Computer Vision - Africa

The Artificial Intelligence market in Africa is experiencing mild growth, driven by factors such as increasing adoption of computer vision technologies, growing awareness about the benefits of AI in healthcare, and the convenience of online services. These factors are particularly impactful in the sub-markets of speech recognition, image recognition, and facial recognition, contributing to the overall growth rate of the market.

Customer preferences: As technology continues to advance in Africa, there is a growing interest in computer vision applications, particularly in the healthcare sector. With limited access to medical professionals in many areas, consumers are turning to AI-powered tools for remote diagnosis and treatment. Additionally, the rise of e-commerce and online shopping has led to an increased demand for computer vision technology in supply chain management and product recognition. This shift towards digital solutions is driven by the need for efficiency and convenience in an increasingly digital landscape.

Trends in the market: In Africa, there is a growing interest in using computer vision technology for various applications, including healthcare, agriculture, and security. This is driven by the increasing availability of affordable smartphones and internet access. In the Computer Vision Market within the Artificial Intelligence Market, there is a trend towards using deep learning algorithms for more accurate and efficient image recognition and analysis. This has significant implications for industry stakeholders, as it can improve productivity, reduce costs, and enable new business opportunities. Furthermore, the adoption of computer vision technology in Africa has the potential to bridge the digital divide and promote economic growth in the region.

Local special circumstances: In Africa, the Computer Vision Market within the Artificial Intelligence Market is influenced by the continent's unique blend of traditional and modern cultures. Additionally, the region's diverse landscape and infrastructure challenges contribute to the market's dynamics. For example, in South Africa, advancements in computer vision technology are being applied to improve agriculture and wildlife conservation efforts, while in Nigeria, the market is driven by the increasing adoption of AI-powered security systems. Furthermore, regulatory initiatives, such as the recent launch of the African Union's AI Continental Strategy, are expected to shape the market's growth in the coming years.

Underlying macroeconomic factors: The growth of the Computer Vision Market within the Artificial Intelligence Market in Africa is influenced by macroeconomic factors such as technological advancements, government support, and investment in digital infrastructure. Countries with favorable regulatory environments and strong investment in AI technologies are experiencing faster market growth compared to regions with regulatory challenges and limited funding. Additionally, the increasing adoption of AI in various industries, such as healthcare, finance, and retail, is driving the demand for computer vision solutions to improve efficiency and productivity. Government initiatives to promote digital transformation and the growing tech-savvy population are also contributing to the market growth.

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.