Conversational AI Market Expands Footprints in United States 2021-2027 || Microsoft, Oracle, IBM, Google LLC, SAP ERP, Baidu

Conversational AI Market

Latest added Conversational AI Market research study by MarketDigits offers detailed product outlook and elaborates market review till 2027. The market Study is segmented by key regions that is accelerating the marketization. At present, the market is sharping its presence and some of the key players in the study are Amazon Web Services, Inc., Microsoft, Oracle, IBM, Google LLC, SAP ERP, Baidu, Inc., Nuance, Artificial Solutions, Haptik and Creative Virtual. The study is a perfect mix of qualitative and quantitative Market data collected and validated majorly through primary data and secondary sources.

The Conversational AI market size is estimated to grow from USD 4.73 Billion in 2020 to USD 18. 5 Billion by 2027, growing at a CAGR of 21.5% during the forecast year from 2021 to 2027.

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The upcoming customer engagement through social media platforms and increasing integration of advanced AI capabilities are the major factors adding value to the conversational AI offerings, which is expected to provide opportunities for enterprises operating in various verticals in the market. The lack of accuracy in chatbots and virtual assistants is a major challenge in the conversational AI market. Moreover, the lack of awareness of conversational AI acts as a key restraining factor in the market.

COVID-19 Impact on Global Conversational AI Market

COVID-19 would have an impact on all the elements of the technology sector. The global ICT spending is estimated to decline by 4%–5% by the end of 2020. Moreover, the hardware business is predicted to have the most impact on the IT industry. Due to the slowdown of hardware supply and reduced manufacturing capacity, the IT infrastructure growth has slowed down. Businesses providing solutions and services are also expected to slow down for a short time. However, the adoption of collaborative applications, analytics, security solutions, and AI is set to increase in the remaining part of the year.

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In a short time, the COVID-19 outbreak has affected markets and customers’ behavior and has a substantial impact on economies and societies. With offices, educational institutions, and manufacturing facilities shutting down for an indefinite period; major sports and events being postponed; and work-from-home and social distancing policies in effect, businesses are increasingly looking for technologies to assist them through these difficult times. Analytics professionals, business intelligence professionals, and professionals providing expertise in more advanced analytics such as AI and ML have been called for their expertise to help executives make business decisions on how to respond to the new business challenges caused by the COVID-19 outbreak.

Driver: Increasing demand for AI-powered customer support services

In the last two to three decades, customer services mean customers looking for help from call centers, websites, emails, applications, and so on. However, with advancements in the use of AI technology, organizations are making use of conversational AI solutions to offer customer service efficiently. Today, the focus of enterprises has shifted from providing customer support services through emails or messages to AI-powered chatbots that help enterprises enhance customer experience and engagement. AI-powered chatbots use NLP technology to carry out human-like conversations and assist customers in real-time.

They help enterprises fetch business intelligence about customer preferences, opinions, and purchase behaviors, thus enabling organizations to provide proactive recommendations and more personalized experiences based on their account activity. Organizations can also leverage AI-enabled chatbots and virtual agents to automate repetitive and manual processes, such as order placement, balance inquiries, general inquiries, technical assistance, and other customer services. With the use of automation, organizations can achieve higher productivity gains with lower manpower requirements.

Restraint: Lack of awareness about conversational AI solutions

The adoption of conversational AI solutions is increasing across verticals that cater to various engagement types, including content consumption, customer services, and other productive engagements. However, consumers have limited knowledge about chatbots, virtual assistants, and digital personal assistants, as well as their benefits. For instance, India and Brazil are the biggest consumers of smartphones; however, the awareness of the benefits of technologies is less as compared to developed regions, such as Europe and North America. People are less likely to use virtual assistants because of the lack of knowledge about the use.

As a result, Small and Medium-sized Enterprises (SMEs) in these countries are reluctant to use virtual assistants for their business processes. In the next five to six years, as the market will gain traction across the globe, an increased level of awareness is expected to be witnessed even in developing regions, which would boost the adoption of conversational AI solutions.

Opportunity: Rise in customer engagement through social media platforms

Social media platforms, such as Facebook, Twitter, Telegram, Tumblr, Skype, Kik, and WeChat, have witnessed significant adoption of conversational AI solutions over the last three to four years. The growth in the adoption of social media platforms is exceptionally high in the current scenario, and it provides high growth opportunities for the deployment of smart advisors using social media platforms. A large number of users have been found spending most of their time on social media platforms. The social presence of enterprises and customer engagement go hand-in-hand for branding as well as advertising.

They help create awareness about a product via online reviews and the company’s social community. The growing use of bots by the world’s largest social media platforms has encouraged the use of conversational AI platforms to offer deployment support for chatbots and virtual agents built on these platforms over multiple social media platforms simultaneously. Users are actively engaged over these platforms through chat pop-ups by bots; thus, making it easier for companies to showcase their products or broaden their business footprint on social media. This has considerably affected the market for conversational AI, which is expected to show significant growth due to the wide-scale ecosystem of social media channels.

Challenge: Lack of accuracy in chatbots and virtual assistants

There are several conversational AI solution providers in the market that are building chatbots and virtual assistants with the help of open platforms with restricted user-specific characteristics. An API is designed for general use without encompassing any specific features. Consequently, the bots built through generalized APIs may fail to meet the expected accuracy levels. The response generated from chatbots and virtual assistants are programmed with a particular set of instructions and can only provide answers for queries that are stored in a database.

The ideal conversational AI interface should deliver answers in such a way that a user is unable to recognize whether he/she is talking to a human or a virtual assistant. Companies are working toward increasing the accuracy level of chatbots and virtual assistants by integrating advanced AI capabilities within their platform offering, as well as by solving a larger number of use cases and user queries. Chatbots and virtual assistants will take some time to obtain the required accuracy, which would be at par with humans. Thus, the lack of accuracy is acting as a challenge for the growth of the conversational AI market.

By component, the services segment is expected to account for the higher market share during the forecast period

By solution, the services segment is expected to grow at a higher CAGR during the forecast period. This growth is primarily due to the wide adoption of conversational AI solutions across major verticals for offering enhanced customer support, thereby generating demand for professional and managed services across the globe. Most of the vendors in the market provide a conversational AI platform to build applications that resolve customer queries, provide advice and recommendations using NLP, and other dialog related technologies. The conversational AI platform comprises bot builder tools to build multiple chatbots and assistants for enterprises. The services segment is sub-segmented into training & consulting, system integration & testing, and support & maintenance services. Service providers for conversational AI help in implementing intelligent automation and technology for effective customer engagement.

By deployment type, the cloud deployment segment to record the higher CAGR during the forecast period

The deployment mode in the conversational AI market includes on-premises and cloud. Deployment refers to the setting-up of an IT infrastructure with hardware, operating systems, and applications that are required to manage the IT ecosystem. Conversational AI solutions can be deployed on any one deployment mode based on security, availability, and scalability. The majority of conversational AI solutions are getting deployed on the cloud as it offers advantages, such as pay-per-use, and low installation and maintenance costs. This deployment mode is expected to show high growth in the near future.

By technology, the ML and deep learning segment to record the higher CAGR during the forecast period

The conversational AI market comprises three broad technologies, such as ML and deep learning, NLP, and ASR. Since the AI technology enables machines to perform activities as that of human beings, it has opened up enormous market opportunities across multiple application areas. One of the major advancements in AI technology has taken place in the field of deep learning, which involves using crude-simulated neurons to process data. The development in AI technology came as a requirement for different verticals, such as BFSI, healthcare and life sciences, retail and eCommerce, telecom, manufacturing, and travel and hospitality. The growth of the ML and deep learning segment is attributed to the increasing demand among enterprises to fetch critical insights from customer conversations on various platforms.

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

The conversational AI market has been segmented into five regions: North America, Europe, APAC, MEA, and Latin America. Among these regions, North America is projected to hold the largest market size during the forecast period. The key factor favoring the growth of the market in North America is the increasing demand for enhancing the customer support service to strengthen customer retention initiatives. Additionally, the rising number of players across different regions is expected further to drive the market.

The APAC region is expected to hold the fastest growth rate during the forecast period. Moreover, the conversational AI market is expected to witness considerable developments and adoption of solutions across the APAC region during the forecast period. The European region is also considered to be the second-largest in terms of market size during the forecast period. The growing demand to reduce enterprise workloads regarding customer engagement and retention is the key factor in adopting conversational AI solutions in Europe.

Key Market Players

Microsoft (US), Google (US), AWS (US), Oracle (US), IBM (US), Baidu (China), SAP (Germany), Artificial Solutions (Spain), Conversica (US), Haptik (India), Nuance (US), Rasa (Germany), Avaamo (US), (US), Solvvy (US), Pypestream (US), Inbenta (US), Rulai (US), Creative Virtual (US), (India), FIS (US), AmplifyReach (India), Interactions (US), Quosphere (US), (US), Cognigy (Germany), SoundHound (US), Kasisto (US), Mindsay (US), and Clinc (US).

Microsoft (US) caters to a broad customer base in the regions of the Americas, EMEA, and APAC. The company provides Azure Bot Services, Microsoft Bot Framework, Azure Cognitive Services, and LUIS QnA Maker. By combining Azure Bot Services, Microsoft Bot Framework, Azure Cognitive Services, and LUIS QnA Maker, the company provides a strong development environment for creating conversational interfaces. Users can develop conversational interfaces using Microsoft services and deploy them on websites, apps, Cortana, Microsoft Teams, Skype, Slack, and Facebook Messenger. The company also offers Microsoft BotBuilder SDK, an open-source offering that can be combined with the other Microsoft services in this market.

Scope of the Report

The research report categorizes the conversational AI market to forecast the revenues and analyze trends in each of the following subsegments:

Conversational AI Market: By Component

  • Platform
  • Services
    • Training and Consulting
    • System Integration and Testing
    • Support and Maintenance

Conversational AI Market: By Type

  • IVA
  • Chatbots

Conversational AI Market: By Deployment Mode

  • On-Premises
  • Cloud

Conversational AI Market: By Technology

  • ML and Deep Learning
  • NLP
  • ASR

Conversational AI Market: By Region

  • North America
  • Europe
  • APAC
  • MEA
  • Latin America

A comprehensive analysis of the market structure along with the forecast of the various segments and sub-segments of the market have been delivered through this Conversational AI market report. The market research and analysis performed in this business report assists clients to forecast investment in an emerging market, expansion of market share or success of a new product. The market is greatly transforming because of the moves of the key players & brands including developments, product launches, joint ventures, mergers & acquisitions that in turn changes the view of the global face of industry.

Table of Contents: Conversational AI Market

Part 01: Executive Summary

Part 02: Scope Of The Report

Part 03: Research Methodology

Part 04: Market Landscape

Part 05: Pipeline Analysis

Part 06: Market Sizing

Part 07: Five Forces Analysis

Part 08: Market Segmentation

Part 09: Customer Landscape

Part 10: Regional Landscape

Part 11: Decision Framework

Part 12: Drivers And Challenges

Part 13: Market Trends

Part 14: Vendor Landscape

Part 15: Vendor Analysis

Part 16: Appendix

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