Publication: June 2024
Report Type: Niche Report
Report Format: PDF DataSheet
Report ID: AI4227 
  Pages: 110+
 

Qatar Generative AI Market Analysis, Size, and Forecast by Component, Deployment Model, Business Function, Technique, End User: 2019-2032

 June 2024   

Qatar Generative AI Market Snapshot

Qatar Generative AI Market


  • The Qatar generative AI market is forecasted to achieve US$ 36.5 million in revenue by 2024, projecting a Compound Annual Growth Rate (CAGR) of 23.97% from 2024 to 2032.
  • US$ 26.5 million was the standing of Qatar generative AI industry in 2023.
  • The most prominent segment, categorized as hardware, is anticipated to command a market value of US$ 117.5 million by 2032.
  • In the Qatar generative AI market, it's anticipated that IT and Telecom end user will account for 24.86% of the total revenue by 2032.
  • Major players in the Qatar generative AI are adopting strategies such as partnerships and collaborations to expand their market presence. For instance, in January 2024, the Investment Promotion Agency Qatar (Invest Qatar) collaborated with Microsoft to create Ai.SHA, a cutting-edge AI-powered assistant utilizing GPT capabilities via the Azure OpenAI service. This pioneering initiative positions Invest Qatar as one of the first investment promotion agencies globally to embrace advanced technology, leading to significant changes in professional interactions between investors and businesses in Qatar.

Qatar Generative AI Industry Coverage

Analysis Period

2019 – 2032

Actual Data

2019 – 2023

Base Year

2023

Estimated Year

2024

CAGR Period

2024 – 2032

Research Scope

Component

  • Hardware
  • Software
  • Service

Deployment Model

  • On-premise Solutions
  • Cloud-based Solutions
  • Hybrid Solutions

Business Function

  • Marketing and sales
  • Customer operations
  • Product R&D
  • Software engineering
  • Supply chain and operations
  • Risk and legal
  • Strategy and finance
  • Corporate IT
  • Talent and organization

Technique

  • Generative Modelling Techniques
  • Text-Based Techniques
  • Code-Based Techniques