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Keywords
AI, agentic AI, Work Fusion, RPA, intelligent automation, compliance, machine learning, LLMs, automation, enterprise technology
Episode Summary
Agentic AI dominated industry conversation in 2025. But in 2026, enterprise leaders are asking a harder question: How do we deploy AI agents safely, accurately, and in production environments?
In this episode, Maribel Lopez speaks with Peter Cousins, CTO of WorkFusion a UiPath company, about how AI agents evolved from RPA and intelligent automation into production-ready “digital workers.” The discussion focuses on regulated industries, where explainability, auditability, and risk controls matter as much as automation gains.
Rather than hype, this conversation explores what it takes to operationalize AI agents: governance frameworks, confidence thresholds, human oversight, and model risk management.
Sound Bites
Chapters
00:00
Introduction to Agentic AI and Work Fusion
02:00
Transitioning from RPA to AI Agents
04:38
Operationalizing AI Agents in Business
09:21
Navigating the Hype of Agentic AI
12:04
The Role of LLMs in Regulated Environments
14:47
Multi-Agent Orchestration and Collaboration
17:21
Improving AI Agents through Learning
21:01
The Importance of Non-Human Identity in AI
24:06
Closing Thoughts on Adopting Agentic AI
By Maribel Lopez5
2121 ratings
Keywords
AI, agentic AI, Work Fusion, RPA, intelligent automation, compliance, machine learning, LLMs, automation, enterprise technology
Episode Summary
Agentic AI dominated industry conversation in 2025. But in 2026, enterprise leaders are asking a harder question: How do we deploy AI agents safely, accurately, and in production environments?
In this episode, Maribel Lopez speaks with Peter Cousins, CTO of WorkFusion a UiPath company, about how AI agents evolved from RPA and intelligent automation into production-ready “digital workers.” The discussion focuses on regulated industries, where explainability, auditability, and risk controls matter as much as automation gains.
Rather than hype, this conversation explores what it takes to operationalize AI agents: governance frameworks, confidence thresholds, human oversight, and model risk management.
Sound Bites
Chapters
00:00
Introduction to Agentic AI and Work Fusion
02:00
Transitioning from RPA to AI Agents
04:38
Operationalizing AI Agents in Business
09:21
Navigating the Hype of Agentic AI
12:04
The Role of LLMs in Regulated Environments
14:47
Multi-Agent Orchestration and Collaboration
17:21
Improving AI Agents through Learning
21:01
The Importance of Non-Human Identity in AI
24:06
Closing Thoughts on Adopting Agentic AI