The Human-Centered AI Market Size was valued at USD 8.2 billion in 2023 and is expected to reach USD 39.5 billion by 2031 and grow at a CAGR of 21.6 % over the forecast period 2024-2031.
The growing desire for user-friendly and ethical artificial intelligence. and a strong demand for Personalization. also, the overall adoption of AI in businesses, these factors are fueling the growth of this market. The global enterprise AI market is expected to reach $1.5 trillion by 2030, this creates a vast opportunity for HCAI solutions. Now a days, Customers are increasingly expect companies to tailor their experiences, and HCAI offers a way to achieve this effectively. Finally, there's a growing focus on ethical AI development. As concerns about bias and fairness in AI rise, HCAI offers a solution by prioritizing transparency and user well-being in the design and implementation of AI systems. the HCAI market presents exciting opportunities also.
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The rise of AI-powered customer service is a prime example. HCAI can create more natural and effective interactions between customers and businesses, leading to higher satisfaction rates. The potential for Personalization in education and healthcare is also significant. HCAI can tailor learning experiences to individual students and provide more targeted healthcare solutions, ultimately improving outcomes for patients. Additionally, HCAI can augment human workforce by automating repetitive tasks, freeing up human employees to focus on more creative and strategic work.
KEY DRIVERS:
Concerns about bias and fairness in AI are driving the demand for HCAI solutions that are transparent and accountable.
Growing User Demand for Personalized Experiences
Consumers crave experiences tailored to their preferences. HCAI offers a way to personalize interactions across various industries, leading to higher engagement and satisfaction. A PWC survey found that 73% of customers expect companies to use their data to personalize interactions. HCAI caters to this need.
RESTRAINTS:
The lack of professionals with expertise in both AI and human-centered design creates a hurdles in HCAI development and implementation.
Data Privacy Concerns remains crucial for both users as well as for company.
Consumers are increasingly wary about how their data is collected and used by AI systems. This creates a need for robust privacy measures in HCAI solutions.
OPPORTUNITIES:
Personalized Education & Healthcare solutions, ultimately improving outcomes for individuals.
Augmented Human Workforce creates immense opportunity
HCAI can automate repetitive tasks, freeing up human workers to focus on more strategic and creative aspects of their jobs, increasing overall productivity.
CHALLENGES:
Striking the right balance between automation and human oversight is crucial.
Transparency and Fairness
Building trust in HCAI systems necessitates clear communication about their functionalities and the data they utilize. This ensures users understand how these systems operate and feel confident in their interactions with them.
Sanctions and logistical barriers have disrupted the flow of critical components, such as semiconductors, essential to building an AI device. This can delay the development and deployment of HCAI products. In addition, the increased risk of cyber warfare puts sensitive data used in HCAI applications at greater risk. In April 2023, the Cyber Security and Infrastructure Agency (CISA) warned of potential attacks against critical infrastructure, including healthcare systems, that could exploit HCAI tools. and according to Check Point Research, cyber attacks worldwide increased by 38% in the first quarter of 2023 compared to the same period in 2022, underscoring the heightened threat landscape. The war therefore underscores the importance of strong cybersecurity measures. HCAI can be used to develop more advanced threat detection and prevention systems to protect critical infrastructure and sensitive data. also emphasized the need for robust telehealth solutions. HCAI can help develop advanced telehealth platforms that provide medical care in conflict zones or areas with limited access to health services.
A KPMG report predicts a significant drop in global GDP growth from a pre-war forecast of 4.1% to 3.2% in 2023. This economic uncertainty can lead to tightened budgets, with businesses potentially delaying or scaling back investments in new technologies like HCAI. Consumer spending might also dip due to the slowdown, impacting industries that heavily rely on HCAI for Personalization and marketing. This could particularly affect sectors like retail and e-commerce, which utilize HCAI for targeted advertising and product recommendations. Furthermore, a Randstad survey in March 2023 found that over 40% of businesses planned to freeze hiring due to the economic slowdown. This could exacerbate the already limited pool of professionals with expertise in both AI and human-centered design, hindering HCAI development. While consumer-facing applications like those in retail, financial services, and travel & hospitality might be most affected due to reduced spending and travel, the economic slowdown can also present opportunities for the HCAI market.
By Function
Decision-Making & Support
Workflow Automation
Safety and Security
Assistance and Support
Collaboration and Others
Based on function It is segmented, into assistance and support, security, decision and support, workflow automation, collaboration, and others. The Assistance and support segment has the largest share of the market. AI help and support systems can help organizations improve customer service by providing 24/7 help, answering questions and solving problems. also, AI can be used to automate processes such as appointment scheduling, customer information management, and product recommendations. This allows employees to focus on more complex functions, such as providing personalized customer support.
By Application
Chatbots and Virtual Assistants
Medical Diagnostic
Quality Control
Personalized Learning
Fraud Detection & Risk Assessment
Human Resources
Based on Application Chatbots and virtual assistants holds the largest market share. In today's digital world, customers expect constant accessibility. Chatbots and virtual assistants offer a solution, providing customer care around the clock, 365 days a year. This is especially valuable for organizations transitioning to a digital-first approach, where immediate responses are crucial. Chatbots and virtual assistants excel at handling repetitive tasks that free up human employees for more strategic work. Appointment scheduling, answering frequently asked questions, and even basic problem resolution can be automated by these AI-powered tools. This allows human workers to focus on complex issues requiring personalized attention and empathy.
AI can streamline the recruitment process by screening resumes, scheduling interviews, and even conducting initial assessments. This frees up HR professionals to focus on attracting top talent and fostering positive candidate experiences. also, AI can personalize training programs by analyzing individual strengths and weaknesses. This targeted approach can lead to more effective learning outcomes and improved employee performance.
By End User
Retail & E-commerce
Healthcare
Automobile
Education
Transportation & Logistics
Manufacturing
North America holds a leading position in the Human-Centered AI (HCAI) market. This dominance can be attributed to the region's pioneering role in adopting AI technology. Early recognition of AI's potential fueled significant investment in research and development (R&D). also, North America boasts a robust ecosystem for AI innovation, characterized by a high concentration of AI companies and research organizations. This strong focus on R&D is evident in the huge number of players in the AI space, along with substantial financial backing from both governments and businesses. HCAI is proving its worth across various applications in North America. Businesses are leveraging it to elevate customer service experiences, personalize product recommendations for individual users, and optimize inventory management for greater efficiency. A prime example is Amazon's use of AI to suggest products tailored to each customer's preferences. This highlights how HCAI is transforming user experiences and driving business success in North America.
The Asia Pacific Human-Centered AI market is growing with the highest growth rate. Also this region boasts several economic giants like China, Japan, and South Korea, which are investing heavily in AI research and development (R&D). This financial muscle fuels innovation and fosters a dynamic HCAI ecosystem. The APAC region has a high mobile phone penetration rate, fostering a mobile-first approach to technology adoption. This creates a fertile ground for HCAI applications tailored for mobile devices, such as chatbots for customer service and voice assistants for personalized interactions. according to a data there are Number of smartphone users globally in 2023 which is approx 6.6 billion, this Increased smartphone usage drives demand for personalized mobile experiences across the region. also, A strong manufacturing base in several APAC countries makes HCAI particularly valuable for optimizing production processes, streamlining supply chains, and improving quality control. This focus on automation and efficiency creates a significant demand for HCAI solutions. for Eg. AI-powered tutoring platforms are being implemented to personalize learning experiences for students in South Korea.
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REGIONAL COVERAGE:
North America
US
Canada
Mexico
Europe
Eastern Europe
Poland
Romania
Hungary
Turkey
Rest of Eastern Europe
Western Europe
Germany
France
UK
Italy
Spain
Netherlands
Switzerland
Austria
Rest of Western Europe
Asia Pacific
China
India
Japan
South Korea
Vietnam
Singapore
Australia
Rest of Asia Pacific
Middle East & Africa
Middle East
UAE
Egypt
Saudi Arabia
Qatar
Rest of the Middle East
Africa
Nigeria
South Africa
Rest of Africa
Latin America
Brazil
Argentina
Colombia
Rest of Latin America
The major key players are Accenture, IBM Corporation, Sentient Technologies, Microsoft Corporation, Google LLC, Nuance Communications, Cognizant, Amazon Inc., Apple Inc., OpenAI, NVIDIA Corporation, Salesforce Inc., Affectiva, BenevolentAI and Zebra Technologies. and other key players.
In May 12, 2024, IBM announced a collaboration with healthcare provider Mayo Clinic to develop HCAI solutions for personalized medicine. This initiative aims to leverage AI to analyze patient data and generate more tailored treatment plans.
In May 25, 2024, Google is expected to host its annual Google I/O developer conference. Announcements related to advancements in its HCAI projects like Project LaMDA, a conversational AI system focused on human-like interactions, are a potential highlight.
In May 18, 2024, Microsoft unveiled its new Azure Cognitive Services for Customer Service, a suite of HCAI tools designed to enhance customer interactions. These tools include AI-powered chatbots and virtual assistants for personalized support and sentiment analysis to understand customer emotions.
| Report Attributes | Details |
|---|---|
| Market Size in 2023 | US$ 8.2 Billion |
| Market Size by 2031 | US$ 39.5 Billion |
| CAGR | CAGR of 21.6% From 2024 to 2031 |
| Base Year | 2023 |
| Forecast Period | 2024-2031 |
| Historical Data | 2020-2022 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Function (Decision-Making & Support, Workflow Automation, Safety And Security, Assistance And Support, Collaboration And Others) • By Application (Chatbots And Virtual Assistants, Medical Diagnostic, Quality Control, Personalized Learning, Fraud Detection & Risk Assessment, And Human Resources) • By End User (Retail & E-Commerce, Healthcare, Automobile, Education, Transportation & Logistics, Manufacturing) |
| Regional Analysis/Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia, Rest of Latin America) |
| Company Profiles | Accenture, IBM Corporation, Sentient Technologies, Microsoft Corporation, Google LLC, Nuance Communications, Cognizant, Amazon Inc., Apple Inc., OpenAI, NVIDIA Corporation, Salesforce Inc., Affectiva, BenevolentAI and Zebra Technologies |
| Key Drivers | • Concerns about bias and fairness in AI are driving the demand for HCAI solutions that are transparent and accountable. • Growing User Demand for Personalized Experiences |
| Challenges | • Striking the right balance between automation and human oversight is crucial. • Transparency and Fairness |
Ans: The Human-Centered AI market is expected to grow at a CAGR of 21.6%.
Ans: Human-Centered AI market size was USD 8.2 billion in 2023 and is expected to Reach USD 39.5 billion by 2031.
Ans: Demand for Personalized Experiences, AI Adoption in Enterprises and, Focus on Ethical AI Development
Ans: Collaborations between healthcare providers and tech companies to develop HCAI solutions for personalized medicine., Advancements in AI-powered customer service tools for enhanced customer interactions. And, Development of conversational AI systems focused on natural and human-like interactions.
Ans: Human-AI Collaboration, Mitigating Algorithmic Bias and, Transparency and Fairness.
TABLE OF CONTENTS
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Industry Flowchart
3. Research Methodology
4. Market Dynamics
4.1 Drivers
4.2 Restraints
4.3 Opportunities
4.4 Challenges
5. Impact Analysis
5.1 Impact of Russia-Ukraine Crisis
5.2 Impact of Economic Slowdown on Major Countries
5.2.1 Introduction
5.2.2 United States
5.2.3 Canada
5.2.4 Germany
5.2.5 France
5.2.6 UK
5.2.7 China
5.2.8 Japan
5.2.9 South Korea
5.2.10 India
6. Value Chain Analysis
7. Porter’s 5 Forces Model
8. Pest Analysis
9. Human-Centered AI market Segmentation, By Function
9.1 Introduction
9.2 Trend Analysis
9.3 Decision-Making & Support
9.4 Workflow Automation
9.5 Safety and Security
9.6 Assistance and Support
9.7 Collaboration and Others
10. Human-Centered AI market Segmentation, By Application
10.1 Introduction
10.2 Trend Analysis
10.3 Chatbots and Virtual Assistants
10.4 Medical Diagnostic
10.5 Quality Control
10.6 Personalized Learning
10.7 Fraud Detection & Risk Assessment
10.8 Human Resources
11. Human-Centered AI market Segmentation, By End-User
11.1 Introduction
11.2 Trend Analysis
11.3Retail & E-commerce
11.4 Healthcare
11.5 Automobile
11.6 Education
11.7 Transportation & Logistics
11.8 Manufacturing
12. Regional Analysis
12.1 Introduction
12.2 North America
12.2.1 Trend Analysis
12.2.2 North America Human-Centered AI market by Country
12.2.3 North America Human-Centered AI market By Function
12.2.4 North America Human-Centered AI market By Application
12.2.5 North America Human-Centered AI market By End-User
12.2.6 USA
12.2.6.1 USA Human-Centered AI market By Function
12.2.6.2 USA Human-Centered AI market By Application
12.2.6.3 USA Human-Centered AI market By End-User
12.2.7 Canada
12.2.7.1 Canada Human-Centered AI market By Function
12.2.7.2 Canada Human-Centered AI market By Application
12.2.7.3 Canada Human-Centered AI market By End-User
12.2.8 Mexico
12.2.8.1 Mexico Human-Centered AI market By Function
12.2.8.2 Mexico Human-Centered AI market By Application
12.2.8.3 Mexico Human-Centered AI market By End-User
12.3 Europe
12.3.1 Trend Analysis
12.3.2 Eastern Europe
12.3.2.1 Eastern Europe Human-Centered AI market by Country
12.3.2.2 Eastern Europe Human-Centered AI market By Function
12.3.2.3 Eastern Europe Human-Centered AI market By Application
12.3.2.4 Eastern Europe Human-Centered AI market By End-User
12.3.2.5 Poland
12.3.2.5.1 Poland Human-Centered AI market By Function
12.3.2.5.2 Poland Human-Centered AI market By Application
12.3.2.5.3 Poland Human-Centered AI market By End-User
12.3.2.6 Romania
12.3.2.6.1 Romania Human-Centered AI market By Function
12.3.2.6.2 Romania Human-Centered AI market By Application
12.3.2.6.4 Romania Human-Centered AI market By End-User
12.3.2.7 Hungary
12.3.2.7.1 Hungary Human-Centered AI market By Function
12.3.2.7.2 Hungary Human-Centered AI market By Application
12.3.2.7.3 Hungary Human-Centered AI market By End-User
12.3.2.8 Turkey
12.3.2.8.1 Turkey Human-Centered AI market By Function
12.3.2.8.2 Turkey Human-Centered AI market By Application
12.3.2.8.3 Turkey Human-Centered AI market By End-User
12.3.2.9 Rest of Eastern Europe
12.3.2.9.1 Rest of Eastern Europe Human-Centered AI market By Function
12.3.2.9.2 Rest of Eastern Europe Human-Centered AI market By Application
12.3.2.9.3 Rest of Eastern Europe Human-Centered AI market By End-User
12.3.3 Western Europe
12.3.3.1 Western Europe Human-Centered AI market by Country
12.3.3.2 Western Europe Human-Centered AI market By Function
12.3.3.3 Western Europe Human-Centered AI market By Application
12.3.3.4 Western Europe Human-Centered AI market By End-User
12.3.3.5 Germany
12.3.3.5.1 Germany Human-Centered AI market By Function
12.3.3.5.2 Germany Human-Centered AI market By Application
12.3.3.5.3 Germany Human-Centered AI market By End-User
12.3.3.6 France
12.3.3.6.1 France Human-Centered AI market By Function
12.3.3.6.2 France Human-Centered AI market By Application
12.3.3.6.3 France Human-Centered AI market By End-User
12.3.3.7 UK
12.3.3.7.1 UK Human-Centered AI market By Function
12.3.3.7.2 UK Human-Centered AI market By Application
12.3.3.7.3 UK Human-Centered AI market By End-User
12.3.3.8 Italy
12.3.3.8.1 Italy Human-Centered AI market By Function
12.3.3.8.2 Italy Human-Centered AI market By Application
12.3.3.8.3 Italy Human-Centered AI market By End-User
12.3.3.9 Spain
12.3.3.9.1 Spain Human-Centered AI market By Function
12.3.3.9.2 Spain Human-Centered AI market By Application
12.3.3.9.3 Spain Human-Centered AI market By End-User
12.3.3.10 Netherlands
12.3.3.10.1 Netherlands Human-Centered AI market By Function
12.3.3.10.2 Netherlands Human-Centered AI market By Application
12.3.3.10.3 Netherlands Human-Centered AI market By End-User
12.3.3.11 Switzerland
12.3.3.11.1 Switzerland Human-Centered AI market By Function
12.3.3.11.2 Switzerland Human-Centered AI market By Application
12.3.3.11.3 Switzerland Human-Centered AI market By End-User
12.3.3.1.12 Austria
12.3.3.12.1 Austria Human-Centered AI market By Function
12.3.3.12.2 Austria Human-Centered AI market By Application
12.3.3.12.3 Austria Human-Centered AI market By End-User
12.3.3.13 Rest of Western Europe
12.3.3.13.1 Rest of Western Europe Human-Centered AI market By Function
12.3.3.13.2 Rest of Western Europe Human-Centered AI market By Application
12.3.3.13.3 Rest of Western Europe Human-Centered AI market By End-User
12.4 Asia-Pacific
12.4.1 Trend Analysis
12.4.2 Asia-Pacific Human-Centered AI market by Country
12.4.3 Asia-Pacific Human-Centered AI market By Function
12.4.4 Asia-Pacific Human-Centered AI market By Application
12.4.5 Asia-Pacific Human-Centered AI market By End-User
12.4.6 China
12.4.6.1 China Human-Centered AI market By Function
12.4.6.2 China Human-Centered AI market By Application
12.4.6.3 China Human-Centered AI market By End-User
12.4.7 India
12.4.7.1 India Human-Centered AI market By Function
12.4.7.2 India Human-Centered AI market By Application
12.4.7.3 India Human-Centered AI market By End-User
12.4.8 Japan
12.4.8.1 Japan Human-Centered AI market By Function
12.4.8.2 Japan Human-Centered AI market By Application
12.4.8.3 Japan Human-Centered AI market By End-User
12.4.9 South Korea
12.4.9.1 South Korea Human-Centered AI market By Function
12.4.9.2 South Korea Human-Centered AI market By Application
12.4.9.3 South Korea Human-Centered AI market By End-User
12.4.10 Vietnam
12.4.10.1 Vietnam Human-Centered AI market By Function
12.4.10.2 Vietnam Human-Centered AI market By Application
12.4.10.3 Vietnam Human-Centered AI market By End-User
12.4.11 Singapore
12.4.11.1 Singapore Human-Centered AI market By Function
12.4.11.2 Singapore Human-Centered AI market By Application
12.4.11.3 Singapore Human-Centered AI market By End-User
12.4.12 Australia
12.4.12.1 Australia Human-Centered AI market By Function
12.4.12.2 Australia Human-Centered AI market By Application
12.4.12.3 Australia Human-Centered AI market By End-User
12.4.13 Rest of Asia-Pacific
12.4.13.1 Rest of Asia-Pacific Human-Centered AI market By Function
12.4.13.2 Rest of Asia-Pacific Human-Centered AI market By Application
12.4.13.3 Rest of Asia-Pacific Human-Centered AI market By End-User
12.5 Middle East & Africa
12.5.1 Trend Analysis
12.5.2 Middle East
12.5.2.1 Middle East Human-Centered AI market by Country
12.5.2.2 Middle East Human-Centered AI market By Function
12.5.2.3 Middle East Human-Centered AI market By Application
12.5.2.4 Middle East Human-Centered AI market By End-User
12.5.2.5 UAE
12.5.2.5.1 UAE Human-Centered AI market By Function
12.5.2.5.2 UAE Human-Centered AI market By Application
12.5.2.5.3 UAE Human-Centered AI market By End-User
12.5.2.6 Egypt
12.5.2.6.1 Egypt Human-Centered AI market By Function
12.5.2.6.2 Egypt Human-Centered AI market By Application
12.5.2.6.3 Egypt Human-Centered AI market By End-User
12.5.2.7 Saudi Arabia
12.5.2.7.1 Saudi Arabia Human-Centered AI market By Function
12.5.2.7.2 Saudi Arabia Human-Centered AI market By Application
12.5.2.7.3 Saudi Arabia Human-Centered AI market By End-User
12.5.2.8 Qatar
12.5.2.8.1 Qatar Human-Centered AI market By Function
12.5.2.8.2 Qatar Human-Centered AI market By Application
12.5.2.8.3 Qatar Human-Centered AI market By End-User
12.5.2.9 Rest of Middle East
12.5.2.9.1 Rest of Middle East Human-Centered AI market By Function
12.5.2.9.2 Rest of Middle East Human-Centered AI market By Application
12.5.2.9.3 Rest of Middle East Human-Centered AI market By End-User
12.5.3 Africa
12.5.3.1 Africa Human-Centered AI market by Country
12.5.3.2 Africa Human-Centered AI market By Function
12.5.3.3 Africa Human-Centered AI market By Application
12.5.3.4 Africa Human-Centered AI market By End-User
12.5.3.5 Nigeria
12.5.3.5.1 Nigeria Human-Centered AI market By Function
12.5.3.5.2 Nigeria Human-Centered AI market By Application
12.5.3.5.3 Nigeria Human-Centered AI market By End-User
12.5.3.6 South Africa
12.5.3.6.1 South Africa Human-Centered AI market By Function
12.5.3.6.2 South Africa Human-Centered AI market By Application
12.5.3.6.3 South Africa Human-Centered AI market By End-User
12.5.3.7 Rest of Africa
12.5.3.7.1 Rest of Africa Human-Centered AI market By Function
12.5.3.7.2 Rest of Africa Human-Centered AI market By Application
12.5.3.7.3 Rest of Africa Human-Centered AI market By End-User
12.6 Latin America
12.6.1 Trend Analysis
12.6.2 Latin America Human-Centered AI market by country
12.6.3 Latin America Human-Centered AI market By Function
12.6.4 Latin America Human-Centered AI market By Application
12.6.5 Latin America Human-Centered AI market By End-User
12.6.6 Brazil
12.6.6.1 Brazil Human-Centered AI market By Function
12.6.6.2 Brazil Human-Centered AI market By Application
12.6.6.3 Brazil Human-Centered AI market By End-User
12.6.7 Argentina
12.6.7.1 Argentina Human-Centered AI market By Function
12.6.7.2 Argentina Human-Centered AI market By Application
12.6.7.3 Argentina Human-Centered AI market By End-User
12.6.8 Colombia
12.6.8.1 Colombia Human-Centered AI market By Function
12.6.8.2 Colombia Human-Centered AI market By Application
12.6.8.3 Colombia Human-Centered AI market By End-User
12.6.9 Rest of Latin America
12.6.9.1 Rest of Latin America Human-Centered AI market By Function
12.6.9.2 Rest of Latin America Human-Centered AI market By Application
12.6.9.3 Rest of Latin America Human-Centered AI market By End-User
13. Company Profiles
13.1 Accenture
13.1.1 Company Overview
13.1.2 Financial
13.1.3 Products/ Services Offered
13.1.4 SWOT Analysis
13.1.5 The SNS View
13.2 IBM Corporation
13.2.1 Company Overview
13.2.2 Financial
13.2.3 Products/ Services Offered
13.2.4 SWOT Analysis
13.2.5 The SNS View
13.3 Sentient Technologies
13.3.1 Company Overview
13.3.2 Financial
13.3.3 Products/ Services Offered
13.3.4 SWOT Analysis
13.3.5 The SNS View
13.4 Microsoft Corporation
13.4.1 Company Overview
13.4.2 Financial
13.4.3 Products/ Services Offered
13.4.4 SWOT Analysis
13.4.5 The SNS View
13.5 Google LLC
13.5.1 Company Overview
13.5.2 Financial
13.5.3 Products/ Services Offered
13.5.4 SWOT Analysis
13.5.5 The SNS View
13.6 Nuance Communications
13.6.1 Company Overview
13.6.2 Financial
13.6.3 Products/ Services Offered
13.6.4 SWOT Analysis
13.6.5 The SNS View
13.7 Cognizant
13.7.1 Company Overview
13.7.2 Financial
13.7.3 Products/ Services Offered
13.7.4 SWOT Analysis
13.7.5 The SNS View
13.8 Amazon Inc.
13.8.1 Company Overview
13.8.2 Financial
13.8.3 Products/ Services Offered
13.8.4 SWOT Analysis
13.8.5 The SNS View
13.9 Apple Inc.
13.9.1 Company Overview
13.9.2 Financial
13.9.3 Products/ Services Offered
13.9.4 SWOT Analysis
13.9.5 The SNS View
13.10 OpenAI
13.10.1 Company Overview
13.10.2 Financial
13.10.3 Products/ Services Offered
13.10.4 SWOT Analysis
13.10.5 The SNS View
13.11 NVIDIA Corporation
13.11.1 Company Overview
13.11.2 Financial
13.11.3 Products/ Services Offered
13.11.4 SWOT Analysis
13.11.5 The SNS View
13.12 Salesforce Inc.
13.12.1 Company Overview
13.12.2 Financial
13.12.3 Products/ Services Offered
13.12.4 SWOT Analysis
13.12.5 The SNS View
13.13 Affectiva
13.13.1 Company Overview
13.13.2 Financial
13.13.3 Products/ Services Offered
13.13.4 SWOT Analysis
13.13.5 The SNS View
13.14 BenevolentAI
13.14.1 Company Overview
13.14.2 Financial
13.14.3 Products/ Services Offered
13.14.4 SWOT Analysis
13.14.5 The SNS View
13.15 Zebra Technologies.
13.15.1 Company Overview
13.15.2 Financial
13.15.3 Products/ Services Offered
13.15.4 SWOT Analysis
13.15.5 The SNS View
14. Competitive Landscape
14.1 Competitive Benchmarking
14.2 Market Share Analysis
14.3 Recent Developments
14.3.1 Industry News
14.3.2 Company News
14.3.3 Mergers & Acquisitions
15. Use Case and Best Practices
16. Conclusion
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When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data. This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.
We at SNS Insider have divided Primary Research into 2 parts.
Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.
This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.
Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.
Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.
Step 3: Data Bank Validation
Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.
Step 4: QA/QC Process
After all the data collection and validation our team does a final level of quality check and quality assurance to get rid of any unwanted or undesired mistakes. This might include but not limited to getting rid of the any typos, duplication of numbers or missing of any important information. The people involved in this process include technical content writers, research heads and graphics people. Once this process is completed the title gets uploader on our platform for our clients to read it.
Step 5: Final QC/QA Process:
This is the last process and comes when the client has ordered the study. In this process a final QA/QC is done before the study is emailed to the client. Since we believe in giving our clients a good experience of our research studies, therefore, to make sure that we do not lack at our end in any way humanly possible we do a final round of quality check and then dispatch the study to the client.
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