HKU and Deloitte China AI Adoption Index 2026

As AI shifts from pilot projects to enterprise core, companies are struggling to translate ambition into measurable outcomes. The HKU and Deloitte China AI Adoption Index 2026, developed by the “Deloitte-HKU Lab for Organizational Transformation” — a joint initiative between Deloitte China and the Centre for AI, Management and Organization at the University of Hong Kong (HKU) provides a data-driven lens into AI’s real-world impact across mainland China and Hong Kong, based on a survey of over 100 C-suite leaders.

The findings reveal a defining paradox: while confidence in AI’s long-term potential has never been higher, scalable outcomes remain elusive. The gap is no longer about technology, it is about how organisations lead, adapt, and align strategy with execution.

Research key findings:

Organisation’s AI Adoption Maturity

More than one-third of organisations are still exploring and 56% in limited implementation, yielding only localized benefits. 23% report measurable financial impact, and only 4% are transformational. Despite strong enthusiasm, most initiatives underperform due to organisational barriers—silos, cultural resistance, and poor data—rather than technical limits.

AI Expectations vs. Reality

AI ROI is consistently overestimated, with 9% of projects delivering negative returns due to hidden costs and disruptions. High‑yield expectations often fall short, while a growing share of initiatives lack clear success metrics—underscoring weak governance and evaluation discipline.

What are the key barriers? If not technology

AI adoption is hindered less by technology than by organisational and executional barriers. The top challenges include siloed departments and cultural resistance, limited understanding of AI capabilities, lack of “quick wins”, unforeseen complexity in implementation and unclear business cases.

Current AI Application and Future Priorities

Current AI applications are most prevalent in customer service (58%), marketing (54%), and IT/technology (53%).

Looking ahead, future priorities largely reinforce current trends but show a strategic shift toward innovation.

The AI Transformation Journey

Our research shows employees’ readiness for AI is hindered by three issues: uncertainty, fear of replacement, and self‑image. Adoption falters when AI is treated as a simple overlay, rather than requiring systemic change across workflows (nodes), cross‑functional links (edges), and enterprise coordination (networks).  

Optimism endures, with most leaders planning to expand AI budgets over the next three years. Understanding the key implications is critical for any leader aiming to convert AI investment into tangible, enterprise-wide value.

Learn more from the research: HKU and Deloitte China AI Adoption Index 2026