# Survey of Artificial Intelligence Model Marketplace
## 2 AI Marketplace Overview
### Marketplace for Existing AI Models
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Ref.** & **Success Factor** & **Description** & **Example** & **Implementation Suggestions** \\ \hline
[43,44] & Robust Pricing & Transparent, fair, and dynamic pricing strategies that maximize value for buyers and sellers. & Amazon SageMaker charges based on usage. Google AI Platform offers credits for trials. & Implement auction-based or performance-driven pricing strategies. \\ \hline
[45,46] & User-Friendly Design & Simple and intuitive interfaces for both technical and non-technical users. & Hugging Face’s intuitive model search and demo system. & Use clean UI/UX with guided workflows and demo options for models. \\ \hline
[47] & Strong Policy & Clear policies for data privacy, intellectual property, and usage terms to build trust standage stakeholders. & DataStax ensures compliance with NVIDIA’s ethical guidelines. HIPAA-compliant AI in healthcare platforms. & Integrate automated compliance checks and robust policy documentation. \\ \hline
[48] & Customization Support & Allow users to customize AI models to meet domain-specific needs. & AI Planet supports industry-specific models (e.g., medical, education). & Provide APIs and developer tools for customization and configuration. \\ \hline
[49] & Performance Transparency & Offer clear metrics (e.g., accuracy, speed) to evaluate model performance pre-purchase. & Google AI Platform provides performance stats for models. & Embed benchmarking and comparison tools with real-time performance metrics. \\ \hline
[50,51] & Marketplace Security & Protect sensitive information and prevent unauthorized access to models or transactions. & Use of blockchain for transaction transparency (e.g., Ethereum-based AI trading). & Implement encryption, blockchain, and secure APIs for transactions. \\ \hline
[52,53] & Standardized Formats & Uniform templates for datasets, models, and metadata to ensure compatibility across use cases. & H\({}_{2}\)O.ai uses standardized model formats. & Develop standards for metadata, versioning, and data schemas. \\ \hline
[54] & Integration Capabilities & Ensure seamless integration with existing tools, platforms, and workflows. & Google AI integrates with GCP. & Provide SDKs, APIs, and tutorials for popular AI frameworks. \\ \hline
[55] & Feedback Loops & Enable buyers to provide feedback and reviews on purchased models. & Hugging Face has a community-based rating system for models. & Include rating and review systems, and encourage regular feedback cycles. \\ \hline
[56] & Cross-Industry Use Cases & Provide models for multiple industries to expand marketplace reach. & Hugging Face offers models for NLP, computer vision, and healthcare. & Diversify model categories and include industry-specific use case demos. \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Critical success factors for AI marketplaces [20]. development [61], as indicated in Table 4. Currently, over 200 startup companies are actively engaged in developing the AI market, spanning more than two dozen distinct categories for GenAI models [62]. Table 5 itemized some of the current Generative AI marketplaces that are designed for existing GenAI models. Besides GenAI, lots of marketplaces were established to sell machine-learning models, a subset of AI models. These machine-learning models are predefined models that allow customers to train models with their own data. Table 6 itemizes some of the existing machine-learning marketplaces.