The Next Enterprise AI Challenge Is Not Adoption.  It is Dependency

Governments, enterprises, technology providers, and investors across the region are accelerating investments in artificial intelligence to improve productivity, enhance customer experiences, modernize operations, and unlock new economic opportunities. The challenge is no longer access to AI. It is managing the dependencies, institutional intelligence, and long-term operational reliance that AI adoption creates over time.

The Rise of the Multi-Vendor AI Enterprise

Across ASEAN, organizations are increasingly leveraging capabilities from multiple AI ecosystems simultaneously. Microsoft, OpenAI, Anthropic, Google, Salesforce, ServiceNow, cloud providers, industry platforms, and emerging regional innovators are all contributing to a rapidly expanding AI landscape.

This diversity is driving innovation and creating significant business value. It is also introducing new operational dependencies as AI systems become integrated into customer engagement, software development, operations, finance, human resources, and business decision-making.

What begins as technology adoption gradually becomes part of the organization's operating model.

Beyond AI Adoption

Unlike previous generations of software, AI does more than automate processes.

It increasingly influences decisions, workflows, knowledge creation, and business outcomes.

As organizations invest in AI-enabled processes, they are also accumulating new dependencies on vendors, platforms, models, integrations, and operational knowledge. At the same time, critical context behind technology decisions, implementations, and lessons learned often becomes fragmented across teams, systems, and individuals.

Over time, understanding these relationships may become just as important as deploying the technology itself.

Sources: Microsoft Work Trend Index 2024, McKinsey State of AI 2025, IBM CIO & CTO Study 2024, Writer Enterprise AI Adoption Report 2025.