The global natural language processing market size was worth USD 13.5 billion in 2021. It is estimated to reach an expected value of USD 91 billion by 2030, growing at a CAGR of 27% during the forecast period (2022–2030).
Natural language processing (NLP) is a well-known feature of artificial intelligence that is being implemented universally through consumer digital assistants and chatbots as well as commercial applications in the fields of textual analysis, sentimental analysis, voice sense (speech analysis), and change impact analysis. Deep learning architectures and algorithms have made remarkable strides in image identification and audio processing in recent years.
NLP has experienced significant growth in recent years due to affordable, scalable computing power, a rise in data digitalization, and the convergence of NLP with deep learning (DL) and machine learning (ML). The rise of the studied market is primarily attributable to the increasing usage of natural language processing in healthcare and contact centers, the rising demand for advanced text analytics, and the expansion of machine-to-machine technologies.
|Market Size||USD 91 billion by 2030,|
|Fastest Growing Market||Europe|
|Largest Market||North America|
|Report Coverage||Revenue Forecast, Competitive Landscape, Growth Factors, Environment & Regulatory Landscape and Trends|
Internet usage and ever-expanding communication, consumption, and interaction channels have empowered consumers. Businesses have been compelled to reconsider their branding and business practices. Attracting clients from competitors in today's competitive market requires more than the dominating product-centric or company-centric paradigm. Numerous channels allow businesses to employ AI-powered chatbots adept at handling inquiries. In certain instances, they can anticipate a customer's next move and preempt inquiries through proactive contact. Customer engagement suppliers are introducing artificial intelligence (AI) capabilities into their platforms to enable end users to develop scalable, personalized customer experiences without the need for human programming or logic construction. These factors lead to the expansion of the market.
The increasing use of digital technology in healthcare organizations has led to the generation of large amounts of data. To acquire data insights, it is critical to process data efficiently. As a result, analytics-driven approaches for quickly analyzing massive amounts of data are becoming more popular. Furthermore, due to the vast amount of patient data and electronic health records, the healthcare sector has employed new technology to evaluate, search, and interpret large volumes of patient data. Consequently, the increasing demand from the healthcare sector will likely contribute to the growth of the national language processing market over the forecast period.
Transitioning from an existing legacy system to SaaS platforms is a costly endeavor requiring technical and non-technical personnel and other obstacles. In addition, a lack of understanding of cloud computing migration results in numerous migration errors that hinder the achievement of organizational objectives. According to independent estimates, about 71% of the IT budget slated for the US federal civilian agencies may be spent on maintaining legacy systems in the future. This indicates that organizations are still relying on the existing legacy systems and are not keen on shifting to modern analytics software, which restricts the growth of the market studied.
Many organizations face the problem of modernizing their existing software systems and migrating to more capable systems. Updating legacy software systems is a complex engineering problem, which includes most aspects of traditional software development with more constraints. About 50% of organizations cite legacy systems as the most significant barrier to realizing their digital goals. Thus, obstacles associated with the modernization of existing legacy systems and the high cost of software migration are impeding the growth of the investigated market.
Cognitive technology is the next generation of artificial intelligence used to enhance the end-user Industry application-based utility. It is used for developing new projects for cognitive computing. In the business-level context, AI can support automating business processes, gaining insights through data analysis, and engaging with customers and employees.
According to the finding of a study carried out by the Harvard Business Review, cognitive technologies (152); robotics, cognitive automation, and cognitive insights (57); cognitive engagement (24); and cognitive insights provided by machine learning differed from those available from traditional analytics in three ways: (i) they are more data-intensive and detailed; (ii) the models typically are trained on some part of the data set; (iii) and the models get better, which means that their ability to use new data to make predictions or put things into categories improves over time. SEB bank in Sweden, and the medical technology giant Becton, Dickinson, and Company, in the United States are using the lifelike intelligent-agent avatar, Amelia, to serve as an internal employee help desk for IT support. Such instances create immense potential for market growth.
By region, the global natural language processing market is segmented into North America, Europe, Asia-Pacific, and the Rest of the World.
North America accounted for the largest market share and is expected to grow at a CAGR of 27.1% during the forecast period. North America is among the leading markets for natural language processing due to its dominance in AI and ML technologies. Most of the major vendors in the market are based in the US, which gives the region an innovation advantage. Additionally, the regional governments are increasingly encouraging the adoption of AI, ML, and NLP technologies, developing the space for market vendors to expand their presence in the region. Companies are also trying to expand their footprint in Canada through their merger and acquisition (M&A) strategies, owing to the increasing potential in the country. For instance, Inspirata acquired Artificial Intelligence in Medicine Inc. (AIM), a Toronto-based company, to extend its foothold in the country and strengthen its position in the market.
Europe is the second largest region and is expected to reach a market value of USD 23 billion by 2030, growing at a CAGR of 26.4%. The UK, Germany, and France have some of the significant markets in the region. The improved focus and increased spending on IT infrastructure are expected to drive the growth of the NLP market in the UK. The government has also laid high emphasis on new software. France is increasing its focus on developing artificial intelligence through regular investments, attracting new consumers. This will likely have a positive impact on the growth of the NLP market. Moreover, companies such as Facebook and Google are planning to invest in expanding and creating new facilities related to AI in Paris, bolstering the adoption of NLP.
Asia-Pacific is among the most promising regions for the natural language processing business. The region is experiencing increased usage of AI and ML technologies, particularly among SMBs. The voice assistance business is also developing in Asia, which is home to numerous consumer electronics producers, including smart speakers and smartphones. The regional dominance in the global semiconductor industry also helps the companies gain a position in the NLP market, as many NLP chips and hardware manufacturers are Asia-based.
The global natural language processing market is segmented by deployment, organization size, type, processing type, end-user, and region.
By deployment, the global market is segmented into On-premise and Cloud.
The On-premise segment occupies the most significant market share and is expected to grow at a CAGR of 23.5% over the forecast period. Organizations across various industries see on-premise deployment as a mode with high upfront capital expenses. However, data security is one of the prime factors forcing these organizations to invest in the on-premise model. With the growth of AI-based NLP and sentiment analysis, document volumes have also increased; hence, shifting to an on-premise solution helps cut costs and gain control over the software, from low-level syntactic analysis to high-level contextual extraction. Additionally, sensitive to latency, organizations prefer the on-premise model, as the latency rate in the cloud is approximately 200 milliseconds, compared to 5-10 milliseconds in the on-premise model.
By organization size, the global natural language processing market is segmented into Large Organizations and Small & Medium Organizations.
Small & Medium Organizations occupy the most significant market share, and it is expected to grow at a CAGR of 26% over the forecast period. The rising cloud adoption among SMEs has made it easier for enterprises to utilize other technologies, like AI and ML. Therefore, the increasing adoption of AI and ML technologies among SMEs is also driving demand for the NLP market. A survey conducted by Vistage regarding the role of AI for small businesses revealed that 13.6% of SMBs currently use AI technologies to enhance their customer engagement and business operations.
By type, the global natural language processing market is segmented into Hardware, Software, and Services.
The Hardware segment occupies the largest market share and is expected to grow at a CAGR of 21.9% over the forecast period. Deep neural networks have radically transformed the NLP in the last decade, primarily through their application in data centers using specialized hardware. MIT researchers added the parallel hardware architecture with fully-pipelined data for complementing the anticipated software for assisting the real-time cascading. Further, the increasing technological innovations in chip manufacturing are also expected to bring development and new applications into the market studied. For instance, the recently launched AI chip, Ascend 910 by Huawei Technologies, has a maximum power consumption of just 310W. Additionally, with the introduction of a tensor processing unit (TPU) by Google, the investment in the studied segment is expected to increase over the forecast period.
By processing type, the global natural language processing market is segmented into Text, Speech/Voice, and Image.
The Text processing segment occupies the largest market share and is expected to grow at a CAGR of 23.4% over the forecast period. Organizations increasingly use text analytics technologies to aid their business-making process by offering actionable insights from various text sources, such as client interaction, emails, blogs, product reviews, tweets, and center logs. Increasing advancements in analytics for a quality management process, to enhance efficiency and customer experience, omnichannel capabilities, for firms to grow their reach to millennial and Gen Z customers, and an increasing number of organizations complying with the European Union's General Data Protection Regulation (GDPR) privacy directive are some of the significant factors fueling the adoption of text analytics solutions and technologies.
By end-user, the global market is segmented into Education, BFSI, Healthcare, IT & Telecommunication, Media & Entertainment, Retail, Manufacturing, and Others.
The IT & Telecommunication segment occupies the most significant market share and is expected to grow at a CAGR of 26.1% over the forecast period. Increasing adoption of 5G and IoT may lead to a massive generation of vast amounts of data. To efficiently manage these data, IT enterprises are facing an increasing need for data-driven solutions. With growing product enhancement in the market studied, these problems are expected to be minimized. The telecom sector is further set to leverage the smart home market uptake by improving hardware and software network technologies. To enhance the smart home experience, the focus may also be directed toward AI-based NLP devices. Both Orange and Telefónica launched multi-service virtual assistants, Djingo and Aura, respectively, to compete with the likes of Amazon's Echo and Google's Home devices. All these factors are expected to positively contribute to the growth of the NLP market in the IT and telecom sector.