The Enterprise AI Platform Market Will Surpass $50 Billion In 2030

The enterprise AI platform market is projected to grow from $13 billion in 2024 to $50.3 billion in 2030, at a CAGR of 27.7%. Our market size model uses LSEG analysis of 184,843 firms across 16 industries and six regions, proprietary data from the enterprise AI platform Green Quadrant assessment, responses to the 2024 and 2025 Verdantix AI global corporate surveys and further market research to inform enterprise spend and buying trends.

Verdantix defines enterprise AI platforms as AI‑first enterprise software with configurable low‑code/no‑code agent builders and workflow orchestration for data ingestion and governance, model development and deployment, and process automation using modern deep learning and retrieval architectures. The report sizes corporate end‑user software spend only (subscriptions/licenses, support and maintenance), excluding implementation services, AI infrastructure and frontier model inference. Enterprise AI platform spend is distributed across a host of vendor types: enterprise-scale data platforms, search-heritage vendors, process automation firms, AI-first application platforms, agent orchestration and deployment platforms, and MLOps platforms. The market size and forecast report reveals:

• North America is the largest market, while Asia is the fastest growing.

  North America accounts for 42% of market spend, reflecting a combination of early enterprise adoption, established budgets for cloud and data modernization, and a mature systems-of-record foundation on which  vendors are increasingly building embedded agent and orchestration capabilities. Although Asia contributes less than a third of global enterprise spend, it is the fastest growing market. China in particular has strong open-source activity and high research intensity, supporting accelerated experimentation and deployment, while policy initiatives are reinforcing local ecosystem development and supply chain digitization.

• Business services is the largest vertical, followed by manufacturing and retail.
  Business services is the largest vertical for AI platform spend and sits among the fastest-growing segments, alongside finance and healthcare. These sectors typically exhibit higher levels of digitization, extensive use of enterprise systems (e.g., CRM/ERP) and more established AI upskilling activity – factors that support faster platform adoption. Additionally, business services is highly exposed to agentic AI disruption, given the ease of replacing labour in tasks such as document generation and knowledge retrieval. Consider Accenture’s emphasis on AI implementation and training alongside staffing reductions, and the statement from McKinsey & Company CEO confirming that it already deploys 25,000 agents.

Several buyer and market dynamics are supporting spend growth. The vendor landscape is rapidly changing as incumbents extend their platform capabilities, morphing into enterprise AI platforms, with releases by IFS, Salesforce, SAP, ServiceNow and Workday. AI-first platforms are also deepening their capabilities through domain-specific machine learning and ontology- or graph-based architectures, including Palantir’s support for MCP integration into its ontology and Glean’s enterprise graph release.

Overall, the forecast indicates a market that spurred on by innovation, hype and fear of missing out (FOMO), although question marks still remain over the robustness, ease and resilience of agentic systems. To learn more about spend drivers, barriers and market segmentation, read the full market size and forecast report and visit the Verdantix AI Applied insights page.