Success in modern business is defined by resilience. Six in 10 global business leaders say it’s a top priority.1 And artificial intelligence (AI) is quickly becoming the backbone of that resilience. The organizations that will benefit the most will be those that stop treating AI as an experiment and start incorporating it into their daily operations. But progress has been uneven. A 2025 report states that only 13% of organizations in APAC are fully ready to derive value from AI.2 Companies face complex obstacles when leveraging AI. These include skills and culture gaps, difficulties in moving from pilot to scale, and complex data and data sovereignty rules at the global, country, and industry levels.
Rewiring for resilience: How APAC companies are navigating the next chapter of AI-powered growth Explore how APAC business leaders choose and prioritize AI platforms, data management, infrastructure, and skills. Looking ahead, it also helps executives plan the next stage of AI-driven growth. The report is based on interviews with 22 executives and experts working on technology, digital and AI across APAC.
Key findings:
Companies in APAC are moving from AI experimentation to enterprise-wide integration. Although progress has been uneven, companies across industries are incorporating AI into their platforms, infrastructure, and daily processes. This move reflects a shift from pilot projects to scalable production-grade deployments with measurable benefits.
Opportunities span efficiency, growth and sustainability. Executives see opportunities for AI in predictive maintenance, fraud detection, network optimization, and hyper-personalized customer experiences. These applications not only reduce costs, but also open up new revenue streams and improve environmental sustainability.
High-quality, well-managed data is the decisive factor for scaling up AI. The main barrier to AI expansion across APAC is poor data quality and access. With growing concerns about privacy and data sovereignty, especially in regulated areas such as banking and public services, successful companies are consolidating siled data into well-managed platforms, hiring privacy officers, and adopting hybrid cloud strategies to ensure data is safe, reliable, and compliant.
AI maturity is increasingly shaped by architectural choices rather than algorithms. Mature companies are redesigning their AI infrastructure for agility, not just performance. A “foundation first” approach, building integrated, reusable platforms rather than isolated systems, is the new ideal. In the cloud, a hybrid model is best, where sensitive data remains on-premises and development and training can use the public cloud.
Risk and liability are paramount considerations. As AI integration increases, companies are formalizing ethical considerations and governance processes for managing AI. They are creating and implementing dedicated rules for the responsible use of AI and establishing a task force to address bias, hallucinations, and accountability. This includes clearly defining liability when AI makes wrong decisions and ensuring that the use of publicly available large-scale language models (LLMs) does not lead to the leakage of sensitive data.
The biggest barrier to incorporating AI is culture, not code. Technology alone cannot drive change. Many employees fear that AI tools will replace them rather than empower them. The most successful companies in APAC invest in training, storytelling, and internal AI champions to increase confidence and literacy.
Executives prioritize governance and purpose over “digital first.” Future readiness depends not on the scale of technology deployment, but on the quality, ethics, and strategy that shapes its use. The most successful companies adopt technology selectively and act on purpose rather than hype. Embed governance and accountability at every level to ensure data integrity, regulatory compliance, and ethical practices. And we balance innovation and trust by using technology not just to automate tasks, but to reimagine the way we work.
