Organizations in Asia-Pacific are entering the new year with a sharper focus than ever before, as they shift from trying emerging technologies to transforming with them. Leaders have moved past experimentation and are now focused on how to operationalize them responsibly, at scale, and with measurable returns – embedding AI into the core of their digital platforms.
The AI era is moving toward specialization and organizations want systems that are tuned to their industries, data, and operational realities. They also want the freedom to run these workloads wherever it makes most sense: be it on-premise, in the cloud, or at the edge. This combination of specialized intelligence and architectural flexibility is what I believe will shape the defining trends of 2026.
AI becomes practical – and fit-for-purpose models will take center stageIf 2023–2025 were defined by generative AI excitement, 2026 will focus on demonstrating its practical value in meeting specific business needs.
A recent IDC study found that 70% of Asia-Pacific organizations expect agentic AI to disrupt their business models within the next 18 months. Enterprises are focusing on specialized, right-sized, explainable systems for specific industries, with 40% projected to adopt custom silicon by 2027 to optimize performance and cost.
In financial services, fit-for-purpose AI can automate high-volume processes like client onboarding and fraud analysis, improving accuracy, cutting costs, and easing regulatory pressure.
Business leaders will need to rethink infrastructure to support increasingly diverse and demanding AI workloads. Unified inference layers, combined with cloud-connected enterprise platforms and AI accelerators, will help organizations operationalize AI more efficiently, moving from pilots to measurable business impact while balancing performance and cost.In India, GenAI adoption is accelerating across financial services, manufacturing, and retail, supported by programs such as Digital India and AI for All. This momentum according to an IDC study is fueling business transformation, with AI spending projected to reach USD 9.2 billion by 2028.
Virtualization evolves to meet the demands of AI-era workloads
AI is reshaping how enterprises think about infrastructure. Traditional virtualization approaches, built for predictable and uniform workloads, are now being stretched by the needs of modern AI — which demand higher performance, lower latency, and far more flexibility.
In 2026, enterprises will increasingly adopt virtualization strategies that bring together virtual machines, containers, and specialized compute under a single operational model. This helps platform teams modernize at their own pace while supporting both existing applications and new AI-driven workloads. The result is an infrastructure foundation that is flexible enough to run traditional applications and intelligent systems side by side — without sacrificing governance or control.
In India, accelerated modernisation is being driven by Digital India, which is pushing enterprises and public sector organizations toward AI-ready platforms and infrastructure.
Hybrid cloud becomes the default architecture for modern AI
As AI models increasingly rely on real-time data, distributed systems, and specialized computing resources, enterprises need architectures that allow them to run workloads as close to their data as possible, while still maintaining scalability and resilience.
The demands of AI require the hybrid cloud. And in 2026, hybrid cloud will solidify its position as the standard operating model for intelligent enterprise systems. Organizations will prioritize platforms that help them maintain control over sensitive workloads on-premises, scale using public cloud capabilities, and bring intelligence closer to where data is generated at the edge.
For financial institutions, the hybrid cloud model is especially critical. Sensitive and regulated workloads must remain on-premises, while AI-driven analytics often require the elasticity and specialized compute of public cloud environments. This balance is becoming foundational for FSI firms modernizing their risk, compliance, and customer systems.
This reflects a broader industry truth: there will not be one place where AI runs. Enterprises that design environments capable of running AI anywhere will be best positioned to capture its value.
Governance frameworks reshape digital strategy across APAC
As AI adoption accelerates, governance is emerging as a defining force for digital strategy across Asia-Pacific, with organizations demanding secure, transparent systems aligned with local regulations and supported across hybrid and multi-cloud platforms.
In India, the AI governance landscape is strengthening through policy frameworks aligned with the National AI Strategy, emphasizing responsible AI, data security, transparency, and ethical model behavior. South Asian markets are similarly advancing governance norms to balance innovation with compliance, particularly in regulated sectors.
Financial services are playing an outsized role, setting benchmarks for auditability, traceability, and responsible AI practices that other industries are likely to follow.
These guardrails are not slowing innovation—they are enabling it. In 2026, enterprises will prioritize auditable and governable AI systems, with governance influencing architecture, vendor selection, and skill priorities. Open, trustworthy solutions that allow scrutiny of model building, data use, and decision-making will become essential, especially in regulated industries.
Skills, communities, and collaboration become the real accelerators
No transformation happens without people. Demand for cloud-native, AI, and cybersecurity talent continues to outpace supply across Asia-Pacific, and in 2026, this gap will widen unless organizations adopt a skills-first approach to develop and operate modern digital systems.
Open source communities will play a central role, providing shared knowledge, transparency, and collaborative tools accessible to all. Tools and frameworks are also made available to everyone, instead of just a few. As enterprises contribute back responsibly, Asia-Pacific will strengthen its position as a digital innovator, not just a consumer.
In India, the talent ecosystem is evolving rapidly, supported by Digital India and government-backed AI programs, with enterprises increasingly upskilling their workforce in GenAI, cloud-native development, and cybersecurity to accelerate adoption of AI-driven solutions. Across South Asia, open-source communities continue to play a pivotal role, enabling developers to build and scale AI capabilities collaboratively.
The right model, in the right environment, on the right architecture will define the next era of enterprise AI. The success of agentic AI will hinge not only on powerful models, but on the infrastructure, governance, and skills that support them. In 2026, openness, flexibility, and collaboration will remain the principles that help organizations move from potential to real, measurable outcomes. With no single model suited to every enterprise context, open source will continue to underpin the freedom and innovation needed to build what comes next.
The author is Navtez Singh Bal, Vice President & General Manager, India and South Asia.
Disclaimer: The views expressed are solely of the author and ETCIO does not necessarily subscribe to it. ETCIO shall not be responsible for any damage caused to any person/organization directly or indirectly.
