Comprehensive analysis of AI registry marketplace growth, enterprise adoption patterns, governance requirements, and infrastructure spending across the evolving tool ecosystem
AI registry marketplaces are transforming how organizations manage, discover, and deploy AI models and agents at scale. The model registry platform market reached $412 million in 2024 and projected growth to $2.4 billion by 2030, while 78% of organizations now use AI in at least one business function. Arcade's Registry addresses the core infrastructure needs this growth creates—enabling developers to build, share, and monetize authenticated AI integrations with managed OAuth, pre-built connectors for 100+ services, and both cloud and self-hosted deployment options.
Key Takeaways
- Registry market growth accelerates to $2.4 billion - Model registry platforms expand from $412 million in 2024 to projected $2.4 billion by 2030
- ModelOps outpaces general AI growth - 41.3% CAGR through 2030 exceeds broader AI market expansion
- Multi-model deployments become standard - 37% of enterprises now operate 5+ AI models in production, up from 29%
- Integration remains critical barrier - 95% of IT leaders cite integration as primary obstacle to AI adoption
- Enterprise AI spending surges - 75% year-over-year growth with budgets rising to $85,521 monthly in 2025
- Agentic AI drives new requirements - By 2028, 15% of work decisions made autonomously through AI agents
- Governance becomes mandatory - 40% of regulated enterprises merge data and AI governance frameworks
- Infrastructure spending doubles - AI infrastructure reaches $47.4 billion in H1 2024, up 97% year-over-year
AI Marketplace Adoption Statistics in 2025
1. 78% of organizations use AI in at least one business function
Enterprise AI adoption reached 78% in 2024, up from 55% in 2022. This rapid growth creates direct demand for registry infrastructure capable of managing expanding model portfolios. Organizations moving beyond single-use experiments require systematic approaches to model governance and deployment.
2. 37% of enterprises operate 5 or more AI models in production
Multi-model deployments became standard practice with 37% of enterprises running 5+ models, up from 29% previously. This normalization drives registry adoption as manual coordination fails at scale. Arcade's toolkit system enables teams to organize and manage diverse tool collections without architectural complexity.
3. Only 28% of enterprise applications effectively connected despite AI adoption
While AI usage expands, just 28% of applications achieve effective integration. This gap between adoption and implementation highlights the integration challenges registries must solve. Standardized authentication and metadata schemas bridge these disconnected systems.
4. 95% of IT leaders identify integration as primary barrier to AI adoption
Technical leaders overwhelmingly cite integration as the primary obstacle preventing faster AI deployment. Registry platforms that simplify connection patterns and credential management directly address this constraint. OAuth 2.1 support in Arcade eliminates custom authentication development for each service.
Registry Market Size and Growth Statistics
5. Model registry platform market valued at $412 million in 2024
The model registry platform market reached $412 million in 2024, establishing baseline market size for specialized governance infrastructure. This valuation reflects early-stage adoption concentrated among large enterprises and technology companies.
6. Registry platforms project growth to $2.4 billion by 2030
Market forecasts show registry platforms expanding to $2.4 billion by 2030, representing nearly 6x growth over six years. This trajectory indicates transition from niche tooling to standard enterprise infrastructure.
7. Alternative market projections estimate $4.2 billion opportunity by 2033
Higher-end forecasts project the registry market reaching $4.2 billion by 2033 from an $850 million 2024 baseline. Variance between estimates reflects market definition challenges and different adoption scenarios.
8. ModelOps market grows at 41.3% CAGR through 2030
The broader ModelOps category expands at 41.3% annually, outpacing general AI market growth. This acceleration demonstrates enterprise prioritization of operational capabilities over raw model development. Registry platforms form critical ModelOps infrastructure.
9. MLOps market reaches $19.55 billion by 2032
MLOps platforms grow from $1.58 billion in 2024 to projected $19.55 billion by 2032 at 35.5% CAGR. This expansion context positions registries as essential components within larger operational ecosystems.
Authentication and Security Statistics
10. 90% of organizations express security concerns about generative AI
Security apprehension affects 90% of organizations implementing generative AI applications. Registry platforms addressing authentication, credential management, and audit trails directly mitigate these concerns. Zero token exposure prevents credential leakage through prompt injection.
11. 61% of companies faced accuracy issues with in-house AI solutions
Implementation challenges affected 61% of companies building internal AI systems. Registries with pre-built integrations and standardized patterns reduce these accuracy problems through battle-tested implementations.
12. 40% of regulated enterprises merge data and AI governance
Highly regulated organizations proactively combine governance frameworks, with 40% merging approaches. This consolidation creates demand for unified registry platforms spanning both domains. Financial services, healthcare, and insurance sectors lead this integration.
Enterprise Spending and Investment Statistics
13. Enterprise AI spending grows 75% year-over-year
AI budgets expand at 75% annually, reflecting transition from experimentation to production deployment. This spending growth enables registry platform adoption as organizations formalize AI operations.
14. Average monthly AI budgets reach $85,521 in 2025
Enterprise AI spending rises from $62,964 monthly in 2024 to $85,521 in 2025. Increased budgets support investment in operational infrastructure including registries and governance platforms.
15. AI infrastructure spending hits $47.4 billion in H1 2024
Total AI infrastructure investment reached $47.4 billion in the first half of 2024, up 97% year-over-year. This infrastructure focus extends beyond compute to include management and orchestration platforms.
16. 51% of organizations can confidently evaluate AI ROI
ROI measurement capability remains limited, with only 51% confident in their evaluation methods. This visibility gap complicates business cases for registry platforms despite their governance benefits. Arcade's transparent pricing with usage-based fees enables clearer cost attribution.
Deployment Model and Architecture Statistics
17. 44% of enterprises prioritize AI explainability investments in 2025
Explainability initiatives attract 44% of enterprises as organizations address transparency requirements. Registry platforms supporting metadata documentation and lineage tracking enable these explainability efforts.
18. Only 10% of AI professionals highly confident in developing in-house solutions
Technical confidence remains limited with just 10% confident in custom AI development. This expertise gap drives adoption of platforms offering pre-built capabilities. Arcade's 100+ battle-tested integrations eliminate the need for teams to build OAuth flows and API wrappers from scratch.
Agentic AI and Future Evolution Statistics
19. By 2028, 15% of work decisions made autonomously through agentic AI
Autonomous decision-making via AI agents will handle 15% of decisions by 2028, up from essentially zero today. This shift creates new requirements for agent registries that enable discovery and coordination between autonomous systems.
20. Machine learning market grows to $309.68 billion by 2032
The broader ML market expands from $55.80 billion in 2024 to $309.68 billion by 2032 at 30.4% CAGR. Registry and governance platforms capture an increasing share of this spending as operational maturity advances.
What Is an AI Registry Marketplace
An AI registry marketplace operates as a centralized catalog for AI models, agents, and tools—enabling teams to discover capabilities, inspect metadata, and obtain connection details for production deployments. Unlike simple API directories, registries provide governance infrastructure including version control, audit trails, and authentication management across the complete model lifecycle.
Modern registries function at two levels. Model registries track ML artifacts, metadata, lineage, and governance policies for traditional machine learning workflows. Agent registries extend this concept to autonomous AI agents, cataloging running agents and their capabilities to enable agent-to-agent discovery and orchestration.
Core Components of AI Tool Registries
Registry platforms deliver four foundational capabilities:
- Centralized discovery - Teams query registries to find the right model or agent for specific tasks without manual coordination
- Metadata management - Standardized schemas document capabilities, inputs, outputs, performance metrics, and dependencies
- Governance infrastructure - Version control, approval workflows, and compliance tracking ensure regulatory requirements are met
- Authentication abstraction - OAuth and credential management eliminate token handling complexity for end users
Arcade's platform implements these capabilities through pre-built connectors with managed authentication, enabling developers to integrate tools without building OAuth flows from scratch.
How Registries Differ from API Marketplaces
API marketplaces focus on commercial transactions—buying and selling access to individual APIs. Registries prioritize operational management and governance across potentially hundreds of models deployed simultaneously. While marketplaces optimize for discovery of new capabilities, registries optimize for control and reliability of production systems.
The distinction matters for enterprise teams managing 5+ models in production. Registries provide the operational infrastructure required to maintain performance, security, and compliance at this scale.
Implementation Best Practices
Successful registry implementations begin with clear governance objectives and incremental rollout strategies. Organizations should prioritize registries when managing 5+ models in production or operating in regulated industries requiring audit trails and compliance documentation.
Key implementation priorities include:
- Metadata standardization - Define consistent schemas for documenting model capabilities, inputs, outputs, and dependencies
- Authentication centralization - Implement OAuth-based credential management to eliminate distributed token storage
- Version control rigor - Maintain complete lineage tracking from development through production deployment
- Incremental adoption - Start with highest-risk or highest-value models before expanding registry coverage
- Integration with existing workflows - Connect registries to CI/CD pipelines and monitoring systems
Arcade's deployment options support both cloud and self-hosted implementations, accommodating varied security requirements and regulatory constraints. Teams can start with cloud deployment for speed, then migrate to self-hosted infrastructure as governance requirements mature.
Future Growth Projections
With 78% of organizations now using AI in at least one business function (McKinsey, Mar 2025), the ModelOps market projected to grow at a 41.3% CAGR to $43.6B by 2030 (Grand View Research), and Gartner forecasting that by 2028 agentic AI will autonomously make 15% of day-to-day work decisions, registry platforms are poised for sustained expansion through 2030.
Strategic priorities for the next 24 months include:
- Agent registry adoption - Implement discovery and orchestration infrastructure for autonomous AI agents
- Governance automation - Deploy automated compliance checking and audit trail generation
- Multi-vendor orchestration - Build registry capabilities spanning diverse model providers and API ecosystems
- Security hardening - Implement zero-trust architectures with credential isolation and encrypted storage
By 2028, registry platforms will transition from specialized infrastructure to standard components in enterprise AI stacks—as fundamental as version control systems in software development.
Frequently Asked Questions
What is an AI registry marketplace?
An AI registry marketplace functions as a centralized catalog for AI models, agents, and tools, providing discovery mechanisms, metadata management, governance infrastructure, and authentication abstraction. Unlike simple API directories, registries manage the complete lifecycle from development through production deployment with version control and audit trails.
How fast is the model registry market growing?
The model registry platform market is projected to grow from $412 million in 2024 to $2.4 billion by 2030, while the broader ModelOps category expands at 41.3% CAGR—outpacing general AI market growth.
What percentage of enterprises use multiple AI models?
37% of enterprises now operate 5 or more AI models in production, up from 29% previously. This multi-model deployment pattern drives demand for registry platforms capable of managing diverse model ecosystems.
How do registries support agentic AI workflows?
Agent registries enable autonomous AI systems to discover and coordinate with other agents through standardized metadata schemas and capability indexing. By 2028, 15% of decisions will be made autonomously through agentic AI, requiring sophisticated registry infrastructure for agent orchestration.
