No-Code Artificial Intelligence Platforms

Global No-Code Artificial Intelligence Platforms Market to Reach US$38.8 Billion by 2030

The global market for No-Code Artificial Intelligence Platforms estimated at US$5.3 Billion in the year 2024, is expected to reach US$38.8 Billion by 2030, growing at a CAGR of 39.4% over the analysis period 2024-2030. Text Data Modality, one of the segments analyzed in the report, is expected to record a 43.4% CAGR and reach US$18.6 Billion by the end of the analysis period. Growth in the Image Data Modality segment is estimated at 37.6% CAGR over the analysis period.

The U.S. Market is Estimated at US$1.4 Billion While China is Forecast to Grow at 37.1% CAGR

The No-Code Artificial Intelligence Platforms market in the U.S. is estimated at US$1.4 Billion in the year 2024. China, the world`s second largest economy, is forecast to reach a projected market size of US$5.7 Billion by the year 2030 trailing a CAGR of 37.1% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 36.5% and 33.7% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 27.0% CAGR.

Global No-Code Artificial Intelligence Platforms Market – Key Trends & Drivers Summarized

How Are No-Code AI Platforms Reshaping Artificial Intelligence Adoption?

No-code artificial intelligence (AI) platforms are democratizing AI adoption by enabling individuals and businesses to develop AI-driven applications without requiring coding expertise. These platforms provide user-friendly interfaces, drag-and-drop tools, and pre-built machine learning models that allow users to automate workflows, analyze data, and optimize decision-making processes without extensive programming knowledge. Industries such as finance, healthcare, marketing, and retail are increasingly integrating no-code AI solutions to accelerate digital transformation, reduce operational costs, and improve efficiency. By eliminating the need for specialized AI developers, these platforms bridge the skills gap, allowing small and medium-sized enterprises (SMEs) to leverage AI for customer service automation, predictive analytics, fraud detection, and business intelligence. Cloud-based infrastructure and advancements in AI-as-a-service (AIaaS) are further propelling the growth of no-code AI platforms, making them accessible to a broader audience. As organizations seek faster and more scalable AI implementation, no-code platforms are becoming a game-changer in enterprise automation and digital transformation strategies.

What Challenges Are Limiting the Widespread Adoption of No-Code AI?

Despite their growing popularity, no-code AI platforms face several challenges that could hinder their broader adoption. One of the major concerns is the limited customization and flexibility of pre-built AI models, which may not be suitable for highly complex, industry-specific use cases. Organizations requiring advanced AI functionalities often struggle with the generic nature of no-code solutions, limiting their ability to fine-tune models for specialized tasks. Additionally, concerns about data security and privacy arise as many no-code AI platforms operate on cloud-based infrastructure, increasing the risk of cyber threats and unauthorized access to sensitive information. Another challenge is the potential for biased AI outcomes due to pre-trained models that may not adequately represent diverse datasets. Furthermore, businesses may face difficulties integrating no-code AI with legacy systems, requiring additional investments in API development and middleware solutions. Addressing these challenges will require ongoing improvements in AI model transparency, data privacy protocols, and hybrid AI solutions that combine no-code accessibility with low-code customization options.

How Are Technological Innovations Enhancing No-Code AI Platforms?

Advancements in AI and automation are significantly improving the functionality and efficiency of no-code AI platforms, making them more adaptable to complex business needs. The integration of natural language processing (NLP) is enhancing user interactions, allowing businesses to train AI models using conversational inputs rather than traditional coding. AI-driven automation tools are also enabling predictive analytics, helping organizations generate insights from large datasets with minimal human intervention. Additionally, improvements in explainable AI (XAI) are addressing concerns about transparency, ensuring that AI decision-making processes are interpretable and accountable. Cloud computing advancements and edge AI are expanding the capabilities of no-code platforms, enabling real-time processing and deployment of AI applications across distributed networks. Furthermore, the incorporation of AI-powered data visualization tools is simplifying data analysis for non-technical users, allowing them to create interactive dashboards and generate reports effortlessly. As these innovations continue to evolve, no-code AI platforms are expected to become more sophisticated, bridging the gap between AI accessibility and enterprise-grade automation.

What Is Driving the Growth of the No-Code AI Market?

The growth in the no-code AI market is driven by several factors, including the increasing demand for AI-driven automation, the shortage of skilled AI developers, and the rise of citizen data scientists. Organizations are turning to no-code platforms to streamline business processes, reduce dependency on technical teams, and accelerate time-to-market for AI-powered applications. The adoption of AI-driven chatbots and virtual assistants in customer service, marketing, and e-commerce is further propelling the market, as businesses seek scalable automation solutions without extensive programming expertise. The rapid digitalization of SMEs and startups is also contributing to market growth, as these companies leverage no-code AI for workflow automation, sales optimization, and data-driven decision-making. Additionally, regulatory compliance requirements are driving the adoption of no-code AI platforms with built-in governance features, ensuring that AI applications adhere to ethical guidelines and industry standards. As businesses continue to prioritize agility, efficiency, and cost-effective AI adoption, the demand for no-code AI platforms is expected to witness sustained growth, shaping the future of AI democratization.

SCOPE OF STUDY:

The report analyzes the No-Code Artificial Intelligence Platforms market in terms of units by the following Segments, and Geographic Regions/Countries:

Segments:
Data Modality Type (Text Data Modality, Image Data Modality, Video Data Modality, Speech & Audio Data Modality, Multimodal Data Modality); End-Use (BFSI End-Use, Retail & Commerce End-Use, Automotive, Transportation & Logistics End-Use, Government & Defense End-Use, Healthcare & Life Sciences End-Use, Telecommunications End-Use, Energy & Utilities End-Use, Manufacturing End-Use, Agriculture End-Use, IT / ITES End-Use, Media & Entertainment End-Use, Other End-Uses)

Geographic Regions/Countries:
World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World.

Select Competitors (Total 44 Featured) -

• Akkio Inc.
• Altair Engineering Inc.
• Amazon Web Services, Inc. (SageMaker Canvas)
• Apple Inc. (Create ML)
• C3.ai, Inc.
• Clarifai, Inc.
• Dataiku
• DataRobot, Inc.
• Google LLC (Google Cloud AutoML)
• Graphite Note
• H2O.ai
• IBM Corporation (Watson Studio)
• Kore.ai
• Levity.ai
• Microsoft Corporation (Azure AI)
• Obviously AI
• Pecan AI
• QlikTech International AB
• Runway AI, Inc.
• Salesforce.com, Inc. (Einstein Analytics)

AI INTEGRATIONS
We`re transforming market and competitive intelligence with validated expert content and AI tools.

Instead of following the general norm of querying LLMs and Industry-specific SLMs, we built repositories of content curated from domain experts worldwide including video transcripts, blogs, search engines research, and massive amounts of enterprise, product/service, and market data.

TARIFF IMPACT FACTOR
Our new release incorporates impact of tariffs on geographical markets as we predict a shift in competitiveness of companies based on HQ country, manufacturing base, exports and imports (finished goods and OEM). This intricate and multifaceted market reality will impact competitors by increasing the Cost of Goods Sold (COGS), reducing profitability, reconfiguring supply chains, amongst other micro and macro market dynamics.

Please note: Reports are sold as single-site single-user licenses. Electronic versions require 24-48 hours as each copy is customized to the client with digital controls and custom watermarks. The Publisher uses digital controls protecting against copying and printing is restricted to one full copy to be used at the same location.

The latest version of Adobe Acrobat Reader is required to view the report. Upon ordering an electronic version, the Publisher will provide a link to download the purchased report.

Prior to fulfillment of an order, the client will be required to sign a document detailing the purchase terms for a publication from this publisher.