{"id":4936,"date":"2026-03-26T14:33:19","date_gmt":"2026-03-26T06:33:19","guid":{"rendered":"https:\/\/conference.thestar.com.my\/cloudtech\/?post_type=event&p=4936"},"modified":"2026-05-20T10:21:21","modified_gmt":"2026-05-20T02:21:21","slug":"masterclass","status":"publish","type":"event","link":"https:\/\/conference.thestar.com.my\/cloudtech\/event\/masterclass\/","title":{"rendered":"AI-Native Enterprise Architecture: Agentic Systems & Automation Strategy"},"content":{"rendered":"

[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_column_text css=””]AI is evolving from productivity tools into autonomous systems that execute workflows across organisations. AI agents can analyse enterprise data, trigger actions, coordinate processes and continuously optimise operations.<\/span><\/p>\n

For management teams and C-suite leaders, the challenge is no longer learning AI tools. The real challenge is designing enterprise architecture where AI agents, automation workflows and data infrastructure operate reliably, securely and at scale.<\/span><\/p>\n

In this full-day interactive masterclass, Dr Lau Cher Han, Chief Data Scientist and CEO of LEAD, introduces the architecture of <\/span>AI-native organisations<\/b>, where automation and agentic systems become operational layers within the enterprise.<\/span><\/p>\n

Participants will explore how AI agents interact with enterprise data, how automation workflows transform business operations, and how leaders can design resilient infrastructure that supports continuous AI-driven execution.<\/span><\/p>\n

Through architecture walkthroughs, enterprise case studies and hands-on exercises using <\/span>n8n to build agentic workflows<\/b>, participants will gain a practical understanding of how organisations move from <\/span>AI experimentation to operational deployment<\/b>.<\/span><\/p>\n

Learning Points<\/b><\/p>\n

Participants will learn how to:<\/span><\/p>\n

    \n
  1. Understand the architecture of AI-native organisations<\/b> and how AI agents interact with enterprise systems, data and workflows.<\/span><\/li>\n
  2. Design agentic automation workflows using platforms such as n8n<\/b>, enabling AI systems to execute tasks across business functions.<\/span><\/li>\n
  3. Build AI-ready enterprise data infrastructure<\/b> that supports automation, decision intelligence and scalable AI deployment.<\/span><\/li>\n
  4. Implement governance and operational oversight for AI agents<\/b>, including workflow monitoring, security and risk management.<\/span><\/li>\n
  5. Evaluate infrastructure, cloud and ecosystem strategies<\/b> to support long-term AI adoption and enterprise resilience.<\/span><\/li>\n<\/ol>\n

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    *All prices are subject to 8% Sales & Services Tax (SST).<\/p>\n

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