Tony explores how Agentic AI can drive next-generation automation, optimize supply chains, and reshape core operational processes. He provides insights into the skills needed to maximize human-AI collaboration and the measurable ROIs early adopters in Asia have achieved.

Agentic AI is considered the fourth version of Robotic Process Automation (RPA), evolving from screen scraping to rule-based systems, then incorporating machine learning, and now leveraging language and reasoning capabilities. This latest iteration addresses challenges that previous RPA versions could not solve, being not solely rule-based or data-dependent but relying on reasoning and language understanding in the performance of tasks.

With the prediction that a significant portion of white-collar work will be digitized through AI, organizations should strive to develop skills in knowledge management and to understand the capabilities and limitations of generative AI in order to maximize human-AI collaboration. When deploying agentic AI, it is crucial to be aware of AI's limitations, such as potential biases and hallucinations, and to understand the risks associated with AI models. Organizations should establish a top-down risk framework to assess the potential harm that could be caused by each automation and ensure ethical implementation. 

In the podcast, Tony further taps into how this collaboration between human and AI can be maximized, ventures about its potentials, and how it will integrate and transform this workforce we know of today, into a well anticipated future.