For the longest time, companies have relied on traditional automation to optimize processes and workflows. But task-based automations aren’t reusable, scalable, or sustainable enough to deliver value at large. As intelligent automation evolves from tactical RPA deployments to AI-enhanced, end-to-end process orchestration, it is opening the door to gain deeper insights, more cost reduction, and productivity gains. By combining RPA, BPA, AI, data and analytics to create an end–to-end process that can learn and adapt on its own, enterprises can manage more complex processes and unlock efficiency, adaptability and innovation.  This session explores how to identify opportunities for intelligent automation while balancing AI innovation with the scale and reliability of traditional automation tools and methods. How organizations are transitioning from traditional to AI-enabled automation. 

·                Understanding how to identify which use cases are best suited for deterministic vs non-deterministic models 

·                Evaluating key considerations for introducing agentic AI into existing automation programs 

·                Ensuring cybersecurity and governance while deploying agentic AI in critical processes 

·                 Driving relevant outcomes across the business with ecosystem automation 

·                Building a roadmap that aligns automation with business strategy and outcomes 

For the longest time, companies have relied on traditional automation to optimize processes and workflows. But task-based automations aren’t reusable, scalable, or sustainable enough to deliver value at large. As intelligent automation evolves from tactical RPA deployments to AI-enhanced, end-to-end process orchestration, it is opening the door to gain deeper insights, more cost reduction, and productivity gains. By combining RPA, BPA, AI, data and analytics to create an end–to-end process that can learn and adapt on its own, enterprises can manage more complex processes and unlock efficiency, adaptability and innovation. This session explores how to identify opportunities for intelligent automation while balancing AI innovation with the scale and reliability of traditional automation tools and methods. How organizations are transitioning from traditional to AI-enabled automation