Cloud Natural Language Processing (NLP) Market Size By Product (Rule Based, Statistical, Hybrid), By Deployment Model (Public, Private, Hybrid), By Technology (Recognition, Analytics, Operational), By Application (Information Extraction, Machine Translation, Processing & Visualization, Question Answering), By End-use (BFSI, IT & Telecommunication, Defense, Government Organization, Retail & E-Commerce, Healthcare, Energy & Utility), Industry Analysis Report, Regional Outlook, Growth Potential, Competitive Market Share & Forecast, 2017 - 2024
Published Date: Nov 2017 | Report ID: GMI2202 | Authors: Ankita Bhutani, Preeti Wadhwani
Cloud Natural Language Processing (NLP) Market size was estimated to be over USD 1.5 billion in 2016 and is estimated to grow with around 17% CAGR from 2017 to 2024.
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Cloud natural language processing market is anticipated to experience substantial growth owing to the increasing investment in AI technology. AI has emerged as one of the most advanced technologies in the wide range of applications ranging from robotics to machine learning to advanced analytics. The technology assists organizations in extracting powerful insights to drive faster business decisions in e-commerce, marketing, competitive intelligence, product management and several other areas of business to close the gap between insights and action. As AI matures, vendors will shift more towards the technology along with the conventional analytics platform, which is estimated to fuel investments.
|Market Size in 2016:||1.5 Billion (USD)|
|Forecast Period:||2017 to 2024|
|Forecast Period 2017 to 2024 CAGR:||17%|
|2024 Value Projection:||6 Billion (USD)|
|Historical Data for:||2013 to 2016|
|No. of Pages:||230|
|Tables, Charts & Figures:||390|
|Segments covered:||Product, Deployment Model, Technology, Application, End-use and Region|
|Pitfalls & Challenges:|
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The investment landscape is led by the digital native companies and tech giants such as Google, Baidu, Amazon and Apple. They are collectively investing billions of dollars in a wide range of AI applications ranging from robotics, machine learning, virtual assistance technology, autonomous vehicles, natural language and computer vision. Internal investments by the technology companies in R&D for enhancing AI capabilities accounts for a major share in the investment in AI. For instance, Google and Baidu have invested approximately USD 20 billion in AI in 2016.
Cloud NLP Market, By Product
The statistical cloud NLP market dominated the global business landscape in 2016 owing to its advanced features and benefits over the conventional methods. Statistical method leverages advanced machine learning algorithms to develop statistical models from bilingual parallel corpora that assist in the precise and rapid translation. Whereas, rule based rule based methods requires human effort to prepare rule and linguistic resources such as syntactic parsers, part of speech taggers, and transfer rules for translation. Furthermore, statistical method is data driven and can handle ambiguity effectively, which makes it an ideal choice for natural language processing solutions.
Cloud NLP Market, By Deployment Model
Public cloud NLP market is analyzed to be the leading deployment model owing to the low cost and scalability offered by the public cloud deployment. On the other hand, hybrid cloud is estimated to witness high growth at over 19% CAGR during the forecast timeline as it offers benefits of both public and private cloud models.
The need for an effective predictive technology and low adoption of the teasdchnology are the major constraints in the cloud NLP market growth. The growing adoption of the technology among media and entertainment, advertisement, and healthcare organizations are estimated to develop myriad growth opportunities for the market.
Cloud NLP Market, By Technology
Recognition technology is estimated to account for major share in the global cloud NLP market owing to wide spread adoption of the image recognition, interactive voice recognition and optical character recognition technology among large and small enterprises for machine translation and information extraction. Furthermore, growing demand of recognition technology among organizations to capture and analyze customer voice for enhancing customer experience and automation is also estimated to back the growth of the recognition technology.
Cloud NLP Market, By Application
Machine translation is the dominating application as it is the most essential component of the NLP solution that converts text and speech inputs from one language to another. Furthermore, increasing requirement of localizing content into more languages is also estimated to fuel the demand. In addition, need for high speed translation and cost effectiveness is also contributing significantly towards the growth of the cloud NLP market.
Cloud NLP Market, By End-use
BFSI sector is the leading end-user of the cloud NLP market solutions. Financial institutes are leveraging the technology for text mining, cross boarder payments, solving insurance queries, foreign exchange, and many other applications. Furthermore, these solutions are also widely used by financial institutes in contact centers for processing customer voice and documentation. For instance, Citibank utilizes NLP in biometric security applications and for text mining. SAS, Fuji Xerox and Nuance Communications are the major vendors that are catering to this industry.
Cloud NLP Market, By Region
U.S. is estimated to be the leading regional segment in the global cloud NLP market owing to the presence of the large number of players. Increasing investment in the AI technology is also estimated to be one of the major factor backing the growth of the market. Furthermore, rapid adoption of the smart device is also estimated to contribute significantly towards the growth.
Competitive Market Share
Major vendors in the cloud NLP market are Google, Microsoft, Amazon Web Services, Apple Inc., IBM, HPE, SAP SE, and Nuance Communication, Baidu, Dolbey Systems, Facebook, Netbase Solutions, Fuji Xerox, Lexalytics, SAS, and Verint systems. Product launch and strategic acquisition are analyzed to be the most common strategies used by the players to gain share and cater to the need of the market. For instance, in March 2017, Google acquired Kaggle, a data scientist community, to strengthen its position in data science and machine learning. Similarly, in July 2017, Facebook launched new messenger platform 2.1 in the market with several additional features such as built-in natural language processing, payment SDK, and global beta.
Cloud NLP Industry Background
Growing demand of the Big Data and IoT technology is analyzed to be the major factors augmenting the growth of the industry. NLP is widely used with IoT and Big data technology to analyze data and drive useful insights. The growing adoption of these technologies will result in the new type of analytics to drive new business insights, which is estimated to drive the cloud NLP market among various industry sectors.
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