A Paradigm Shift in Organizational Thinking Enabled by AI Transformation
release time：2025-06-06
GAO FENG ADVISORYJune 2025
The rapid rise of artificial intelligence is profoundly reshaping the global business landscape and has become an unavoidable strategic imperative for all enterprises. AI’s impact spans manufacturing, retail, healthcare, finance and other industries, going far beyond a mere technological upgrade—it is a systemic challenge and reconfiguration of traditional operating models, organizational structures, and even management philosophies. In this profound and far-reaching transformation wave, enterprises cannot afford to be passive bystanders; only proactive embrace of AI can help them gain a competitive edge in the next phase of industrial evolution and achieve a strategic leap from passive adaptation to leading transformation.
Chinese enterprises have demonstrated a first-mover advantage in both the practical application of AI and in-depth strategic thinking around its adoption. They have carried out large-scale exploration and deployment of AI across multiple cutting-edge scenarios such as intelligent manufacturing, digital marketing, and smart customer service. This early leadership is not accidental: it is rooted in China’s complex and dynamic market environment, highly digitalized user behavior, and enterprises’ "commercial DNA" of strong sensitivity to new technologies and rapid responsiveness.
However, being at the forefront of AI adoption also means confronting deep-rooted challenges earlier than others. As AI shifts from the periphery to the core of business operations, enterprises are increasingly facing a series of non-technical, structural issues that go beyond technology itself—touching on the reconstruction of organizational capabilities, redefinition of management boundaries, and systemic evolution of corporate cognitive frameworks. These challenges cannot be solved by piecemeal optimization or short-term tactical responses, but require a strategic perspective, systematic thinking, and a long-term approach.
Building the Cognitive Foundations for the AI Era: Systemic Awareness and Insight
AI is developing at a pace far exceeding any previous general-purpose technology, with broader and deeper implications. Faced with the constant emergence of new algorithms, models and platforms, enterprises that rely on anecdotal experience, fragmented information or traditional path dependency risk falling into cognitive inertia and missing critical strategic windows—even leading AI cloud providers are struggling with this issue. It has become essential for enterprises to establish a systematic and structured mechanism for technological awareness and insight.
This mechanism must be supported by two core pillars: internal data analytics capabilities, and an open external knowledge network that leverages academia, industry ecosystems, capital markets and startups. By establishing frequent interactions and collaboration mechanisms with universities, research institutes, AI startups, industry think tanks and venture capital firms, enterprises can capture emerging trends earlier, gain deeper insights into the potential and limitations of new technologies, and provide more forward-looking and insightful inputs for strategic decision-making.
Some leading Chinese enterprises are already building such "industry knowledge networks"—for example, a diversified international conglomerate regularly releases white papers to this end. Corporate venture capital (CVC) is of particular importance: it allows enterprises to participate in the AI startup ecosystem and observe innovation and failure mechanisms up close. Xiaomi’s CVC-driven entry into the electric vehicle sector demonstrates this strategic value, and the same logic applies to AI. CVC not only enables technical and business synergy, but also realizes forward-looking "cognitive investment" and organizational learning—enterprises can track industry trends, conduct intelligent experiments, and absorb insights through investment activities, thereby sharpening their adaptive strategic capabilities.
For enterprises, the return on investment (ROI) of AI is a critical consideration, and they must clearly assess the rationality of each AI initiative. After the surge of enthusiasm for DeepSeek earlier this year, many entrepreneurs have reported that AI "returns fell short of expectations" and that "indefinite investment is unsustainable". At the same time, enterprises need to reorient their AI investment logic to align with in-depth strategic understanding: AI is not a one-off tool or a deliverable-based project, but a strategic asset that evolves continuously and appreciates over time.
Unlike traditional IT infrastructure or capital investment projects, AI’s value is released in a phased and compound manner. As an AI leader at a top Chinese innovative pharmaceutical company noted, "Many pharma companies still expect a major breakthrough from a single upfront investment, but in reality, AI’s value can only be realized through continuous iteration." This requires a fundamental shift from conventional ROI calculations to a multi-phase, multi-dimensional return assessment framework. This framework must be combined with the aforementioned external knowledge network to form a dynamic, continuously validated and strategically adaptive feedback loop.
Driving AI Transformation: Governance Mechanisms and People
As AI is embedded into core business processes, the complexity of corporate decision-making rises significantly. The dynamic and iterative nature of the AI environment demands that organizations develop a new form of dynamic thinking—capable of making frequent decisions, continuously learning from small-scale failures, and operating in high-uncertainty environments. For large enterprises in particular, this means adjusting internal governance systems and mechanisms to support AI transformation.
Establish a Specialized AI Decision-Making and Leadership Mechanism
AI-related strategic decisions cannot be made in isolation by a single position, technical team, or a small group of individuals through top-down judgments. Instead, a dedicated AI decision-making center should be established, consisting of stakeholders from different functional departments and roles. However, in practice, many large corporate groups still make critical AI decisions based on the opinions of only a few people.
Enterprises must strengthen the participation and leadership of senior management, and AI strategy must be included in the CEO’s core agenda. Senior executives need to act as AI transformation champions to lead organizational strategic alignment and capability coordination—this requires not only technical literacy, but also the leadership to guide the evolution of organizational culture, governance systems and business cognition alongside AI transformation. Enterprises should consider setting up a dedicated AI strategy team or appointing a Chief AI Officer (CAIO) to lead end-to-end transformation, covering strategic insight, technology integration, organizational coordination and cultural guidance. AI must be embedded into the enterprise’s "nervous system", rather than remaining an "external plug-in".
Cultivate a Culture and Mechanism of Smart Trial and Error with Controlled Failure Tolerance
AI transformation requires smart trial and error, as well as a deliberate mechanism and culture that tolerates failure within acceptable boundaries. Enterprises must be able to make small mistakes while avoiding catastrophic ones, and treat failure as a controllable and predictable cost of exploration. However, unlike the short iteration cycles of the internet era, AI experimentation involves significantly higher risks and costs, making it essential for organizations to follow the principle of failing intelligently.
Enterprises should tolerate small-scale, contained failures and treat them as an integral part of systemic learning and capability building—instead of unrealistically demanding "only success, no failure", or responding to setbacks with widespread organizational frustration. Instead, businesses need to build an innovation system with clear exploration boundaries and explicit fault-tolerance mechanisms, enabling continuous iteration and steady progress in complex environments.
Strengthen Cross-Stakeholder Communication and Alignment Capabilities
Advancing AI transformation also requires the organizational ability to communicate and align with diverse stakeholders. This is both an art of judgment and a test of cross-functional coordination. Effective transformation cannot rely solely on structured planning, but also requires tactical finesse in coordination across departments and organizational boundaries.
No AI transformation is possible without the right talent. Looking ahead to the "endgame" of AI development, it is clear that AI will not only reshape work methods, but also fundamentally transform organizational capabilities, talent structures and cultural dynamics. The enterprise of the future will be highly dynamic, adaptive and symbiotic; traditional organizations built around static processes and rigid job roles will be replaced by data-driven, intelligence-responsive, task-oriented models.
In this context, the real talent gap is in hybrid professionals who understand data, can apply AI, and drive business innovation. Repetitive back-office functions will be drastically reduced—for example, Ping An Insurance has already automated more than half of its internal processes through AI. This shift forces not only operational departments, but also business units to rethink their work methods and organizational models.
Cognitive Leap Determines Strategic Success
Globally, a new generation of "AI-native" enterprises is emerging. These are not traditional enterprises simply adopting AI, but entities fundamentally rebuilt with AI logic at their core—they are reimagining every aspect of their industries, from product design and business models to organizational structures and customer relationships. For incumbent enterprises, this represents a paradigm-level challenge, which requires not only a willingness to change, but also the courage and capability for self-disruption.
Enterprises must be willing to incubate new AI-driven business units internally, experiment in frontier application scenarios with leaner resources and faster iteration cycles, and shape their own "future form". Chinese companies have already achieved leading results in some AI scenarios, and this momentum should be converted into a broader strategic capability to set industry standards and shape global paradigms. In doing so, they also provide a unique "lab" and partnership platform for multinational corporations to explore AI innovation in the Chinese market.
Yet turning today’s advantages into sustainable strategic value requires a deeper transformation. Success is not measured by the number of AI models deployed or the amount of AI software purchased, but by whether the organization has achieved a simultaneous upgrade in strategic cognition and organizational capability. The true winners will be those who treat AI as a strategic imperative and leverage it as a catalyst for organizational transformation. The AI era places an extraordinary demand on corporate leaders’ strategic cognitive capacity.
As the AI era deepens, corporate competition will no longer depend solely on tool usage. Once access to data, models and platforms becomes relatively equal, the core differentiators will be: the ability to gain insightful judgments in the face of complexity and ambiguity; the clarity of strategic direction definition; and the depth, speed and rhythm of innovation. Creating and sustaining competitive advantages will require leaders to internalize the "AI mindset" and act as thought leaders in their organizations’ transformation.
This AI mindset is a new, systemic paradigm of thinking—it not only involves an understanding of AI technologies and applications, but also requires comprehensive restructuring across strategic positioning, organizational architecture, business processes, talent models and corporate culture.
AI is not the destination—it is the starting point for redefining the very essence of business. May every enterprise on the transformation path move forward with systemic vision, strategic clarity and organizational strength, toward a more resilient, innovative and intelligent future.
About the Author
Edward Tse: Founder & CEO of Gao Feng Advisory Company, a pioneer in China’s management consulting industry. He built and operated the Greater China operations of two leading international management consulting firms (BCG and Booz) for 20 years, and has provided consulting services to hundreds of Chinese and foreign companies, investors, start-ups, public-sector organizations (both domestic and overseas) on all critical aspects of doing business in China and global business for Chinese enterprises. He has also advised various levels of the Chinese government on strategies, state-owned enterprise reform and Chinese companies' overseas development, as well as the World Bank and the Asian Development Bank. He is the author of hundreds of articles and six books, including The China Strategy (2010), China’s Disruptors (2015) and Mindset for Mega Changes 2 (2025) (《变局思维 2》).
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