Conference Description
Key Takeaways
- Focus on agentic AI systems capable of autonomous decision-making and action within enterprise environments
- Addresses data governance, model governance, and responsible AI frameworks for regulated industries
- Targets senior technology and business leaders including CIOs, CDOs, CTOs, and heads of digital transformation
- Covers emerging architectures including edge infrastructure, HTAP systems, and data clean rooms
- Explores AI operationalisation challenges specific to ASEAN markets and regulatory environments
Introduction
The ASEAN AI & Data Summit 2026 brings together technology executives and business decision-makers in Singapore to examine the practical realities of deploying artificial intelligence at enterprise scale. Organised by IDC, the event addresses a pivotal moment in the region’s digital trajectory: the shift from experimental AI projects toward production systems that operate autonomously and deliver measurable business outcomes.
Southeast Asia’s enterprise technology landscape has matured considerably over the past several years. Organisations that once focused primarily on cloud migration and basic analytics now face more complex questions about AI governance, data architecture modernisation, and the integration of autonomous systems into core business processes. The summit responds to this evolution by concentrating on agentic AI—systems designed to take independent action rather than simply generate recommendations for human review.
About This Event
The summit takes place at Frasers House in Singapore and follows an in-person format combining keynote presentations, expert panel discussions, hands-on demonstrations, and structured networking sessions. The programme is designed for executive-level participants who hold direct responsibility for technology strategy, data operations, and digital transformation initiatives within their organisations.
IDC, the global technology research and advisory firm, organises the event as part of its broader engagement with enterprise technology leadership across the Asia-Pacific region. The format emphasises strategic conversation over product demonstration, though solution providers participate alongside enterprise practitioners and government representatives.
Agentic AI and the Evolution Beyond Generative Models
The summit’s central theme—agentic AI—represents a significant conceptual shift from the generative AI applications that dominated enterprise discussions throughout 2023 and 2024. While generative AI systems excel at content creation, summarisation, and conversational interaction, agentic AI extends these capabilities into autonomous execution. An agentic system can interpret objectives, plan multi-step workflows, interact with external tools and databases, and complete tasks with minimal human intervention.
This distinction carries substantial implications for enterprise architecture. Agentic systems require robust governance frameworks, clear boundaries on autonomous action, and integration with existing business processes in ways that generative chatbots do not. The summit examines how organisations can build the technical and organisational infrastructure necessary to deploy these systems responsibly.
Customer experience represents one domain where agentic AI shows particular promise. Rather than routing enquiries to human agents or providing scripted responses, agentic customer service systems can resolve issues end-to-end—accessing account information, processing transactions, and coordinating across backend systems to deliver outcomes rather than answers.
Data Readiness and Governance Challenges
The effectiveness of any AI system depends fundamentally on the quality, accessibility, and governance of underlying data. The summit addresses data readiness as a prerequisite for AI success, examining how organisations can assess and improve their data foundations before scaling AI initiatives.
Data governance takes on additional complexity when AI systems begin making autonomous decisions. Model governance—the discipline of tracking model versions, monitoring performance drift, and ensuring continued alignment with business objectives—becomes essential when systems operate without constant human oversight. The summit explores frameworks for managing both data and models throughout their operational lifecycles.
Synthetic data emerges as a related topic, offering organisations a path to train and test AI systems without exposing sensitive production data. This approach addresses privacy concerns while potentially accelerating development cycles, though it introduces its own challenges around data fidelity and model generalisation.
Architecture Modernisation for AI Workloads
Enterprise AI deployment often exposes limitations in existing data architectures. The summit examines several architectural patterns relevant to organisations scaling AI initiatives.
Hybrid transactional and analytical processing (HTAP) architectures allow organisations to run analytical workloads against operational data without the latency introduced by traditional extract-transform-load processes. For AI applications requiring real-time data access, HTAP systems can eliminate the gap between operational reality and analytical insight.
Distributed edge infrastructure addresses scenarios where AI inference must occur close to data sources—whether for latency reasons, bandwidth constraints, or data sovereignty requirements. As AI applications extend into manufacturing, logistics, and field operations, edge deployment becomes increasingly relevant.
Data clean rooms facilitate collaboration between organisations that need to combine datasets without exposing underlying records. This architecture supports use cases in advertising, financial services, and healthcare where multiple parties can derive joint insights while maintaining data separation and privacy compliance.
Regional Context and Cross-Sector Collaboration
ASEAN’s technology landscape presents distinct characteristics that shape AI adoption patterns. The region encompasses economies at varying stages of digital maturity, regulatory frameworks that differ significantly across national boundaries, and a mix of large enterprises, government agencies, and rapidly scaling technology companies.
Government participation in AI initiatives has accelerated across Southeast Asia, with public sector organisations exploring applications in citizen services, regulatory compliance, and policy analysis. The summit addresses how government and enterprise participants can collaborate on shared challenges, particularly around data sharing frameworks and interoperability standards.
Regulatory considerations vary considerably across ASEAN member states. Organisations operating regionally must navigate different approaches to data protection, AI transparency requirements, and sector-specific regulations. The summit provides a forum for examining these variations and their practical implications for technology strategy.
Who Should Attend
The summit targets senior leaders with strategic responsibility for technology and data initiatives. This includes chief information officers, chief data officers, chief technology officers, and other C-level executives, as well as heads of digital transformation, data science, analytics, and innovation functions.
The programme assumes familiarity with enterprise technology concepts and focuses on strategic and architectural considerations rather than technical implementation details. Participants from large enterprises and government agencies will find the content most directly applicable, though the themes resonate across organisation types grappling with AI adoption at scale.
Organisations at different stages of AI maturity can extract value from the summit. Those early in their AI journey will gain frameworks for building foundational capabilities, while those with established AI programmes can examine approaches to governance, scaling, and the transition toward more autonomous systems.
Conclusion
The ASEAN AI & Data Summit 2026 arrives at a moment when enterprise AI is transitioning from proof-of-concept to production reality. The challenges that now confront technology leaders—governance at scale, architectural modernisation, responsible autonomy—differ substantially from those of even two years ago. For organisations seeking to navigate this transition within the specific context of Southeast Asian markets, the summit offers a concentrated opportunity to examine emerging practices and engage with peers facing similar strategic decisions.