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Conversational AI Market 2021 – Explained Effective Movements | Microsoft, Oracle, IBM, Google LLC, SAP ERP, Baidu, Nuance

Conversational AI Market

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.

The “Conversational AI – Market Analysis, Trends, and Forecasts 2021-2027 ” Study has been added to MarketDigits Market Research offering. The study focus on both qualitative as well as quantitative side and follows Industry benchmark and NAICS standards to built coverage of players for final compilation of study. Some of the major and emerging players profiled are Amazon Web Services, Inc., Microsoft, Oracle, IBM, Google LLC, SAP ERP, Baidu, Inc., Nuance, Artificial Solutions, Haptik and Creative Virtual.

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Scroll down 100s of data Tables, charts and graphs spread through Pages and in-depth Table of Content on “Conversational AI Market, By Technology (Machine Learning & Deep Learning, Natural Language Processing, ASR), Component (Platform, Services), Type (IVA and Chatbots) Application, Deployment Mode (Cloud and On-premises), Vertical – Global Forecast to 2027”. Early buyers will get 10% customization on study.

To Avail deep insights of Conversational AI Market Size, competition landscape is provided i.e. Revenue Analysis (M $US) by Company (2018-2020), Segment Revenue Market Share (%) by Players (2018-2020) and further a qualitative analysis is made towards market concentration rate, product/service differences, new entrants and the technological trends in future.

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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.

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.

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.

Market Dynamics

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), Kore.ai (US), Solvvy (US), Pypestream (US), Inbenta (US), Rulai (US), Creative Virtual (US), Saarthi.ai (India), FIS (US), AmplifyReach (India), Interactions (US), Quosphere (US), Exceed.ai (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

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

Recent Developments:

  • In June 2020, Google Cloud announced that it signed a Memorandum of Understanding (MoU) with UK Crown Commercial Service (CCS). The MoU intends to make it easier and more affordable for the UK public sector agencies to leverage the full range of Google Cloud’s services to increase innovation and deliver digital transformation.
  • In June 2020, Microsoft and SAS announced an extensive technology and go-to-market strategic partnership. The two companies will enable customers to easily run their SAS workloads in the cloud, expanding their business solutions and unlocking critical value from their digital transformation initiatives. As part of the partnership, the companies will migrate SAS’ analytical products and industry solutions onto Microsoft Azure as the preferred cloud provider for the SAS Cloud.
  • In July 2019, Microsoft and OpenAI, two companies thinking deeply about the role of AI in the world and how to build secure, trustworthy, and ethical AI to serve the public, have partnered to further extend Microsoft Azure’s capabilities in large-scale AI systems. Through this partnership, the companies will accelerate breakthroughs in AI and power OpenAI’s efforts to create artificial general intelligence (AGI). The resulting enhancements to the Azure platform will also help developers build the next generation of AI applications.
  • In June 2019, Microsoft and Oracle announced a cloud interoperability partnership enabling customers to migrate and run mission-critical enterprise workloads across Microsoft Azure and Oracle Cloud. Enterprises can now seamlessly connect Azure services, like Analytics and AI, to Oracle Cloud services, like Autonomous Database. By enabling customers to run one part of a workload within Azure and another part of the same workload within the Oracle Cloud, the partnership delivers a highly optimized, best-of-both-clouds experience. Taken together, Azure and Oracle Cloud offer customers a one-stop-shop for all the cloud services and applications they need to run their entire business.
  • In May 2019, Microsoft announced a new set of Azure AI technology aimed to help developers and data scientists apply AI to any solution. These technologies include – Azure Cognitive Services, MLOps capabilities, Automated ML advancements, and Visual machine learning interface, among others.
  • In January 2019, IBM signed a multi-year service agreement with Bank of the Philippine Islands for USD 260 million. In accordance with this agreement, IBM would provide IT infrastructure services to accelerate the digital transformation of Bank of the Philippine Islands.
  • In November 2018, Microsoft signed an agreement to acquire XOXCO, a solution provider for conversational AI and bot development. This acquisition would help Microsoft strengthen its initiative to offer accessible software tools to developers for enabling them to create and deploy conversational interfaces across platforms.

All viewpoints in the report are based on iterative validation by engaging influencer, experts of the market, whose opinions supersede all other research methodologies. Both primary and secondary approach are used and detailed product portfolio / service offering were analysed and have been presented in a separate chapter of competitive landscape along with company profile.

Detailed Insights on Market Concentration Rate:

CR4, CR8 and HHI Index Analysis of Overall Market

Comparative Market Share Analysis (Y-o-Y)

Major Companies

Emerging Players – Heat Map Analysis

MarketDigits MR also offers Custom Research services providing focused, comprehensive and tailored research according to clientele objectives. Thanks for reading this article; you can also get individual chapter wise section or region wise report like North America, Europe or Asia.

Table of Contents

1 Market Overview

1.1 Global Conversational AI Introduction

1.2 Market Analysis by Type

1.3 Market Analysis by Applications

1.4 Market Analysis by Regions

1.5 Market Dynamics

1.5.1 Market Opportunities

1.5.2 Market Risk

1.5.3 Market Driving Force

2 Manufacturers Profiles

2.1.1 Business Overview

2.1.2 Conversational AI Type and Applications

2.1.3 Conversational AI Sales, Price, Revenue, Gross Margin and Market Share (2021-2027)

3 Global Conversational AI Market Competition, by Manufacturer

4 Global Conversational AI Market Analysis by Regions

5 Region 1, Type, Application and Manufacturers

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10 Global Conversational AI Market Segment by Type

11 Conversational AI Market Segment by Application

12 Conversational AI Market Forecast (2021-2027)

13 Sales Channel, Distributors, Traders and Dealers

14 Research Findings and Conclusion

15 Appendix

….Continued

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