AI Industrial Robotics - Worldwide

There has been an increasing demand over the past years, for robots that can perform complex tasks with precision and speed. These robots are being designed to collaborate with human workers to increase productivity and efficiency in manufacturing and other industrial sectors. There is also a trend towards the integration of artificial intelligence (AI) and machine learning technologies into industrial robots, enabling them to adapt to changing environments and improve their decision-making capabilities.

Given these circumstances, the artificial intelligence (AI) industrial robotics market is likely to experience steady growth over the next few years. Contributing factors include increasing automation in manufacturing and other industries, rising labor costs, and the need for more efficient and flexible production processes. Advances in AI and machine learning technologies are also driving growth, as these technologies enable industrial robots to perform more complex tasks with greater accuracy and efficiency. The COVID-19 pandemic has also increased the demand for automation in industries such as healthcare and pharmaceuticals and accelerated the growth of the AI industrial robotics market.

The Artificial Intelligence (AI) Industrial Robotics market is expected to show significant growth in the coming years, with a CAGR of over 13.5% from 2023 to 2030. This growth is being driven by the increasing adoption of industrial robots in the automotive, electronics, and food and beverage industries, among others, and market developments in the Asia-Pacific region.

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.