Cognitive computing solutions utilize a combination of Artificial Intelligence (AI), neural networks, Machine Learning (ML), Natural Language Processing (NLP), and analytic models to solve day-to-day problems. These solutions have the ability to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues in real time. They examine large amounts of data, help simplify business processes, reduce risk, and pivot according to changing circumstances. Rising demand for cognitive solutions in both, large and small enterprises for better customer experience, is propelling the growth of the global cognitive computing market. As per the findings of a new market research report by Persistence Market Research, the worldwide cognitive computing market reached US$ 14.8 Bn in 2019, and is anticipated to exhibit a high CAGR of 23% over the forecast period of 2020 to 2030.
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Key Takeaways from Cognitive Computing Market Study
- Organizations are heavily investing in cognitive computing solutions to reduce operational costs and improve customer experience.
- Among the applications, the speech recognition segment is expected to witness high growth, owing to wide adoption in automated devices to provide voice assistance services.
- Among the regions, South Asia & Pacific is exhibiting a high growth rate, owing to growing digitalization and adoption of advanced technologies such as Artificial Intelligence (AI) and Machine Learning (ML).
- Large enterprises will continue being the primary contributors to the growth of the cognitive computing market on a global scale.
- The COVID-19 pandemic has compelled organizations to work remotely, and cognitive computing is helping critical functions to continue to operate seamlessly.
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Increasing Demand for Business Process Automation to Drive Market Growth
Over the past few decades, business architecture has evolved and helped companies shape the future of organizations. Organizations are continuously incorporating data capture technologies into their business processes. When this captured data is digitalized and automated, it eliminates the human error factor, and increases data quality and accuracy. It also saves a huge amount of time, increases efficiency and productivity, and lowers organizational and storage costs. It improves business processes and increases transparency internally. Cognitive computing solutions make use of AI techniques such as machine learning, cognitive computing, speech recognition, and natural language processing to automate business processes that are normally performed by humans. These solutions help companies transform their business networks, enhancing performance, delivering a superior user experience, and boosting service availability.
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