AI Industrial Robotics - ASEAN

In the ASEAN region, the AI Industrial Robotics market is witnessing significant growth due to factors such as increasing adoption of AI technologies, rising demand for automated solutions, and the convenience offered by AI-powered robotics. This growth is being driven by the overall growth rate of the Artificial Intelligence market in the region. The increasing demand for efficient and precise industrial processes is also impacting the growth rate of the AI Industrial Robotics market.

Customer preferences: With the rise of automation and the adoption of artificial intelligence in industrial settings, there has been a growing demand for AI-powered industrial robots in the ASEAN region. These robots not only increase efficiency but also reduce the risk of human error, making them highly desirable for businesses. Additionally, there is a growing trend towards collaborative robots, which work alongside humans and can be easily programmed for different tasks. This shift towards more advanced and flexible industrial robots is driven by the need for increased productivity and cost-effectiveness in manufacturing processes.

Trends in the market: In ASEAN, we are seeing a trend of increased investment in AI industrial robotics technology, particularly in countries like Singapore, Malaysia, and Thailand. This is driven by the region's expanding manufacturing sector and the need for more efficient and precise production processes. Additionally, there is a growing focus on developing AI-driven solutions for specific industries, such as automotive, electronics, and healthcare. This trend is expected to continue as companies aim to stay competitive and optimize their operations. For industry stakeholders, this presents opportunities for partnerships and collaborations, as well as potential challenges in adapting to new technologies and training a workforce with the necessary skills.

Local special circumstances: In ASEAN, the AI Industrial Robotics Market is heavily influenced by the region's growing manufacturing sector and the increasing adoption of automation technologies. Additionally, government initiatives promoting Industry 4.0 and the use of AI in manufacturing have further accelerated the demand for industrial robotics. In countries like Singapore and Malaysia, with their advanced infrastructure and skilled workforce, there is a higher adoption of AI industrial robotics in the manufacturing sector. In contrast, countries like Indonesia and Philippines, with their large and growing consumer markets, have seen a rise in demand for AI industrial robotics in the food and beverage and consumer goods industries.

Underlying macroeconomic factors: The growth of the AI Industrial Robotics market is heavily influenced by macroeconomic factors such as technological advancements, government policies, and investments in research and development. Countries with supportive government policies and significant investments in AI technologies are experiencing rapid market growth, while regions with limited resources and regulatory challenges are facing slower growth. Furthermore, the increasing demand for automation and efficiency in industries, coupled with the rising labor costs, is driving the adoption of AI industrial robotics, especially in developing countries.

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.