AI Development Tool Software - Africa

Revenue in the AI Development Tool Software market is projected to reach US$202.80m in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2029) of 10.09%, resulting in a market volume of US$328.00m by 2029.
The average Spend per Employee in the AI Development Tool Software market is projected to reach US$0.39 in 2024.
In global comparison, most revenue will be generated United States (US$2.23bn in 2024).

Definition:

The AI Development Tool Software market represents a specialized category of enterprise software focused on providing the tools, platforms, and environments necessary for the efficient creation, deployment, management, and optimization of AI models and applications.

These solutions are designed to streamline the AI development process, offering frameworks, libraries, and integrated development environments (IDEs) tailored to tasks like machine learning, deep learning, natural language processing (NLP), and computer vision. They are critical resources for data scientists, machine learning engineers, and developers working to build and implement AI-driven solutions across diverse industries.

Additional Information:

The AI Development Tool Software market comprises revenue and revenue growth as the key performance indicators. Only the revenues that are generated by primary vendors at the manufacturer price level either directly or through distribution channels (excluding value-added tax) are included and the revenues generated by resellers are excluded. Revenues are generated through both online and offline sales channels and include spending by enterprises (B2B) as well as governments (B2G).

Key players in this market include Google, Microsoft, Amazon Web Services, IBM, and Oracle.

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AI model deployment and management platforms, such as Microsoft (Azure DevOps for AI), IBM (Watson Machine Learning), and Google (AI Platform Prediction).
AutoML tools, such as H2O.ai, Google AutoML, DataRobot.
AI-Integrated development environments (IDEs), such as Microsoft (Visual Studio with AI tools), JetBrains (PyCharm with AI integrations), and Kite.
Collaboration and version control tools for AI, such as GitHub with ML extensions, DVC (Data Version Control).
Data Handling and Processing, such as DataRobot, Alteryx, and Trifacta.
Conversational AI and Chatbot development platforms, such as Microsoft Bot Framework, Google Dialogflow, Rasa.

Consumer-Focused AI applications, such as Virtual assistants (Siri, Alexa), AI-powered personal recommendations in e-commerce.
General enterprise software (Non-AI Specific), such as ERP systems (SAP, Oracle ERP), CRM software (Salesforce).
Basic data analytics and business intelligence tools, such as Tableau, Power BI.
Traditional software development tools, such as Standard IDEs (Eclipse, IntelliJ IDEA), basic version control systems (Git).
End-User AI applications, such as AI-driven marketing automation (HubSpot), AI-powered cybersecurity (CrowdStrike and Palo Alto Networks).

Data coverage:

The data encompasses B2B, B2G, and B2C enterprises. Figures are based on the allocation to the country where the money was spent at manufacturer price level (excluding VAT).

Modeling approach / Market size:

The segment size is determined through a top-down approach. We use financial statements such as annual reports, quarterly earnings, and expert opinions to analyze the markets. To estimate the segment size for each country individually, we use relevant key market indicators and data from country-specific industry associations such as GDP, level of digitization, GDP sector composition, and observed level of software piracy.

Forecasts:

We use a variety of forecasting techniques, for instance, advanced statistical methods, depending on the behavior of the relevant segment. The main drivers are the GDP and the level of digitization.

Additional notes:

The data is modeled using current exchange rates. The market is updated twice a year in case market dynamics change. The impact of the COVID-19 pandemic is considered at a country-specific level.

This report presents a comprehensive analysis and additional information on the Technology market, in a PDF format.

Imagine a world without the apps you use daily, the games you enjoy, or the websites you rely on. Software development is the invisible hand behind this digital magic, transforming ideas into the tools that shape our lives. Software development is the process of creating, designing, deploying, and supporting software. It includes all the computer activities between the software's conception and final manifestation.

These activities are planned and put into stages in a logical order, a process known as the software development life cycle (SDLC) or software development. The SDLC often includes six stages: requirement analysis, design, development, testing, implementation, documentation, and evolution. Programming languages such as JavaScript and C++ are used to create software, with JavaScript being the most popular programming language in 2023 and used by roughly 65 percent of software developers.