Lenovo data shows why AI spending is rising across Asia Pacific

• Lenovo’s CIO Playbook shows AI spending rising, while scaling remains difficult.
• CIOs expect returns but still face hurdles in governance and infrastructure.

Across Asia Pacific, AI is no longer treated as a side project. For most enterprises, it is now a core budget and planning item. New data from the fourth edition of the Lenovo CIO Playbook 2026 – The Race for Enterprise AIdeveloped with input from IDC, shows how quickly this shift is taking place.

Nearly all organisations surveyed—96% across Asia Pacific—plan to increase AI spending in the next 12 months. On average, budgets are expected to rise by about 15%. That investment covers a wide range of areas, including generative and agent-based systems, public cloud services, on-prem infrastructure, and security tools designed to support AI workloads.

The same pattern holds across ASEAN+, where 96% of organisations also expect to spend more on AI. The numbers suggest that AI is no longer viewed as an experiment or innovation program. It is being treated as part of the core systems that support growth and competition.

“When 96% of organisations are planning a 15% on average increase in AI investment, it tells us that AI decisions are now being made at the core of enterprise strategy,” said Sumir Bhatia, President, Asia Pacific, ISG, Lenovo. “The differentiator will be how effectively organisations integrate AI, embedding it into infrastructure, operations, and security so value compounds over time.”

From pilot projects to returns on AI spending

Last year, many CIOs were still focused on building business cases for AI. The 2026 Playbook shows a clear shift away from that phase. Instead of asking whether AI can deliver value, organisations are now under pressure to show results that last.

Confidence remains high, with around 88% of Asia Pacific organisations expecting AI to deliver a positive return in 2026. On average, they anticipate earning about US$2.85 for every US$1 invested. At the same time, many teams are finding that moving from pilot projects to full production is harder than expected.

Scaling AI across the business has become a major test. Issues around governance, operating models, and how AI systems are managed over time continue to slow progress. The message from CIOs is not that AI is failing, but that discipline matters more as deployments grow.

AI moves beyond the IT team

AI adoption is also spreading well beyond technology departments. Two-thirds of organisations in Asia Pacific are already piloting or systematically using AI, while another 15% are still in early stages. Only 19% are still weighing whether to move forward.

ASEAN+ shows almost the same breakdown. About 67% are piloting or adopting AI, 15% are early adopters, and 18% are still evaluating next steps.

AI tools are now being used in customer service, marketing, operations, finance, and industry-specific functions. This wider use is changing how decisions are made. In half of the organisations surveyed, non-IT teams are now funding AI projects. That shift is pushing CIOs into a broader coordination role, where they must balance demand from across the business while keeping systems secure and manageable.

Agentic AI draws attention, but caution remains

Interest in Agentic AI is rising quickly. Over the next year, adoption is expected to double. Today, 21% of organisations in Asia Pacific say they are already using Agentic AI in a meaningful way. Almost 60% are exploring it or planning limited deployments.

Sectors such as telecommunications, healthcare, and government are showing the strongest interest, often because they deal with complex workflows and large volumes of data.

Still, few organisations believe they are ready to scale Agentic AI. Only 10% say they can deploy it widely today. For 41%, meaningful scale is more than a year away. Security concerns, data quality issues, governance gaps, and integration challenges remain major obstacles.

“Agentic AI represents a fundamental shift in how intelligence is embedded into the enterprise,” said Fan Ho, ED & GM, Asia Pacific, Solutions & Services Group, Lenovo. “With nearly 60% of organisations already exploring Agentic AI and the majority are choosing a measured path to scale, it reflects that enterprises want AI that operates within core workflows, meets security and governance expectations, and delivers consistent outcomes.”

Hybrid AI becomes the default setup

As AI workloads grow, infrastructure choices are becoming harder to ignore. The Playbook shows that 86% of organisations across Asia Pacific now include on-prem or edge environments as part of their AI setup. Hybrid models, rather than cloud-only approaches, are becoming the norm.

In ASEAN+, 81% of organisations prefer hybrid architectures. Combining on-prem and edge systems allows teams to manage data privacy rules, security needsand performance demands more effectively. This approach is especially important as enterprises handle larger inferencing workloads and systems that support day-to-day operations.

“ASEAN+ organisations, including Indonesia’s rapidly digitising enterprises, have moved from AI experimentation to execution at scale. With 67% systematically adopting AI and integration with devices and infrastructure as the top investment priority, the focus is clear: embed AI into existing environments and extract value fast. The expected 2.7x return per dollar invested proves AI is business-critical infrastructure,” said Nigel Lee, General Manager, Singapore, Lenovo.

Where CIOs plan to direct AI spending next

Looking ahead to 2026, the Playbook highlights three areas shaping CIO priorities.

First, inferencing is becoming the main cost driver over time. Across a model’s lifecycle, inferencing can cost up to 15 times more than training. By 2030, most AI compute is expected to support inferencing, much of it running on distributed edge systems.

Second, employee productivity is gaining importance. AI-enabled devices and local inferencing are now the second-highest IT investment priority. Around half of enterprise PC purchases are expected to shift toward systems with on-device AI agents.

Finally, scale remains the hardest problem to solve. While most organisations expect positive returns from AI, only about half of proof-of-concept projects make it into production. For CIOs, execution—not ambition—is where success will be decided.

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