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Scaling AI Agents in the Enterprise: Frameworks, Processes, and Best Practices
As AI adoption grows across organizations, it is crucial to scale AI agents effectively to drive productivity, innovation, and competitive advantage. However, many enterprises struggle with integrating AI agents seamlessly into their operations. In this article, I will outline key frameworks, processes, and best practices for scaling AI agents across the enterprise.
The first step in scaling AI agents is to leverage existing ecosystems (1). AI agents should integrate with platforms like SAP, ServiceNow, and Salesforce to deliver immediate business value. This approach allows organizations to build upon established infrastructure and minimize the risk of duplicated efforts.
Unite RPA and AI teams
Next, it’s essential to unite robotic process automation (RPA) and AI teams to ensure holistic automation solutions. Cross-functional collaboration between these two groups enables the creation of comprehensive workflow designs that cater to a wide range of business needs.
Choose The Right Workflow Architecture
A thoughtful orchestration strategy is vital to maintain reliability and scalability. Instead of focusing solely on individual agent performance, organizations should design workflows that prioritize AI-enabled automation.
Prioritize Governance And Upskilling
Effective AI governance requires clear ownership and versioning, along with ongoing training initiatives for teams. Establishing strict protocols not only resolves issues but also facilitates smoother interdepartment collaboration.
Conclusion
The tools to scale AI agents are readily available. By combining thoughtful orchestration, modular design, strong governance, and real-time monitoring, enterprises can unlock AI’s full potential.
Source: https://www.forbes.com/councils/forbestechcouncil/2025/05/01/scaling-ai-agents-in-the-enterprise-frameworks-processes-and-best-practices/
