The AI pilot era is over, with many APAC CEOs taking over ownership of AI strategies.
If 2024 was the year of AI hype, and 2025 was the year of aggressive adoption, 2026 looks to be where organizations face reality on what it really means to be AI-ready.
The Asia Pacific (APAC) region has taken the lead in the global AI race, with Forrester noting that 26% of APAC firms are investing more aggressively in generative AI, versus their counterparts in North America at just 19%. The same report also calls out that the CEO is now taking ownership of AI strategy; 33% of CEOs in APAC are already doing so.
Despite this momentum in adoption, readiness is lagging. Companies are building AI into their offerings and solutions, but their data systems cannot keep up.
“In 2026, the winners will not be the companies with the smartest models, but the ones with the most fluid yet unified data.”
Dhruv Dhumatkar, Chief Technology Officer, Asia Pacific & Japan at NetApp.
In 2026, the winners will not be the companies with the smartest models, but the ones with the most fluid yet unified data. The ability to modernize data infrastructure with discipline is not just a matter for IT teams to consider, but a prerequisite for deploying AI at scale and safely while boosting cyber resilience and overall organizational performance.
Here is how this maturity will manifest in 2026:
Prediction 1: Disaggregation becomes standard practice
Disaggregation has become foundational for data-intensive workloads, but 2026 will see it reach new scale and precision. Enterprises will increasingly decouple how they scale capacity from how they scale performance, delivering optimal speed for AI and analytics while controlling storage growth.
Leaders will also look to architectures that allow them to scale performance for AI workloads, but independently of capacity for archival matters. Solutions like NetApp AFX enable this flexibility without overprovisioning, extending the value of existing systems like AFF and ASA while powering next-generation workloads.
Prediction 2: Intelligent consumption and no-copy migration accelerate modernization
Modernization will be measured by speed to adapt, not spend to build. APAC organizations that are facing tighter scrutiny on AI ROI will pivot to consumption-based models that allow them to treat storage as a utility, with the ability to scale up and down as the situation demands.
Prediction 3: Unified, single-namespace access at scale Data sets are outgrowing single data centers. As sovereign AI and edge computing deployments grow across APAC, data is becoming more distributed. Yet organizations must maintain unified access without compromising security
In 2026, a seamless, single-namespace view spanning on-premises and multi-cloud locations will be essential, with protection embedded directly at the data layer. This ensures that apps and users can access the same data without disruption, while assuring businesses that their data is secure by design.
Intelligent Data Infrastructure will provide consistent metadata and performance tuning alongside global access controls and built-in protection. With these capabilities, organizations will be able to treat all data as one unified system, regardless of where it lives, and ensure it remains resilient against evolving threats.
Conclusion
The companies that thrive in 2026 will be the ones that stop treating data modernization and data security as optional.
By embracing disaggregation, smarter consumption models, and a secure, unified view of data across environments, enterprises can finally build the foundations needed for reliable, scalable AI.
With modern data infrastructure in place, AI stops being an experimental cost center and starts driving real cyber resilience and performance gains that business leaders in APAC are demanding.
