CIOs as orchestrators of transformation and innovation

As Asian enterprises accelerate their adoption of artificial intelligence, the role of the Chief Information Officer (CIO) has evolved from a technology steward to a strategic orchestrator of AI-driven business transformation by 2026.

No longer confined to IT infrastructure, today’s CIO is central to embedding AI into operational workflows, ensuring compliance, managing risk, and driving innovation across business units. According to Guna Chellappan, general manager for Singapore at Red Hat, AI success hinges on systemic, responsible integration founded on openness and agility, moving beyond isolated pilots to embedding AI deeply into operational workflows.

Open source is about empowering everyone.

A critical first step is empowering non-technical staff to engage with AI tools and contribute meaningfully to decision-making. Chellappan highlights that “the open-source advantage can empower non-technical staff to utilise AI tools and contribute to decision-making.”

This democratisation is critical in Asia, where enterprises face diverse skill levels and data sovereignty constraints.

By adopting user-friendly, open-source generative AI (GenAI) platforms, businesses enable employees across various functions—from marketing to finance—to experiment and innovate, thereby lowering barriers and fostering widespread adoption.

Put another way, this inclusivity fosters broader AI adoption while addressing real-world constraints, such as cost, data sovereignty, and varying skill levels.

Hybrid cloud enables scalability

Scaling AI beyond siloed pilot projects requires a cohesive infrastructure strategy. Chellappan identifies an open hybrid cloud approach as the most effective model: “The most effective approach to scaling AI across multiple business units has been to adopt an open hybrid cloud strategy.”

This enables operational consistency and flexibility, allowing AI workloads to run seamlessly across on-premises, cloud, and edge environments.

In Singapore’s financial sector, for example, both local and regional banks are already leveraging hybrid cloud architectures to deploy AI at scale, demonstrating its viability in highly regulated industries.

Industry research supports this view. Gartner notes that the hybrid cloud is now indispensable for balancing innovation with risk and operational efficiency. IDC forecasts that by 2026, 67% of enterprises in the Asia-Pacific region will increase their investment in AI-driven hybrid cloud infrastructures to enhance agility and regulatory compliance.

From pilot to production

Many organisations struggle to move beyond AI pilots. Chellappan stresses that “transitioning from AI pilot projects to full-scale implementation requires building a solid foundation with open-source tools and practices.”

Integrating AI into existing workflows—rather than treating it as a standalone initiative—ensures smoother deployment and monitoring.

He adds, “Success lies in treating AI development as a continuous process,” with model tuning often proving more efficient than building from scratch. Platforms like OpenShift AI enable this iterative, scalable evolution, accelerating time-to-value.

Measure what matters

Measuring impact is essential for justifying investment and guiding strategy. According to the 2023 State of AI report by McKinsey, companies that track such metrics are 1.8 times more likely to report significant financial benefits from AI.

Organisations should track metrics across efficiency, customer experience, and innovation.

As Chellappan explains, “Key metrics include operational efficiency, such as time saved through task automation, reductions in manual effort, and process speed improvements.”

Additionally, innovation velocity—measured by speed of product development and time to market—offers insight into AI’s strategic contribution.

Compliance through culture

Compliance and ethics cannot be afterthoughts. With regulations like Singapore’s Personal Data Protection Act (PDPA) and emerging AI governance frameworks, Chellappan asserts that “data governance and regulatory compliance are not just checkboxes, but critical enablers of sustainable AI growth.”

Red Hat promotes a culture of responsible innovation, combining technological investment with workforce upskilling to ensure AI is developed transparently and ethically.

This aligns with findings from IDC, which reports that by 2026, 70% of APAC organisations will prioritise AI governance frameworks to mitigate regulatory and reputational risks.

Ethics built-in

Managing AI risks, particularly algorithmic bias, demands proactive safeguards. Chellappan advocates for “applying open source principles such as transparency, inclusivity, and collaboration, while putting safeguards in place to prevent misuse.”

This includes standardised safety benchmarks, filtering mechanisms, and fairness detection frameworks. Community oversight and ethical discussions further reinforce accountability. As noted in a 2024 Gartner report, organisations using open, auditable AI systems report 35% higher trust scores among stakeholders.

Secure by design

Security and infrastructure experts at FutureCIO have confirmed the statement: 'Secure by Design.'

In complex, multi-environment IT landscapes—spanning on-premises, public cloud, edge, and mobile—operationalising AI demands a security-first approach.

Chellappan states, “AI models can be operationalised effectively through prioritising security at the core of operations.”

By integrating MLOps with DevSecOps on a hybrid cloud platform, enterprises can streamline deployment across environments while maintaining security and developer productivity.

CIOs as orchestrators in 2026

IDC and Gartner research collectively highlight the CIO’s pivotal role as an evolving strategic orchestrator who balances innovation with compliance, operational execution, and ethical stewardship. By 2026, 80% of CIOs in the Asia-Pacific region are expected to leverage AI and automation to drive agile, insight-driven businesses, advancing from technology managers to catalysts of cultural and operational change.

Chellappan encapsulates this transformation:

“The CIO’s responsibility is no longer confined to technology infrastructure but extends to driving responsible AI adoption that aligns with business goals, regulatory demands, and employee empowerment—turning AI from promise to performance driver.” Guna Chellapan

Lessons from around the world

Asian enterprises can draw valuable lessons from global leaders. Chellappan notes that “enterprises in APAC can learn from global organisations by embracing open source software, which has underpinned AI innovation.”

From Google and Microsoft to Alibaba and Huawei, leading tech firms are investing heavily in open source. This collaborative model has powered the internet, cloud computing, and now AI. By adopting tools like OpenShift AI, APAC businesses can foster innovation that is both scalable and sustainable.

In sum, the CIO’s role is pivotal in navigating this transformation, not merely as a technologist, but as a catalyst for cultural, operational, and ethical change. With open source, hybrid cloud, and responsible innovation as cornerstones, Asian enterprises can turn AI from a promise into a performance driver.