NLP Market Size, Market Share and Forecast | $45 billion by 2032

NLP Market Size, Market Share and Forecast | $45 billion by 2032

Overall NLP Market It stands at $14 million to date and is expected to reach $45 billion at a staggering 23% CAGR between 2022 and 2032.

With the increasing trend towards digital technology based programs all over, the demand for Natural Language Processing (NLP) is expected to rise in the forecast period. Along these lines, Apple Inc. To launch the next generation 5G infrastructure. In fact, it has announced an investment of nearly 430 billion US dollars to develop 5G for the US economy through 2026.

Also, Startup One AI launched, in May 2022, a new Natural Language Processing technology business. Venture capitalists such as Tech Aviv, Ariel Maislos, and SentinelOne Inc. and many others raised nearly 8 million US dollars to establish the company. Future Market Insights has detailed these facts along with future perspectives in its latest market study titled “Natural Language Processing (NLP) Market”.


Key Takeaways of the Natural Language Processing (NLP) Market

  • North America holds more than 50% of the market share due to the US being home to the majority of the major players.
  • Europe comes in second with nearly 40% market share as companies increasingly adopt cloud-based services.
  • The Asia Pacific region is expected to grow at the fastest rate in the Natural Language Processing (NLP) market with countries like Japan leading the way in terms of NLP adoption.
  • LATAM is expected to grow in the Natural Language Processing (NLP) market in the back part of Brazil, where more than 20% of large companies rely on machine learning and artificial intelligence.
  • The GCC governments have also seen that nearly 25% of companies are using NLP to improve customer experience.

Competitive processing

  • Askdata was acquired by SAP Se, in July 2022. The main goal is to help customers make the right choices through “natural language searches” that are driven by artificial intelligence.
  • SAP SE, in July 2021, entered into a strategic collaboration with Google Cloud to help end customers migrate critical systems to the cloud, thus stimulating existing systems. ML and Ai are posted here.
  • Inbenta, in June 2021, started a partner ecosystem to work jointly with enterprise partners who show interest in automating business processes and reshaping customer service with AI.
  • Inbenta, in October 2020, partnered with IntelePeer to provide intelligent workflows to customers.
  • Apple Inc. acquired , in May 2020, on Inductive Inc. (ML start-up) to improve Siri performance.
  • Intel, in 2020, partnered with China-based Alibaba Group Holding Ltd., and created advanced tracking technology powered by an artificial intelligence platform to meet the 2021 Tokyo Olympics.
  •, in November 2020, introduced advanced tools that work for cutting edge application development and AI. It facilitates the smoothest deployment of AI technology on private, hybrid or on-prem cloud.
  • Baidu, in December 2021, launched PCL-BAIDU Wenxin (ERNIE 3.0 Titan). It comes as the first optimized model with hundreds of billions of knowledge (the pre-training language model has 260 billion parameters). This model excels at NLG as well as NLU. Apple, in June 2022, announced plans to provide an open source PyTorch reference implementation for the Transformer architecture.

says an analyst from Future Market Insights.

How does the report unfold?

  • The research study is based on technology (auto-coding, text analytics, OCR (optical character recognition), interactive voice response, pattern and image recognition, speech analytics), by type (rule-based natural language processing, statistical natural language processing, and mixed natural language processing), by service (integration services, consulting services, maintenance services), by deployment model (on-demand and on-premises), by application (sentiment analysis, data mining, risk and threat detection, automatic summarization, content management, and logging Language, Portfolio Control, Branding and Advertising, Human Resources and Recruitment, and Vertical (Healthcare, Public Sector, Retail Sector, Media and Entertainment, Manufacturing, and others).
  • With deep learning architectures along with algorithms making significant advances in the field of speech processing and image recognition, the global Natural Language Processing (NLP) market is bound to see a bulge in the forecast period.

table of contents

1. Executive summary

1.1 Global Market Outlook

1.2 Demand Side Trends

1.3 Supply-side trends

1.4 Analysis and recommendations

1.5 Global Market: Long-term Strategies for Profitable Growth

1.6 Global Market Analysis – Key Findings

1.7 Key success factors

2. Market introduction

2.1. Market coverage/classification

2.2. Market definition/scope/constraints

3. Market background

3.1. macroeconomic factors

3.1.1. general economic prospects

3.1.2. Overview of the world’s population

3.1.3. Real GDP growth

3.1.4. Industry added value growth

3.1.5. World GDP by region

3.1.6. A profile of the global construction industry

3.1.7. World automobile production, by region

3.1.8. global energy consumption

3.2 Truck and Trailer Production Forecasts

3.3 Global refrigerated warehouse capacity: an overview

3.4. Consumer spending and refrigerated warehouses: an overview

3.5 Analysis of global manufacturing output

3.6 The demographic view

3.7 Projections of urban population growth

3.8 India Market Analysis – Key Growth Area

3.9 Predicting factors: relevance and impact

3.10. value chain


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