Three years on since the introduction of ChatGPT and the continuing commoditization of artificial intelligence, Asia’s CIOs and CAIOs continue to face intensified AI pressures. Yet 79% of firms globally report inadequate GPU capacity for AI workloads – signalling critical infrastructure strain. Beyond hardware, fragmented data ecosystems threaten regional AI scalability.

Ben Canning, chief product officer at Alteryx, highlights the disconnect between AI ambition and operational data realities, urging APAC enterprises to prioritise foundational data integration over algorithmic hype to unlock sustainable AI value.

Given the importance of data in the function of AI systems, we have asked Canning to share with us his perspective on how data integration can spell the success or failure of AI adoption.

1. Briefly give us a state of AI adoption in Asia in 2025. What has worked and what has not worked? (second wave of AI adoption now)

2. What is the understanding of CIOs and CAIOs/Chief Data Officers when it comes to the relationship between data and AI? What about the rest of the C-suite leadership?

3. What makes APAC’s data-AI gap distinct from global counterparts, and how can it be bridged?

4. What metrics have proven data integration’s ROI in accelerating AI deployment?

5. How do regulatory variances across Asian economies impact integrated data strategies for AI?

6. How can APAC leaders better align their executive AI vision with legacy data infrastructure constraints?

7. Our topic is data integration as an enabler of successful AI adoption, given AI adoption trends, data sprawl, AI sprawl, governance issues, etc., what is your guidance for CIOs and CAIOs to ensure organisations are able to better data integration when it comes to AI adoption?

In 2025, Asia Pacific CIOs must optimise cloud value delivery amid a $250 billion market surge driven by AI and regulatory demands. With nearly 90% of enterprises adopting multi-cloud strategies, balancing hybrid cloud innovation and stringent data privacy laws is critical.

Addressing these challenges requires strategic focus on security, compliance, workforce capabilities, and data-driven decision-making to navigate this rapidly evolving landscape.

In this PodChats for FutureCIO, we are joined by Brett Wheeldon, VP, Solutions Consulting, Asia Pacific, SAP Concur, for his take on how CIOs can optimise cloud strategies for value delivery.

Questions:

Strategic Vision

Q1: How can integrated cloud solutions be designed to deliver seamless end-to-end operational excellence across enterprises? (orchestration/press for suite-based approach that focus on outcomes)

Productivity & Innovation

Q2: How can cloud automation be leveraged to enhance employee productivity and improve user experience?

Architecture & Scalability

Q3: What hybrid cloud architecture best balances enterprises’ needs for innovation, data sovereignty, security, and cost optimisation?

Secure Implementation

Q4: What strategies can ensure secure and compliant migration and management of workloads across multi-cloud and edge environments?

Q5: How should CIOs and CISOs address growing cybersecurity risks (e.g., AI-driven threats) in cloud/edge deployments?

Governance & Compliance

Q7: What governance frameworks are needed to comply with evolving data privacy regulations across APAC jurisdictions?

Data-Driven Sustainability

Q8: How can cloud data platforms be optimised to provide actionable insights that support sustainability and reduce carbon footprint?

Talent & Adaptability

Q6: How can we build cloud and AI skills internally or through partnerships to accelerate cloud value delivery?

Future-Proofing

Q9: What measures ensure workload portability/flexibility to avoid vendor lock-in while maintaining performance?

Q10: What strategy integrates AI capabilities within cloud infrastructure to drive innovation without compromising security/compliance?

Q11: Our topic is Optimise cloud for value delivery, what is your final advise for enterprises as they try to leverage technologies like AI and other solutions to optimise cloud for the best value delivery possible?

In 2025/2026, CISOs in Asia face the dual challenge of leveraging AI for innovation while safeguarding against its unique vulnerabilities. As generative AI reshapes the landscape, strategies must evolve to address risks like prompt injection and data poisoning. By prioritizing transparency, compliance, and a security-first culture, CISOs can navigate the complexities of AI integration and enhance organizational resilience.

In this PodChats for FutureCISO, we are joined by Reinhart Hansen, director of Technology, Field CTO APJ, Thales, who will help us navigate the AI imperative from the security perspective.

1. How can we identify and mitigate the unique vulnerabilities introduced by generative AI?, such as prompt injection and data poisoning?

2. What specialised AI security monitoring and detection tools should we deploy to reduce breach detection and containment times?

3. How do we ensure transparency and compliance with evolving AI regulations like the ASEAN Guide on AI Governance and Ethics?

4. How can we secure AI systems (LLM factories) provided by third-party vendors and manage supply chain risks related to AI data access and processing?

5. How do we balance the business imperative to adopt AI-driven innovation with the need to defend against increasingly sophisticated AI-powered cyber threats?

6. How can we foster a security-first culture that promotes responsible AI use and equips security teams with the necessary AI expertise?

7. What investment priorities and cross-functional collaborations are essential to build a comprehensive and proactive AI security programme that aligns with business objectives?

8. Name top three recommendations that CISOs and their organisations should take as they lead their organisations into a more AI-immersed operating environment?