Deloitte-HKU Lab for Organizational Transformation

Lab Directors:

Prof. Matthias Fahn

Associate Professor, Management and Strategy

Prof. Jie Gong

Associate Professor, Economics and Management and Strategy

Mission

Our mission is to understand how organizations should adapt to the challenges and opportunities of artificial intelligence. We research effective responses and develop frameworks to help leaders successfully implement AI in their organizations.

Core Objectives

AI is transforming the foundation of organizational success – how to attract talent, motivating them, and coordinating their efforts. Through rigorous research and real-world insights, we aim to:

the real-world state of AI transformation in firms across industries

the common pitfalls and strategic missteps that organizations should avoid

practical frameworks to help organizations adapt and thrive in the AI era

📚 Research Projects

Generative AI boosts efficiency but can lower work quality. In an experiment with professional illustrators, we found that AI speeds up early progress but limits further improvement. Many chose to trade quality for speed, revealing a key challenge: GenAI may undermine motivation for creative excellence and innovation.

Paper

We argue that widespread AI adoption raises the cost of incentivizing high human performance, as improved baseline outcomes make “good enough” results more acceptable to firms. Our analysis shows this “shirk-biased technological change” can reduce firm profitability and alter labor market dynamics—workers may benefit initially, but gains fade as competition grows. European regulatory frameworks, which give workers more say in AI adoption, may preserve higher value per worker but could limit competitiveness compared to less regulated regions. Ultimately, firms outside Europe may achieve higher profits per worker and outcompete their European counterparts over time.

This project explores how AI influences doctors when they disagree on diagnoses. Disagreements stem from attention (objective, complementary) and comprehension (subjective, substitutive) differences. Uninterpretable AI can be more persuasive by letting doctors attribute disagreements to attention gaps, especially for those with lower abnormality detection skills or career concerns. This can ultimately improve diagnostic accuracy.

Paper

📊 AI Adoption in Enterprise: Deloitte-HKU C-Suite Survey

Across industries worldwide, the race to harness artificial intelligence (AI) is accelerating. Yet, while enthusiasm runs high, execution often lags behind lofty ambitions. Under this backdrop, Deloitte China and the Centre for AI, Management and Organization at the University of Hong Kong (HKU) have jointly established the “Deloitte-HKU Lab for Organizational Transformation” to unveil findings from a survey of more than 100 C-suite executives that there is a disconnect between the transformative promise of AI and the measurable outcomes realised so far.

Most companies have begun integrating AI into customer-facing and operational functions, signalling that the technology has moved firmly beyond experimentation. However, only a small proportion of companies have successfully scaled these initiatives to achieve a meaningful impact on profitability. Nearly half of respondents acknowledge that realized returns fall short of expectations, indicating that the hype surrounding AI’s return on investment (ROI) still exceeds the reality.

The obstacles to success are largely organizational and executional rather than technical. Legacy structures, talent limitations, and inconsistent implementation strategies remain the main barriers to enterprise-wide adoption. While current AI priorities continue to centre on customer service and process optimisation, emerging investments in research and development mark a slow but significant shift from efficiency towards innovation.

Despite the uneven results, optimism prevails. Most executives plan to expand AI budgets over the next three years, confident that the technology will ultimately deliver sustainable growth, competitive advantage, and new sources of enterprise value. – All materials may be used or shared for non‑commercial purposes with proper citation.

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Research Labs.

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Deloitte-HKU Lab for Organizational
Transformation

Organizations succeed by attracting talent, motivating action, and coordinating efforts—areas AI is transforming, demanding structural adaptation. Our lab guides this shift, identifying effective responses and their interplay with markets, norms, and institutions. Through research and industry collaboration, we assess AI adoption, spotlight pitfalls, and craft frameworks for leaders.

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Lab for AI-Agents in Business and Economics

Our mission is to pioneer AI-driven solutions for business challenges by developing multi-agent systems and domain-specific AI architectures, while guiding organizations through ethical, scalable, and transformative AI adoption. We focus on developing platforms for AI agents and multi-agent architecture for business and management, designing AI agents for specific business applications with deep domain knowledge, and studying the economic impact of AI transformation on human behavior, business and organizations.

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AI Implementation (AI²) Lab

The AI Implementation (AI²) Lab is dedicated to turning AI and business research into real-world AI adoption. We collaborate with organizations to identify frictions, develop deployment strategies, and measure impact of AI implementation. Our work focuses on helping firms adopt and scale AI, designing business models for the AI era, and incubating AI-related innovations through experimentation and prototyping.

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Lab for the Future of Work
and Well-being

We advance understanding of generative AI’s transformation of China’s labor markets, leisure, and wellbeing through rigorous, data-driven, causally robust research generating actionable insights. Our people-centered approach prioritizes human wellbeing, going beyond productivity and profitability to foster better jobs and lives.