Open Model Engineering: Scaling Agentic AI With Open Models
Summary
Open models are becoming an important option for organizations looking to scale agentic AI while maintaining greater flexibility and control over their technology stack. This white paper explores how enterprises can combine open and proprietary models across different workloads, manage AI costs and token economics, strengthen data and intellectual property protection, and deploy models across cloud, on-premises, and other infrastructure environments. It also examines the growing role of open-source AI frameworks, model customization, sovereign AI architectures, and governance in enterprise agentic AI deployment.
Key Insights
- Open and proprietary models can work together, allowing organizations to select different models and architectures according to workload requirements.
- Model flexibility can improve AI economics, enabling enterprises to select appropriate models, infrastructure, and deployment patterns as agentic AI usage grows.
- Sovereignty is becoming increasingly important, particularly regarding where AI models run, where enterprise data is processed, and how organizations maintain control over their technology environment.
- Enterprise data and intellectual property require stronger protection, especially as AI systems increasingly process proprietary information and generate business-critical outputs.
- Open models can be customized for specific environments, including geographical, linguistic, and cultural requirements.
- Full-stack open-source engineering can expand deployment choices, giving organizations greater flexibility across cloud services, on-premises infrastructure, AI platforms, and different model providers.
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About the Author
Lee Wilson
Digital Transformation Executive helping organizations unlock growth through data, AI, and operational excellence.
Lee Wilson is a digital transformation leader focused on helping businesses leverage technology for greater visibility, control, and strategic decision-making. His expertise spans business transformation, data-driven operations, enterprise technology, and organizational performance.