When integrating AI into your organization, should you patch existing systems or replace them altogether? This panel brings together process excellence leaders from across APAC to explore what to do if AI exposes existing design flaws in the way your organization is set up, how to integrate AI safely within your processes for best results and where enterprises are seeing the greatest uplift so far.

Key takeaways:

• Learn why process architecture is essential for effective, scalable AI deployments
• Find out how AI amplifies both strengths and weaknesses in end-to-end processes
• Discuss new organizational models to support AI-ready process ecosystems
• Should you rebuild your core processes before adopting AI? Find out our panel’s own opinions on how best to take your organization forward  

This session explores how integrated workflow, AI prediction engines, and automated decisioning can create the foundation for fully autonomous processes. Discover the benefits of shifting from human-triggered actions towards AI-driven, continuously optimising workflows.

Key takeaways:

• Learn how orchestration layers enable end-to-end autonomous operations
• Discover how to link prediction, monitoring, and actioning for self-healing processes
• Find out about architectural patterns for moving from human-in-the-loop to human-on-the-loop
• See real-world use cases where autonomy reduced cycle time and cost-to-serve 

As processes become faster, more complex, and increasingly digitised, small inefficiencies can scale into massive costs before teams even notice. In this session, explore how AI-powered telemetry and streaming analytics act as real-time guardrails, continuously scanning workflows, flagging deviations, and triggering corrective actions instantly. Discover how attendees are moving from periodic reviews to always-on process optimisation, stopping value leakage before it impacts customers or financial performance.

Key takeaways:

• Discover how to capture and analyse real-time process signals
• Learn how to translate variability detection into actionable interventions
• Identify when to use AI to predict failures vs. trigger preventive changes
• See examples of value leakage recovered using real-time monitoring 

‘A stitch in time prevents nine!’ In this case study, discover how AI can completely transform a company’s approach to identifying process breakdowns, and how, instead of diagnosing failures after they have actually occurred, organizations can now use AI to detect patterns of risk and intervene early.

Key takeaways:

• Improve your understanding of the impact of AI on quality, compliance, and operational stability
• Discover how to integrate predictive diagnostics into legacy processes and what effect this will have on your business
• Find out how to structure governance for proactive vs. reactive improvement
• Discuss the cultural shifts required among staff when AI challenges human assumptions and how to find the best way forward