Augmented Intelligence Market (By Component: Solution, Hardware, Software Platform, On-Premise, Cloud, Services; By Technology: Machine Learning, Natural Language Processing, Computer Vision , Others; By Enterprise Size: Large Enterprises, Small & Medium Enterprises; By End User: IT & Telecom, Retail & E-Commerce, BFSI, Healthcare, Manufacturing, Automotive, Others) - Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2023-2032

The global augmented intelligence market size was exhibited at USD 19.32 billion in 2022 and is projected to hit around USD 207.42 billion by 2032, growing at a CAGR of 26.79% during the forecast period 2023 to 2032.

Key Pointers:

• North American market generated for the largest revenue share in 2022.
• By Component, the cloud segment captured the highest revenue share in 2022. 
• By Technology, the machine learning segment recorded the maximum revenue share in 2022.
• By End User, the large enterprises segment contributed the biggest revenue share in 2022.

The Augmented intelligence industry is driven by increasing volume of complex business data, however, rising in adoption of advanced augmented intelligence and analytics tools, and adoption and scaling of digital initiatives.

Augmented Intelligence Market Report Scope

Market Dynamics

Driver: Increasing volume of complex business data

To analyze the data, there is a growing need for augmented intelligence technologies, such as ML and Natural Language Processing (NLP). Augmented intelligence makes it possible to analyze structured, semi-structured, and unstructured data sets available within organizations. The variety and volume of data produced are expected to considerably increase in the years to come, due to the evolution of digital technologies across business functions. This increasing volume of complex data is expected to drive the growth of the augmented intelligence market.

Restraint: Data Security Concerns

The backbone of augmented intelligence solutions, data, remains an important aspect that most organizations find difficult to manage. The inefficiency of managing exabytes and petabytes of data has increased the chances of security breaches and data losses. In today’s competitive marketplace, marketing teams require real-time and secure data to deliver an outstanding customer experience. Organizations are gathering data through multiple touchpoints and measure them virtually. Such data is used in support and communication and may include a variety of data types. These data types comprise public information, big data, and small data collected from customers. As IoT becomes more widespread, organizations will increasingly require more robust security and privacy to prevent breaches. The issue of security endangers the success of digitalization. With the growing number of IoT-enabled systems, the number of security and privacy issues will also increase, and every endpoint, gateway, sensor, and smartphone will become a potential target for hackers.

Opportunity: Increase in adoption of artificial intelligence, machine learning, and natural language processing technologies

The generation of a massive amount of data and the need to analyze it in real-time have compelled organizations to adopt new technologies, such as AI, ML, and NLP. These technologies have eased the whole process of gathering insights from data. Usually, data analysis was done through graphs and charts. To an untrained eye, the data analysis was not user-friendly, and there was a risk of misinterpretation and poor decision-making..

Challenge: Integration of Data from Data Silos

Extracting value from data has become a key requirement for companies to successfully mitigate risks, target valuable customers, and evaluate business performance. Monetizing these data assets require the availability of a sufficient amount of data. However, data consolidation from distinct data sources into meaningful information can incite various new challenges for organizations, especially centralized business enterprises. Data exchange and data ecosystem deliver tools to analyze the collected data at a centralized location and help extract and cross-check business-critical components. The development of data exchanges and data ecosystems varies based on the assumptions made in the value of the data for each customer segment. Various augmented intelligence providers offer unified data aggregation and data analytics platforms that help users in successfully aggregating and analyzing data from disparate data sources. Data exchange is a major concern for industries, such as BFSI and healthcare, which deal with individual’s confidential data. As the need for data exchange increases, it needs to be balanced with risk mitigation capabilities. With companies adopting the augmented intelligence software integrated with data security capabilities, data exchange is not expected to be a major issue in the near future.

North America to account for largest market size during the forecast period

North America is expected to have the largest market share in the augmented intelligence market. Key factors favoring the growth of the augmented intelligence market in North America include the increasing technological advancements in the region. The growing number of augmented intelligence players across regions is expected to further drive market growth.

Some of the prominent players in the Augmented Intelligence Market include:

• Salesforce.com, Inc.
• Samsung
• SAP SE
• Sisense Inc.
• TIBCO Software Inc.
• Amazon Web Services, Inc.
• International Business Machines Corporation
• Micron Technology, Inc.
• Microsoft Corporation
• QlikTech International AB

Segments Covered in the Report

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2032. For this study, Nova one advisor, Inc. has segmented the global Augmented Intelligence market.

By Component

• Solution
• Hardware
• Software Platform
• On-Premise
• Cloud
• Services

By Technology

• Machine Learning
• Natural Language Processing
• Computer Vision 
• Others

By Enterprise Size

• Large Enterprises
• Small & Medium Enterprises

By End User

• IT & Telecom
• Retail & E-Commerce
• BFSI
• Healthcare
• Manufacturing
• Automotive 
• Others

By Region

• North America
• Europe
• Asia-Pacific
• Latin America
• Middle East & Africa (MEA)