IBM Says APAC AI Has Entered “Transferable Value” Era As Sectors Borrow Breakthroughs From Each Other

Artificial intelligence in Asia‑Pacific is shifting into what IBM calls a “transferable value” era, where breakthroughs in one industry rapidly spread to others, allowing early adopters to repurpose models, workflows and talent across sectors from banking and energy to telecoms and public services.

IBM’s APAC AI Outlook 2026 report, produced by the IBM Institute for Business Value, finds that 64% of AI investments in the region are now directed toward core business functions that directly impact customer value and top‑line growth, rather than purely back‑office efficiency. By the end of 2026, 95% of executives globally expect generative‑AI initiatives to be at least partially self‑funded, reflecting confidence that AI will generate substantial revenue and cost savings.

The report synthesizes perspectives from executives at 14 top‑performing organizations, including the Philippines’ EastWest Bank and Meralco PowerGen, and identifies five priority sectors: banking, manufacturing, telecommunications, energy and public services. Across these industries, enterprises are embedding AI into product design, customer engagement, risk management and operations.

IBM argues that cross‑industry transfer is becoming APAC’s competitive advantage. For example, fraud‑detection models and anomaly‑detection techniques developed in banking can be adapted to cybersecurity and grid‑stability monitoring in energy. Likewise, predictive‑maintenance systems honed in manufacturing can be repurposed for telecom networks or hospital equipment.

The concept of “transferable value” implies that organizations no longer need to build AI capabilities from scratch for each use case. Instead, they can assemble solutions from pre‑trained models, reusable pipelines and shared governance frameworks, accelerating AI maturity and reducing development cycles.

Generative AI is central to this shift. Philippine outlet PhilstarTech notes that IBM’s outlook sees generative AI becoming a full‑fledged engine of strategic growth, not just a support tool. Enterprises are using it to create new products and services, automate knowledge work, and design entirely new business models—such as AI‑driven advisory services or “AI‑as‑a‑teammate” offerings embedded in enterprise platforms.

Looking ahead, IBM forecasts closer convergence between AI and quantum computing, especially in optimization and simulation tasks, which could give early adopters an additional edge in areas like portfolio optimization, logistics routing and complex system design.

The outlook dovetails with separate research on APAC CIOs’ spending plans. IDC’s Lenovo‑backed CIO Playbook 2026 finds that 96% of organizations intend to boost AI spending this year, with average increases of about 15%. Hybrid AI architectures—combining cloud, on‑premise and edge—are becoming standard as firms seek to balance performance, cost and data‑sovereignty constraints.​

Governance remains a critical enabler and constraint. IBM stresses that enterprises must adopt clear frameworks for data protection, model risk, transparency and human oversight, particularly as “agentic AI” systems capable of autonomous actions become more common. Regulators in markets such as Singapore, Australia and Japan are already moving to clarify expectations around AI auditing, accountability and sector‑specific obligations.

For Gulf partners, APAC’s AI trajectory offers both inspiration and partnership opportunities. GCC governments are pursuing their own AI strategies, investing in data centers and national AI programs; IBM’s concept of cross‑industry transferable value is highly relevant as Gulf banks, energy firms and public agencies look to adapt proven Asian use cases.

If IBM’s forecasts prove accurate, 2026 could be remembered as the year AI in Asia‑Pacific moved decisively from cost‑saving experiments to cross‑industry growth engine, setting new benchmarks that regions like the Middle East will need to match if they hope to stay competitive.