in Conservative Scenario 3.3. Opportunity Map Analysis 3.4. Investment Feasibility Matrix 3.5. PESTLE and Porter’s Analysis 3.6. Regulatory Landscape 3.6.1. By Key Regions 3.6.2. By Key Countries 3.7. Regional Parent Market Outlook 4. Global Market Analysis 2018 to 2022 and Forecast, 2023 to 2033 4.1. Historical Market Size Value (US$ Million) Analysis, 2018 to 2022 4.2. Current and Future Market Size Value (US$ Million) Projections, 2023 to 2033 4.2.1. Y-o-Y Growth Trend Analysis 4.2.2. Absolute $ Opportunity Analysis 5. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Component 5.1. Introduction / Key Findings 5.2. Historical Market Size Value (US$ Million) Analysis By Component, 2018 to 2022 5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Component, 2023 to 2033 5.3.1. Solution 5.3.2. Services 5.3.2.1. Training and Consulting Services 5.3.2.2. System Integration and Implementation Services 5.3.2.3. Support and Maintenance Services 5.4. Y-o-Y Growth Trend Analysis By Component, 2018 to 2022 5.5. Absolute $ Opportunity Analysis By Component, 2023 to 2033 6. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Type 6.1. Introduction / Key Findings 6.2. Historical Market Size Value (US$ Million) Analysis By Type, 2018 to 2022 6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Type, 2023 to 2033 6.3.1. Chatbots 6.3.2. Intelligent Virtual Assistants 6.4. Y-o-Y Growth Trend Analysis By Type, 2018 to 2022 6.5. Absolute $ Opportunity Analysis By Type, 2023 to 2033 7. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Deployment Mode 7.1. Introduction / Key Findings 7.2. Historical Market Size Value (US$ Million) Analysis By Deployment Mode, 2018 to 2022 7.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Deployment Mode, 2023 to 2033 7.3.1. Cloud 7.3.2. On-Premises 7.4. Y-o-Y Growth Trend Analysis By Deployment Mode, 2018 to 2022 7.5. Absolute $ Opportunity Analysis By Deployment Mode, 2023 to 2033 8. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Organization Size 8.1. Introduction / Key Findings 8.2. Historical Market Size Value (US$ Million) Analysis By Organization Size, 2018 to 2022 8.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Organization Size, 2023 to 2033 8.3.1. Large Enterprises 8.3.2. Small and Medium-Sized Enterprises (SMEs) 8.4. Y-o-Y Growth Trend Analysis By Organization Size, 2018 to 2022 8.5. Absolute $ Opportunity Analysis By Organization Size, 2023 to 2033 9. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Mode of Integration 9.1. Introduction / Key Findings 9.2. Historical Market Size Value (US$ Million) Analysis By Mode of Integration, 2018 to 2022 9.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Mode of Integration, 2023 to 2033 9.3.1. Web-Based 9.3.2. App-based 9.3.3. Telephonic 9.4. Y-o-Y Growth Trend Analysis By Mode of Integration, 2018 to 2022 9.5. Absolute $ Opportunity Analysis By Mode of Integration, 2023 to 2033 10. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Technology 10.1. Introduction / Key Findings 10.2. Historical Market Size Value (US$ Million) Analysis By Technology, 2018 to 2022 10.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Technology, 2023 to 2033 10.3.1. Machine Learning and Deep Learning 10.3.2. Natural Language Processing 10.3.3. Automatic Speech Recognition 10.4. Y-o-Y Growth Trend Analysis By Technology, 2018 to 2022 10.5. Absolute $ Opportunity Analysis By Technology, 2023 to 2033 11. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Vertical 11.1. Introduction / Key Findings 11.2. Historical Market Size Value (US$ Million) Analysis By Vertical, 2018 to 2022 11.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Vertical, 2023 to 2033 11.3.1. BFSI 11.3.2. Healthcare and Life Sciences 11.3.3. IT and Telecom 11.3.4. Retail and eCommerce 11.3.5. Travel and Hospitality 11.3.6. Media and Entertainment 11.3.7. Automotive 11.3.8. Others 11.4. Y-o-Y Growth Trend Analysis By Vertical, 2018 to 2022 11.5. Absolute $ Opportunity Analysis By Vertical, 2023 to 2033 12. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Region 12.1. Introduction 12.2. Historical Market Size Value (US$ Million) Analysis By Region, 2018 to 2022 12.3. Current Market Size Value (US$ Million) Analysis and Forecast By Region, 2023 to 2033 12.3.1. North America 12.3.2. Latin America 12.3.3. Europe 12.3.4. South Asia 12.3.5. East Asia 12.3.6. Oceania 12.3.7. MEA 12.4. Market Attractiveness Analysis By Region 13. North America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 13.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 13.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 13.2.1. By Country 13.2.1.1. The USA 13.2.1.2. Canada 13.2.2. By Component 13.2.3. By Type 13.2.4. By Deployment Mode 13.2.5. By Organization Size 13.2.6. By Mode of Integration 13.2.7. By Technology 13.2.8. By Vertical 13.3. Market Attractiveness Analysis 13.3.1. By Country 13.3.2. By Component 13.3.3. By Type 13.3.4. By Deployment Mode 13.3.5. By Organization Size 13.3.6. By Mode of Integration 13.3.7. By Technology 13.3.8. By Vertical 13.4. Key Takeaways 14. Latin America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 14.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 14.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 14.2.1. By Country 14.2.1.1. Brazil 14.2.1.2. Mexico 14.2.1.3. Rest of Latin America 14.2.2. By Component 14.2.3. By Type 14.2.4. By Deployment Mode 14.2.5. By Organization Size 14.2.6. By Mode of Integration 14.2.7. By Technology 14.2.8. By Vertical 14.3. Market Attractiveness Analysis 14.3.1. By Country 14.3.2. By Component 14.3.3. By Type 14.3.4. By Deployment Mode 14.3.5. By Organization Size 14.3.6. By Mode of Integration 14.3.7. By Technology 14.3.8. By Vertical 14.4. Key Takeaways 15. Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 15.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 15.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 15.2.1. By Country 15.2.1.1. Germany 15.2.1.2. United Kingdom 15.2.1.3. France 15.2.1.4. Spain 15.2.1.5. Italy 15.2.1.6. Rest of Europe 15.2.2. By Component 15.2.3. By Type 15.2.4. By Deployment Mode 15.2.5. By Organization Size 15.2.6. By Mode of Integration 15.2.7. By Technology 15.2.8. By Vertical 15.3. Market Attractiveness Analysis 15.3.1. By Country 15.3.2. By Component 15.3.3. By Type 15.3.4. By Deployment Mode 15.3.5. By Organization Size 15.3.6. By Mode of Integration 15.3.7. By Technology 15.3.8. By Vertical 15.4. Key Takeaways 16. South Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 16.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 16.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 16.2.1. By Country 16.2.1.1. India 16.2.1.2. Malaysia 16.2.1.3. Singapore 16.2.1.4. Thailand 16.2.1.5. Rest of South Asia 16.2.2. By Component 16.2.3. By Type 16.2.4. By Deployment Mode 16.2.5. By Organization Size 16.2.6. By Mode of Integration 16.2.7. By Technology 16.2.8. By Vertical 16.3. Market Attractiveness Analysis 16.3.1. By Country 16.3.2. By Component 16.3.3. By Type 16.3.4. By Deployment Mode 16.3.5. By Organization Size 16.3.6. By Mode of Integration 16.3.7. By Technology 16.3.8. By Vertical 16.4. Key Takeaways 17. East Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 17.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 17.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 17.2.1. By Country 17.2.1.1. China 17.2.1.2. Japan 17.2.1.3. South Korea 17.2.2. By Component 17.2.3. By Type 17.2.4. By Deployment Mode 17.2.5. By Organization Size 17.2.6. By Mode of Integration 17.2.7. By Technology 17.2.8. By Vertical 17.3. Market Attractiveness Analysis 17.3.1. By Country 17.3.2. By Component 17.3.3. By Type 17.3.4. By Deployment Mode 17.3.5. By Organization Size 17.3.6. By Mode of Integration 17.3.7. By Technology 17.3.8. By Vertical 17.4. Key Takeaways 18. Oceania Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 18.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 18.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 18.2.1. By Country 18.2.1.1. Australia 18.2.1.2. New Zealand 18.2.2. By Component 18.2.3. By Type 18.2.4. By Deployment Mode 18.2.5. By Organization Size 18.2.6. By Mode of Integration 18.2.7. By Technology 18.2.8. By Vertical 18.3. Market Attractiveness Analysis 18.3.1. By Country 18.3.2. By Component 18.3.3. By Type 18.3.4. By Deployment Mode 18.3.5. By Organization Size 18.3.6. By Mode of Integration 18.3.7. By Technology 18.3.8. By Vertical 18.4. Key Takeaways 19. MEA Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 19.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022 19.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033 19.2.1. By Country 19.2.1.1. GCC Countries 19.2.1.2. South Africa 19.2.1.3. Israel 19.2.1.4. Rest of MEA 19.2.2. By Component 19.2.3. By Type 19.2.4. By Deployment Mode 19.2.5. By Organization Size 19.2.6. By Mode of Integration 19.2.7. By Technology 19.2.8. By Vertical 19.3. Market Attractiveness Analysis 19.3.1. By Country 19.3.2. By Component 19.3.3. By Type 19.3.4. By Deployment Mode 19.3.5. By Organization Size 19.3.6. By Mode of Integration 19.3.7. By Technology 19.3.8. By Vertical 19.4. Key Takeaways 20. Key Countries Market Analysis 20.1. USA 20.1.1. Pricing Analysis 20.1.2. Market Share Analysis, 2022 20.1.2.1. By Component 20.1.2.2. By Type 20.1.2.3. By Deployment Mode 20.1.2.4. By Organization Size 20.1.2.5. By Mode of Integration 20.1.2.6. By Technology 20.1.2.7. By Vertical 20.2. Canada 20.2.1. Pricing Analysis 20.2.2. Market Share Analysis, 2022 20.2.2.1. By Component 20.2.2.2. By Type 20.2.2.3. By Deployment Mode 20.2.2.4. By Organization Size 20.2.2.5. By Mode of Integration 20.2.2.6. By Technology 20.2.2.7. By Vertical 20.3. Brazil 20.3.1. Pricing Analysis 20.3.2. Market Share Analysis, 2022 20.3.2.1. By Component 20.3.2.2. By Type 20.3.2.3. By Deployment Mode 20.3.2.4. By Organization Size 20.3.2.5. By Mode of Integration 20.3.2.6. By Technology 20.3.2.7. By Vertical 20.4. Mexico 20.4.1. Pricing Analysis 20.4.2. Market Share Analysis, 2022 20.4.2.1. By Component 20.4.2.2. By Type 20.4.2.3. By Deployment Mode 20.4.2.4. By Organization Size 20.4.2.5. By Mode of Integration 20.4.2.6. By Technology 20.4.2.7. By Vertical 20.5. Germany 20.5.1. Pricing Analysis 20.5.2. Market Share Analysis, 2022 20.5.2.1. By Component 20.5.2.2. By Type 20.5.2.3. By Deployment Mode 20.5.2.4. By Organization Size 20.5.2.5. By Mode of Integration 20.5.2.6. By Technology 20.5.2.7. By Vertical 20.6. United Kingdom 20.6.1. Pricing Analysis 20.6.2. Market Share Analysis, 2022 20.6.2.1. By Component 20.6.2.2. By Type 20.6.2.3. By Deployment Mode 20.6.2.4. By Organization Size 20.6.2.5. By Mode of Integration 20.6.2.6. By Technology 20.6.2.7. By Vertical 20.7. France 20.7.1. Pricing Analysis 20.7.2. Market Share Analysis, 2022 20.7.2.1. By Component 20.7.2.2. By Type 20.7.2.3. By Deployment Mode 20.7.2.4. By Organization Size 20.7.2.5. By Mode of Integration 20.7.2.6. By Technology 20.7.2.7. By Vertical 20.8. Spain 20.8.1. Pricing Analysis 20.8.2. Market Share Analysis, 2022 20.8.2.1. By Component 20.8.2.2. By Type 20.8.2.3. By Deployment Mode 20.8.2.4. By Organization Size 20.8.2.5. By Mode of Integration 20.8.2.6. By Technology 20.8.2.7. By Vertical 20.9. Italy 20.9.1. Pricing Analysis 20.9.2. Market Share Analysis, 2022 20.9.2.1. By Component 20.9.2.2. By Type 20.9.2.3. By Deployment Mode 20.9.2.4. By Organization Size 20.9.2.5. By Mode of Integration 20.9.2.6. By Technology 20.9.2.7. By Vertical 20.10. India 20.10.1. Pricing Analysis 20.10.2. Market Share Analysis, 2022 20.10.2.1. By Component 20.10.2.2. By Type 20.10.2.3. By Deployment Mode 20.10.2.4. By Organization Size 20.10.2.5. By Mode of Integration 20.10.2.6. By Technology 20.10.2.7. By Vertical 20.11. Malaysia 20.11.1. Pricing Analysis 20.11.2. Market Share Analysis, 2022 20.11.2.1. By Component 20.11.2.2. By Type 20.11.2.3. By Deployment Mode 20.11.2.4. By Organization Size 20.11.2.5. By Mode of Integration 20.11.2.6. By Technology 20.11.2.7. By Vertical 20.12. Singapore 20.12.1. Pricing Analysis 20.12.2. Market Share Analysis, 2022 20.12.2.1. By Component 20.12.2.2. By Type 20.12.2.3. By Deployment Mode 20.12.2.4. By Organization Size 20.12.2.5. By Mode of Integration 20.12.2.6. By Technology 20.12.2.7. By Vertical 20.13. Thailand 20.13.1. Pricing Analysis 20.13.2. Market Share Analysis, 2022 20.13.2.1. By Component 20.13.2.2. By Type 20.13.2.3. By Deployment Mode 20.13.2.4. By Organization Size 20.13.2.5. By Mode of Integration 20.13.2.6. By Technology 20.13.2.7. By Vertical 20.14. China 20.14.1. Pricing Analysis 20.14.2. Market Share Analysis, 2022 20.14.2.1. By Component 20.14.2.2. By Type 20.14.2.3. By Deployment Mode 20.14.2.4. By Organization Size 20.14.2.5. By Mode of Integration 20.14.2.6. By Technology 20.14.2.7. By Vertical 20.15. Japan 20.15.1. Pricing Analysis 20.15.2. Market Share Analysis, 2022 20.15.2.1. By Component 20.15.2.2. By Type 20.15.2.3. By Deployment Mode 20.15.2.4. By Organization Size 20.15.2.5. By Mode of Integration 20.15.2.6. By Technology 20.15.2.7. By Vertical 20.16. South Korea 20.16.1. Pricing Analysis 20.16.2. Market Share Analysis, 2022 20.16.2.1. By Component 20.16.2.2. By Type 20.16.2.3. By Deployment Mode 20.16.2.4. By Organization Size 20.16.2.5. By Mode of Integration 20.16.2.6. By Technology 20.16.2.7. By Vertical 20.17. Australia 20.17.1. Pricing Analysis 20.17.2. Market Share Analysis, 2022 20.17.2.1. By Component 20.17.2.2. By Type 20.17.2.3. By Deployment Mode 20.17.2.4. By Organization Size 20.17.2.5. By Mode of Integration 20.17.2.6. By Technology 20.17.2.7. By Vertical 20.18. New Zealand 20.18.1. Pricing Analysis 20.18.2. Market Share Analysis, 2022 20.18.2.1. By Component 20.18.2.2. By Type 20.18.2.3. By Deployment Mode 20.18.2.4. By Organization Size 20.18.2.5. By Mode of Integration 20.18.2.6. By Technology 20.18.2.7. By Vertical 20.19. GCC Countries 20.19.1. Pricing Analysis 20.19.2. Market Share Analysis, 2022 20.19.2.1. By Component 20.19.2.2. By Type 20.19.2.3. By Deployment Mode 20.19.2.4. By Organization Size 20.19.2.5. By Mode of Integration 20.19.2.6. By Technology 20.19.2.7. By Vertical 20.20. South Africa 20.20.1. Pricing Analysis 20.20.2. Market Share Analysis, 2022 20.20.2.1. By Component 20.20.2.2. By Type 20.20.2.3. By Deployment Mode 20.20.2.4. By Organization Size 20.20.2.5. By Mode of Integration 20.20.2.6. By Technology 20.20.2.7. By Vertical 20.21. Israel 20.21.1. Pricing Analysis 20.21.2. Market Share Analysis, 2022 20.21.2.1. By Component 20.21.2.2. By Type 20.21.2.3. By Deployment Mode 20.21.2.4. By Organization Size 20.21.2.5. By Mode of Integration 20.21.2.6. By Technology 20.21.2.7. By Vertical 21. Market Structure Analysis 21.1. Competition Dashboard 21.2. Competition Benchmarking 21.3. Market Share Analysis of Top Players 21.3.1. By Regional 21.3.2. By Component 21.3.3. By Type 21.3.4. By Deployment Mode 21.3.5. By Organization Size 21.3.6. By Mode of Integration 21.3.7. By Technology 21.3.8. By Vertical 22. Competition Analysis 22.1. Competition Deep Dive 22.1.1. Google 22.1.1.1. Overview 22.1.1.2. Product Portfolio 22.1.1.3. Profitability by Market Segments 22.1.1.4. Sales Footprint 22.1.1.5. Strategy Overview 22.1.1.5.1. Marketing Strategy 22.1.2. Microsoft 22.1.2.1. Overview 22.1.2.2. Product Portfolio 22.1.2.3. Profitability by Market Segments 22.1.2.4. Sales Footprint 22.1.2.5. Strategy Overview 22.1.2.5.1. Marketing Strategy 22.1.3. IBM 22.1.3.1. Overview 22.1.3.2. Product Portfolio 22.1.3.3. Profitability by Market Segments 22.1.3.4. Sales Footprint 22.1.3.5. Strategy Overview 22.1.3.5.1. Marketing Strategy 22.1.4. AWS 22.1.4.1. Overview 22.1.4.2. Product Portfolio 22.1.4.3. Profitability by Market Segments 22.1.4.4. Sales Footprint 22.1.4.5. Strategy Overview 22.1.4.5.1. Marketing Strategy 22.1.5. Baidu 22.1.5.1. Overview 22.1.5.2. Product Portfolio 22.1.5.3. Profitability by Market Segments 22.1.5.4. Sales Footprint 22.1.5.5. Strategy Overview 22.1.5.5.1. Marketing Strategy 22.1.6. Oracle 22.1.6.1. Overview 22.1.6.2. Product Portfolio 22.1.6.3. Profitability by Market Segments 22.1.6.4. Sales Footprint 22.1.6.5. Strategy Overview 22.1.6.5.1. Marketing Strategy 22.1.7. SAP 22.1.7.1. Overview 22.1.7.2. Product Portfolio 22.1.7.3. Profitability by Market Segments 22.1.7.4. Sales Footprint 22.1.7.5. Strategy Overview 22.1.7.5.1. Marketing Strategy 22.1.8. FIS 22.1.8.1. Overview 22.1.8.2. Product Portfolio 22.1.8.3. Profitability by Market Segments 22.1.8.4. Sales Footprint 22.1.8.5. Strategy Overview 22.1.8.5.1. Marketing Strategy 22.1.9. Artificial Solutions 22.1.9.1. Overview 22.1.9.2. Product Portfolio 22.1.9.3. Profitability by Market Segments 22.1.9.4. Sales Footprint 22.1.9.5. Strategy Overview 22.1.9.5.1. Marketing Strategy 22.1.10. Kore.ai 22.1.10.1. Overview 22.1.10.2. Product Portfolio 22.1.10.3. Profitability by Market Segments 22.1.10.4. Sales Footprint 22.1.10.5. Strategy Overview 22.1.10.5.1. Marketing Strategy 22.1.11. Conversica 22.1.11.1. Overview 22.1.11.2. Product Portfolio 22.1.11.3. Profitability by Market Segments 22.1.11.4. Sales Footprint 22.1.11.5. Strategy Overview 22.1.11.5.1. Marketing Strategy 22.1.12. Inbenta 22.1.12.1. Overview 22.1.12.2. Product Portfolio 22.1.12.3. Profitability by Market Segments 22.1.12.4. Sales Footprint 22.1.12.5. Strategy Overview 22.1.12.5.1. Marketing Strategy 22.1.13. Creative Virtual 22.1.13.1. Overview 22.1.13.2. Product Portfolio 22.1.13.3. Profitability by Market Segments 22.1.13.4. Sales Footprint 22.1.13.5. Strategy Overview 22.1.13.5.1. Marketing Strategy 22.1.14. SoundHound 22.1.14.1. Overview 22.1.14.2. Product Portfolio 22.1.14.3. Profitability by Market Segments 22.1.14.4. Sales Footprint 22.1.14.5. Strategy Overview 22.1.14.5.1. Marketing Strategy 22.1.15. Avaamo 22.1.15.1. Overview 22.1.15.2. Product Portfolio 22.1.15.3. Profitability by Market Segments 22.1.15.4. Sales Footprint 22.1.15.5. Strategy Overview 22.1.15.5.1. Marketing Strategy 22.1.16. Haptik 22.1.16.1. Overview 22.1.16.2. Product Portfolio 22.1.16.3. Profitability by Market Segments 22.1.16.4. Sales Footprint 22.1.16.5. Strategy Overview 22.1.16.5.1. Marketing Strategy 22.1.17. Solvvy 22.1.17.1. Overview 22.1.17.2. Product Portfolio 22.1.17.3. Profitability by Market Segments 22.1.17.4. Sales Footprint 22.1.17.5. Strategy Overview 22.1.17.5.1. Marketing Strategy 22.1.18. MindMeld 22.1.18.1. Overview 22.1.18.2. Product Portfolio 22.1.18.3. Profitability by Market Segments 22.1.18.4. Sales Footprint 22.1.18.5. Strategy Overview 22.1.18.5.1. Marketing Strategy 22.1.19. Kasisto 22.1.19.1. Overview 22.1.19.2. Product Portfolio 22.1.19.3. Profitability by Market Segments 22.1.19.4. Sales Footprint 22.1.19.5. Strategy Overview 22.1.19.5.1. Marketing Strategy 22.1.20. Gupshup 22.1.20.1. Overview 22.1.20.2. Product Portfolio 22.1.20.3. Profitability by Market Segments 22.1.20.4. Sales Footprint 22.1.20.5. Strategy Overview 22.1.20.5.1. Marketing Strategy 23. Assumptions & Acronyms Used 24. Research Methodology
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