The predictions highlight shadow risks, modernization needs, agentic systems, and trustworthy models amid infrastructure and sovereignty constraints across Singapore, Malaysia, Indonesia.

In 2026, ASEAN enterprises are predicted to shift AI implementation from experimental pilots to a governed operational discipline. Fragmented data pipelines, legacy architectures, regulatory pressures, and shadow tool proliferation demand standardization across governance, integration, and infrastructure.

Here are five perspectives from spokespersons of industry, curated in alphabetical order to guide readers through their 2026 corporate strategies:

  • JFrog on “AI governance as the new DevOps and shadow AI eclipse”
  • SAS on “Trustworthy AI amid ASEAN audits and sovereign ecosystems”
  • Zebra Technologies on “Autonomous agents driving APAC efficiency”
  • MongoDB on “Data over models and modernization against talent crunches”
  • Hitachi Vantara on infrastructure constraints like power and data sovereignty

(Note: Quotes have been edited for length and editorial balance)

AI governance will become the new “DevOps” for the enterprise

“In 2026, enterprises will recognize AI adoption as primarily an operational challenge rather than a modeling one. As teams from development to security and business operations adopt AI tools and agents, CIOs will standardize discovery, approval, security, and monitoring processes. AI governance will evolve into a new enterprise discipline, akin to DevOps a decade ago — treating AI as a governed supply chain to scale faster and avoid compliance pitfalls.

Shadow AI will surpass shadow IT as CIOs’ top operational risk. Enterprises will respond with centralized AI catalogs and model allow-lists, mirroring software artifact governance in the DevOps era.

Firms will shift from standalone LLMs and prototypes to deeply integrated systems connected to internal data sources, tools, APIs, workflows, and governance layers. Models using context-enriched connectors will query real-time business data and perform actions, turning AI into an operational participant that reduces drift and accelerates time-to-value.”

Yuval Fernbach, Vice President, VP and CTO (MLOPs), JFrog

Trustworthy AI at scale

“2026 will be the year ASEAN enterprises face increased scrutiny of AI systems, as boards and regulators demand visible, explainable models with measurable business value. The era of unchecked pilots and shadow AI will decline, with EU AI Act principles influencing multinational operations in Singapore, Malaysia, and Indonesia. Firms demonstrating model lineage and governance will gain trust and compliance advantages.

Regional data sovereignty frameworks will drive sovereign AI ecosystems — locally trained, governed, and deployed systems. In ASEAN’s diverse markets, governance will function as a competitive edge rather than bureaucracy. Trustworthy AI at scale will emphasize systems supporting governance, model trust, and transparency. Enterprises prioritizing credibility over speed will treat AI accountability as a boardroom priority.”

Deepak Ramanathan, Vice President, Global Technology Practice, SAS

Autonomous agents in APAC will evolve

“By 2026, AI-powered agents will evolve from routine task management to automating complex processes with minimal human oversight. These systems, capable of understanding intent and anticipating needs, will support organizational operations.

In APAC, structural challenges — labor shortages, cost pressures, and rising customer expectations — will drive rapid AI adoption. Multi-agent systems already show efficiency gains in finance, IT, and customer service sectors.

Our research indicates top retail, manufacturing, and logistics firms could gain significant revenue and profit through AI-improved frontline workflows. As APAC AI maturity advances, embedding agents into devices will enable autonomous inventory tracking, predictive maintenance, and task optimization. AI orchestration tools will enhance efficiency and allow frontline workers to focus on higher-value activities.”

Christanto Suryadarma, Vice President, Southeast Asia (SEA), South Korea and Channel (APJeC), Zebra Technologies

Data, not models, will define the next wave of enterprise AI

“ASEAN’s digital transformation plans in 2026 will reach a critical turning point, shifting focus from maintaining legacy systems to modernization. Leaders will realize ambitious AI initiatives stall not due to technology limitations, but because legacy architectures cannot support the speed, scalability, and flexibility AI demands.

This recognition redefines modernization from cleaning technical debt to enabling workforce optimization. Moving to cloud-native architectures frees technical teams from outdated system maintenance, redeploying them toward innovation, AI adoption, and customer-facing projects. Modernization also becomes a hiring advantage as developers seek organizations with modern tools and automation rather than ageing systems. In 2026, enterprises will adopt bolder modernization beyond contained pilots. AI pressures organizations to rethink system architectures, as rigid cores with fragmented integrations block meaningful value. More firms will modernize entire stacks —  data, applications, infrastructure — to remove blockers slowing AI adoption.”

Thorsten Walther, Managing Director, CXO Advisory (Asia), MongoDB

2026 will be the year AI becomes a discipline, not an experiment

“In 2025, AI became operational across South-east Asia with expanding data centers and accelerated GPU procurement. Scaling adoption revealed constraints: power availability, operational costs, data management maturity, and regulatory alignment now shape enterprise investment and national digital infrastructure policy.

Organizations previously viewed AI as a compute challenge, assuming more accelerators would deliver capability. The limiting factor has shifted to data pipelines, storage, network architecture, and operational discipline for reliable large-scale systems. Agentic AI will raise accountability, transparency, and security questions for regulated industries. ASEAN data center expansion faces finite power and land constraints, particularly in Singapore, Malaysia, Indonesia, Thailand, and the Philippines. Data sovereignty expectations around residency, control, and cybersecurity drive hybrid models combining local control with secure data mobility. AI maturity will depend on disciplined data ecosystems, energy-efficient architectures, and resilient platforms rather than compute volume.”

Lawrence Yeo, ASEAN Solutions Director, MHitachi Vantara