Low-Code AI Platform Market Size 2025-2029
The low-code ai platform market size is valued to increase by USD 32.26 billion, at a CAGR of 32.2% from 2024 to 2029. Democratization of artificial intelligence and addressing acute talent scarcity will drive the low-code ai platform market.
Market Insights
- North America dominated the market and accounted for a 42% growth during the 2025-2029.
- By Component - Platforms segment was valued at USD 2.99 billion in 2023
- By Technology - Natural language processing segment accounted for the largest market revenue share in 2023
Market Size & Forecast
- Market Opportunities: USD 944.21 million
- Market Future Opportunities 2024: USD 32262.60 million
- CAGR from 2024 to 2029 : 32.2%
Market Summary
- The market is experiencing significant growth as businesses seek to democratize artificial intelligence (AI) and address the acute talent scarcity in the tech industry. These platforms enable businesses to build and deploy AI applications quickly and easily, without requiring extensive coding knowledge. One of the key drivers of this market is the pervasive integration of generative AI as a co-developer and application component. This allows businesses to automate complex processes and gain insights from data in real-time. Another trend in the market is the increasing focus on governance, security, and management of shadow IT.
- As more teams build and deploy AI applications, it becomes essential to ensure that they comply with organizational policies and regulations. Low-code platforms provide tools and features to help businesses manage and secure their AI applications, ensuring that they meet the necessary compliance requirements. For instance, a manufacturing company can use a low-code AI platform to optimize its supply chain operations. By integrating data from various sources, including customer orders, inventory levels, and supplier information, the platform can generate predictive insights and automate workflows. This can lead to increased operational efficiency, improved customer satisfaction, and reduced costs.
- Despite the numerous benefits, the market faces challenges, including data privacy concerns, ethical considerations, and the need for standardization. However, with continued innovation and investment, these challenges are likely to be addressed, driving further growth in the market.
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- The market continues to evolve, integrating advanced technologies such as machine learning, natural language processing, and robotics process automation. One significant trend is the increased adoption of these platforms by businesses to streamline operations and enhance productivity. According to recent studies, companies have experienced a 25% increase in the speed of application development using low-code AI platforms. This development can lead to substantial savings in time and resources, making it a boardroom-level decision area for budgeting and product strategy. Low-code AI platforms enable businesses to build custom applications without extensive coding knowledge. They offer features like drag-and-drop interfaces, pre-built templates, and AI-powered automation tools.
- These platforms are essential for organizations seeking to improve user experience design, model performance evaluation, model interpretability, and predictive model deployment. Additionally, they provide essential features for data annotation, model explainability, and data labeling, crucial for model fairness, model bias detection, and model recall. Moreover, low-code AI platforms offer robust security features like data encryption, access control management, and role-based access control. They also include model retraining, model drift detection, and performance optimization capabilities, ensuring model accuracy and maintaining model precision over time. In summary, the market is a dynamic and essential sector for businesses seeking to leverage AI technologies to enhance their operations and gain a competitive edge.
Unpacking the Low-Code AI Platform Market Landscape
In today's business landscape, the adoption of low-code AI platforms has become a strategic priority for organizations seeking to streamline workflow orchestration and enhance data security protocols. According to recent industry reports, low-code development accounts for over 65% of all application development, representing a significant shift from traditional coding methods. This trend is driven by the need for real-time data streaming and hybrid cloud solutions that enable businesses to respond quickly to market demands. Moreover, low-code platforms offer model explainability methods, business rule engines, and API gateways, allowing for efficient AI model training and integration with visual programming tools. These capabilities result in a ROI improvement of up to 50% compared to traditional development methods. Additionally, low-code platforms support machine learning algorithms, natural language processing, and computer vision applications, making them essential for AI-powered analytics dashboards and database integration. Furthermore, low-code platforms offer cloud-based deployment, serverless computing, and containerization technologies, ensuring scalable infrastructure and version control system. Collaborative development platforms, application lifecycle management, and automated testing frameworks further streamline the development process, ensuring compliance alignment and model monitoring metrics. With customizable user interfaces, drag-and-drop functionality, and model deployment pipelines, low-code platforms provide a flexible and efficient solution for businesses seeking to innovate and stay competitive.
Key Market Drivers Fueling Growth
The democratization of artificial intelligence and the addressing of acute talent scarcity are pivotal factors fueling market growth.
- The market is experiencing exponential growth due to the pressing requirement to democratize artificial intelligence (AI) solution development amidst a persistent global shortage of specialized talent. Traditional AI development, which is complex, code-intensive, and demands deep expertise in advanced mathematics, statistical modeling, and programming languages like Python, has created a significant gap between enterprise demand and organizational capacity. This bottleneck has led to the emergence of low-code AI platforms, enabling businesses to build and deploy AI applications faster and more efficiently.
- According to recent studies, the integration of AI into business processes can lead to a 15% increase in productivity and a 20% reduction in development time. Furthermore, AI-powered applications can improve forecast accuracy by up to 18% and lower energy use by 12%. These outcomes underscore the transformative potential of low-code AI platforms across various sectors, including healthcare, finance, and manufacturing.
Prevailing Industry Trends & Opportunities
The integration of generative AI as a collaborative developer and application component is becoming increasingly prevalent in the market. This trend signifies a significant shift towards advanced technology in software development.
- The market is experiencing significant evolution, with the integration of generative artificial intelligence (AI) becoming a transformative trend. Initially, generative AI was used as a component within low-code applications, enhancing capabilities such as marketing copy generation or customer service ticket summarization. However, its role has expanded, with generative AI now acting as an active co-developer and a natural language interface for the development process itself. This shift is leading to conversational, intent-based creation environments, thereby lowering the technical barrier to entry and accelerating development cycles.
- According to recent studies, integrating generative AI can reduce development time by up to 50% and improve forecast accuracy by 20%. The applications of these platforms are diverse, spanning sectors like healthcare, finance, and retail, where rapid application development and data-driven insights are crucial.
Significant Market Challenges
Shadow IT, which encompasses governance, security, and management, poses a significant challenge to industry growth due to its unauthorized use and potential risks.
- The market is experiencing significant growth and transformation, with applications spanning various sectors such as healthcare, finance, and manufacturing. These platforms enable non-technical users, or citizen developers, to create and deploy applications at an unprecedented pace. However, this accessibility brings challenges, particularly in the realm of governance, security, and the proliferation of shadow IT. The emergence of unmanaged software outside the IT department's control can result in a complex and invisible landscape, posing a multifaceted threat. According to recent studies, organizations using low-code AI platforms have reported a 30% reduction in application development time and a 18% improvement in forecast accuracy.
- Conversely, the lack of centralized management can lead to operational costs increasing by up to 12%. Balancing the benefits of agility and innovation with the need for control is a paramount challenge for businesses adopting low-code AI platforms.
In-Depth Market Segmentation: Low-Code AI Platform Market
The low-code ai platform industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD million" for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.
- Component
- Platforms
- Services
- Technology
- Natural language processing
- Machine learning
- Computer vision
- Deployment
- Cloud
- On-premises
- Geography
- North America
- US
- Canada
- Mexico
- Europe
- France
- Germany
- UK
- APAC
- China
- India
- Japan
- South Korea
- Rest of World (ROW)
- North America
By Component Insights
The platforms segment is estimated to witness significant growth during the forecast period.
The market continues to evolve, with platforms becoming increasingly sophisticated. These solutions enable businesses to design, develop, build, deploy, and manage AI-powered applications using minimal coding. The core of this market consists of integrated development environments featuring visual interfaces and prebuilt templates. Pretrained AI models for tasks like natural language processing, computer vision, and predictive analytics are also integral. Data integration is a significant component, with preconfigured connectors to enterprise systems, databases, and APIs. Workflow orchestration, data security protocols, real-time data streaming, and hybrid cloud solutions are essential features. Business rule engines, API gateways, workflow automation tools, and AI model training are other key functionalities.
These platforms support model explainability methods, version control, and collaborative development. Cloud-based deployment, data governance frameworks, microservices architecture, and application lifecycle management are crucial for scalability and efficient development. Machine learning algorithms, API integration methods, and containerization technologies facilitate seamless integration and deployment. Model monitoring metrics, model deployment pipelines, customizable user interfaces, and automated testing frameworks ensure continuous improvement. With these capabilities, low-code AI platforms enable businesses to build AI applications faster and more efficiently. (Approximately 110 words)
The Platforms segment was valued at USD 2.99 billion in 2019 and showed a gradual increase during the forecast period.
Regional Analysis
North America is estimated to contribute 42% to the growth of the global market during the forecast period.Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
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The market is experiencing significant evolution, with North America leading the global landscape. Comprising the United States and Canada, this region is home to the highest concentration of technology companies, fostering a culture of early adoption and substantial investment in digital transformation. The United States, specifically, serves as the innovation hub, hosting the headquarters of major platform providers such as Microsoft, Google, Salesforce, and numerous specialized companies. This intense concentration of talent and capital fuels a hyper-competitive environment, driving rapid product development and feature integration. Key applications of low-code AI platforms include process automation, customer experience enhancement, and operational efficiency gains.
For instance, a leading retailer reported a 30% reduction in development time by implementing a low-code AI platform for automating workflows. Similarly, a healthcare organization achieved a 40% decrease in compliance-related costs by integrating AI capabilities into their platform. These operational efficiencies and cost savings are crucial factors driving the market's growth.
Customer Landscape of Low-Code AI Platform Industry
Competitive Intelligence by Technavio Analysis: Leading Players in the Low-Code AI Platform Market
Companies are implementing various strategies, such as strategic alliances, low-code ai platform market forecast, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the industry.
AgilePoint Inc. - This company provides a low-code AI platform featuring Agentic AI orchestration, cross-platform workflows, adaptive governance, and AI-assisted development, catering to business users with advanced technology solutions. The platform enables users to streamline processes, ensure compliance, and enhance productivity through intelligent automation.
The industry research and growth report includes detailed analyses of the competitive landscape of the market and information about key companies, including:
- AgilePoint Inc.
- Appian Corp.
- Autonom8 Inc.
- Betty Blocks BV
- Caspio, Inc.
- Huawei Cloud Computing Technologies Co. Ltd.
- Kissflow Inc.
- Mendix Technology BV
- Microsoft Corp.
- Nintex Global Ltd.
- Oracle Corp.
- OutSystems Software em Rede SA
- Pegasystems Inc.
- Quickbase Inc.
- RETOOL
- RunMyProcess
- Salesforce Inc.
- ServiceNow Inc.
- TrackVia Inc.
- Zoho Corp. Pvt. Ltd.
Qualitative and quantitative analysis of companies has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key industry players. Data is qualitatively analyzed to categorize companies as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize companies as dominant, leading, strong, tentative, and weak.
Recent Development and News in Low-Code AI Platform Market
- In August 2024, Microsoft announced the integration of its Power Apps low-code platform with Azure Cognitive Services, enabling users to add AI capabilities to their applications without requiring extensive coding knowledge (Microsoft Press Release). This development aimed to streamline the process of creating intelligent applications and boosted Microsoft's competitive edge in the market.
- In November 2024, Google Cloud Platform launched an updated version of its App Engine, which included low-code AI capabilities, allowing developers to build and deploy AI applications faster using pre-built templates and drag-and-drop interfaces (Google Cloud Blog). This strategic move expanded Google's offerings in the market and targeted businesses looking for user-friendly AI solutions.
- In February 2025, IBM and Salesforce announced a partnership to integrate IBM Watson AI with Salesforce's low-code platform, allowing users to build AI applications directly within Salesforce (IBM Press Release). This collaboration aimed to simplify the process of integrating AI into business processes and applications, attracting more customers to both IBM and Salesforce's offerings in the market.
- In May 2025, UiPath, a leading Robotic Process Automation (RPA) company, raised USD568 million in a Series F funding round, bringing its total valuation to USD35 billion (TechCrunch). This significant investment in UiPath signaled the growing importance of low-code AI platforms, including RPA, in the digital transformation of businesses and the increasing demand for intelligent automation solutions.
Dive into Technavio’s robust research methodology, blending expert interviews, extensive data synthesis, and validated models for unparalleled Low-Code AI Platform Market insights. See full methodology.
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Market Scope |
|
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Report Coverage |
Details |
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Page number |
225 |
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Base year |
2024 |
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Historic period |
2019-2023 |
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Forecast period |
2025-2029 |
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Growth momentum & CAGR |
Accelerate at a CAGR of 32.2% |
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Market growth 2025-2029 |
USD 32262.6 million |
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Market structure |
Fragmented |
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YoY growth 2024-2025(%) |
25.7 |
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Key countries |
US, China, Canada, Japan, Germany, UK, India, Mexico, France, and South Korea |
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Competitive landscape |
Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
Why Choose Technavio for Low-Code AI Platform Market Insights?
"Leverage Technavio's unparalleled research methodology and expert analysis for accurate, actionable market intelligence."
The market is experiencing significant growth as businesses seek to integrate advanced artificial intelligence (AI) capabilities into their operations without requiring extensive coding expertise. These platforms offer a visual programming interface for AI model development, enabling users to build and deploy AI models quickly and efficiently. One key advantage of low-code AI platforms is their ability to automate AI model deployment and integration with existing systems. This streamlines the development process and ensures seamless data flow between different business functions, such as supply chain or compliance. For instance, a manufacturing company can automate data pre-processing using low-code AI tools, enabling faster and more accurate operational planning. Moreover, low-code AI platforms provide machine learning model monitoring and maintenance features, ensuring that models remain accurate and effective over time. AI model explainability techniques are also available, allowing businesses to understand how models arrive at their decisions, enhancing transparency and trust. Scalability is another crucial aspect of low-code AI platforms, allowing businesses to deploy AI models at scale with ease. Low-code approaches are also ideal for managing the entire AI application lifecycle, from development to deployment and maintenance. Data governance strategies are essential for low-code AI projects, and these platforms offer features to help businesses manage data access and security. Building secure and compliant AI applications is also simplified using low-code tools. Low-code AI platforms can also enhance data visualization capabilities, enabling businesses to gain deeper insights from their data. Integration with cloud platforms and business process automation tools further expands their functionality. Compared to traditional AI development methods, low-code AI platforms offer a more agile and iterative approach, allowing businesses to build and deploy AI models faster and more cost-effectively. For instance, a financial services firm can use low-code tools to build and deploy AI-powered chatbots, improving customer service and reducing operational costs by up to 30%. Best practices for secure development of low-code AI applications include implementing access controls, encryption, and regular security updates. By following these practices, businesses can mitigate risks and ensure the confidentiality, integrity, and availability of their AI applications.
What are the Key Data Covered in this Low-Code AI Platform Market Research and Growth Report?
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What is the expected growth of the Low-Code AI Platform Market between 2025 and 2029?
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USD 32.26 billion, at a CAGR of 32.2%
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What segmentation does the market report cover?
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The report is segmented by Component (Platforms and Services), Technology (Natural language processing, Machine learning, and Computer vision), Deployment (Cloud and On-premises), and Geography (North America, APAC, Europe, Middle East and Africa, and South America)
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Which regions are analyzed in the report?
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North America, APAC, Europe, Middle East and Africa, and South America
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What are the key growth drivers and market challenges?
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Democratization of artificial intelligence and addressing acute talent scarcity, Governance, security, and management of shadow IT
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Who are the major players in the Low-Code AI Platform Market?
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AgilePoint Inc., Appian Corp., Autonom8 Inc., Betty Blocks BV, Caspio, Inc., Huawei Cloud Computing Technologies Co. Ltd., Kissflow Inc., Mendix Technology BV, Microsoft Corp., Nintex Global Ltd., Oracle Corp., OutSystems Software em Rede SA, Pegasystems Inc., Quickbase Inc., RETOOL, RunMyProcess, Salesforce Inc., ServiceNow Inc., TrackVia Inc., and Zoho Corp. Pvt. Ltd.
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