The extent to which artificial intelligence can deliver value within an enterprise hinges critically on the depth of its digital transformation and the richness of its accumulated industry data. This perspective was shared by Cui Lili, Vice Dean of the Digital Economy Research Institute and a tenured professor at Shanghai University of Finance and Economics, during a dialogue at the 2026 Frost & Sullivan Summit.
Professor Cui Lili noted that the rapid evolution of digital technologies, particularly large-scale AI models, has already begun to permeate multiple sectors of the economy. Even traditionally slow-moving fields like education are now adapting their admissions, curricula, and talent development strategies. She identified two key trends in the current digital economy: the fast-paced development of core technologies and the deepening penetration of digital tools across industries, which are driving widespread transformation.
Where to start leveraging AI
When discussing how AI can empower businesses, Professor Cui Lili emphasized that the focus should not solely be on whether a company has adopted a general-purpose AI model. Instead, the critical factor is its underlying digital infrastructure. She compared a basic AI model to a "high school student" with broad but shallow knowledge. While all companies can access the same general models, the initial difference lies in how they instruct and use the tool. However, businesses with a long history of accumulated industry data, structured knowledge systems, and operational experience can refine this general capability into a "undergraduate, graduate, or even doctoral-level" expert, making it far more specialized and effective.
Company-specific knowledge is the differentiator
"Whether a company has its own proprietary domain knowledge determines how closely AI can align with its operations and how efficiently it can create value," Professor Cui Lili explained. Companies with solid digital foundations can generate and leverage substantial proprietary data to build highly targeted AI capabilities. In other words, a basic model can help a company transition from "walking to riding a bicycle," but giving that bicycle a "propeller" depends entirely on the company's prior data accumulation and digital construction efforts.
Unlocking value from data assets
Regarding how to further unlock the value of data as a factor of production, Professor Cui Lili believes that companies can use data to quickly sense market shifts, identify consumer needs, and discover niche markets that are difficult to pinpoint through experience alone. In an environment of increasing uncertainty, data can also help businesses proactively identify risks and enhance operational resilience. Furthermore, where compliance allows, data can become a tradeable asset or be used in financial instruments like data pledge financing to release its value.
Supporting small and medium-sized enterprises
For small and medium-sized enterprises (SMEs) with limited resources and talent, Professor Cui Lili acknowledged that digital transformation remains a persistent challenge. Many SMEs are primarily focused on survival and cannot afford the high costs of building proprietary technology systems like large enterprises. She suggested that SMEs should learn from industry leaders by adopting cost-effective options such as cloud services, cloud-based computing power, and mature industry solutions. Additionally, industry associations and government bodies can provide support through recommendations for high-quality solutions and subsidies for basic digital technology services, helping to lower the cost of trial and error for these businesses.
The rise of the 'super individual'
Commenting on Shanghai's exploration of the One Person Company (OPC) model, Professor Cui Lili sees it as a significant organizational structure change driven by digital technology. As AI agents become more capable, traditional small teams may evolve into "super individuals" composed of one person managing multiple AI agents. However, she proposed that policy support should establish clear criteria and boundaries for development. The priority should be to encourage OPCs that can synergize with Shanghai's dominant industries and existing industrial ecosystem, thereby effectively combining individual expertise, AI tools, and the city's industrial resources.
Leveraging Shanghai's strengths
In Professor Cui Lili's view, Shanghai possesses multiple advantages for developing the digital economy, including a robust industrial ecosystem, diverse application scenarios, and a strong talent pool. The city has formed a relatively complete industrial chain, from chips and computing power to foundational models and industry applications. The construction of international economic, financial, trade, shipping, and scientific and technological innovation centers, along with competitive industries like automotive and consumer goods, provides rich real-world environments for AI deployment.
Navigating career anxiety in the AI era
Addressing career anxiety in the face of the AI wave, Professor Cui Lili advised professionals to either choose an area of interest to learn anew or to build on their existing industry experience by strengthening their AI application skills, thereby shaping themselves into "super individuals" capable of integrating into the industrial ecosystem. Instead of succumbing to anxiety, she urged people to combine their personal experience and interests to actively explore new possibilities.
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