AI Robotics - GCC

Artificial intelligence (AI) robotics are currently experiencing an increase in demand as a result of advancements in artificial intelligence, machine learning, and sensor technology. This has led to the development of robots that are more intelligent, autonomous, and capable of performing a wide range of tasks, from manufacturing and logistics to healthcare and home assistance. Some of the key trends in the market include the integration of AI with robotics, the rise of collaborative robots or cobots, and the emergence of cloud robotics that can operate in a decentralized manner.

The growth of the AI robotics market is being propelled by several factors, including increasing labor costs, a shortage of skilled workers, and the need for greater productivity and efficiency. Additionally, the rise of Industry 4.0, the Internet of Things (IoT), and the increasing adoption of automation in various industries are expected to further fuel the growth of the market. Moreover, the advancements in the field of natural language processing, computer vision, and machine learning are expected to make robots more intuitive, versatile, and adaptable to changing environments.

The Artificial Intelligence (AI) Robotics market is projected to maintain a steady growth trajectory, with a compound annual growth rate (CAGR) of 13.6% forecasted from 2023 to 2030.

Data coverage: The data encompasses B2B, B2G, and B2C enterprises. Figures are based on the funding values from different industries for the market.

Modeling approach / Market size:Market sizes are determined through a top-down approach with a bottom-up validation, building on a specific rationale for each market. As a basis for evaluating markets, we use annual financial reports, funding data, and third-party data. In addition, we use relevant key market indicators and data from country-specific associations such as GDP, number of internet users, number of secure internet servers, and internet penetration. This data helps us estimate the market size for each country individually.

Forecasts:In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, the S-curve function and exponential trend smoothing are well suited to forecast digital products and services due to the non-linear growth of technology adoption. The main drivers are the level of digitalization, the number of secure internet servers, and the revenue of the Public Cloud market.

Additional Notes: The data is modeled using current exchange rates. The impact of the COVID-19 pandemic and the Russian-Ukraine war are considered at a country-specific level. The market is updated twice a year. In some cases, the market is updated on an ad-hoc basis (e.g., when new, relevant data has been released or significant changes within the market have an impact on the projected development). Data from the Statista Consumer Insights Global survey is weighted for representativeness.