Artificial intelligence (AI) has become one of the defining technologies of the modern digital economy. From large language models (LLMs) to predictive analytics, AI systems are shaping how businesses operate, how information flows, and how decisions are made.
At the same time, the rapid rise of AI has uncovered structural problems, particularly around data ownership, governance, and the concentration of power in a handful of technology companies.
According to SMU Associate Professor of Computer Science Zhu Feida, addressing these challenges will require more than better algorithms. It calls for a redefining of how the digital economy should be structured.
“AI and Web3 are not competing paradigms. They are complementary forces that, together, can create a sustainable digital economy,” he explains. “AI provides the intelligence layer that creates value; Web3 provides the trust and incentive layer that makes collaboration sustainable.”
Assoc Prof Zhu believes this combination will reshape how digital value is created and shared—an approach he emphasises in both his research and teaching in the SMU Master of IT in Business (MITB) and SMU-Fudan Doctor of Business Administration (Technology).
The MITB programme equips professionals with the essential skills to navigate the intersections of technology, data, and business. It also explores the use cases and potential of digital innovations like Web3 in the Financial Technology & Analytics (FTA) Track of the programme.
Meanwhile, the SMU-Fudan DBA (Tech) cultivates leaders who can bridge emerging technologies with applied business practice through a cross-disciplinary doctoral programme grounded in advanced business research.
Turning data into assets
Assoc Prof Zhu envisions that the next phase of the internet will move beyond the platform-centric model, which has dominated the landscape for the past two decades.
“In the current digital economy, individuals generate enormous amounts of data through their online activities, such as browsing habits, purchases, health metrics, and location data,” he shares.
However, most of the economic value derived from these data only benefit the platforms that collect and analyse them, while data contributors receive nothing.
Web3 technologies, including blockchain infrastructure, privacy-enhancing technologies, and token-based systems, offer a possible alternative to the current system. Instead of having platforms control data and value flows, Web3 proposes a framework that allows individuals to retain ownership of their data, participating directly in the economic value generated.
He describes Web3 as a new cluster of innovations that enables both individuals and organisations to transform what they own—physical or digital—into assets linked to their identity and governed by transparent economic rules. Data, in this sense, becomes a new type of asset rather than merely raw information.
Building a collaborative intelligence ecosystem with Web3
One of the Web3 research initiatives Assoc Prof Zhu is leading explores leveraging data as an asset. Called SYMPHONY, a blockchain-based protocol, it envisions a system where personal data is treated much like financial assets in a bank account: stored securely, exchanged under user-defined conditions, and potentially generating economic returns.
The approach could also help address a major concern surrounding AI: the extreme centralisation of computational resources required to train large-scale models.
Training advanced AI systems today can require tens of thousands of specialised graphics processing units (GPUs), placing development largely within the reach of the largest technology firms.
Assoc Prof Zhu believes decentralisation, using the SYMPHONY protocol, could mitigate this issue. Universities, research institutes, and data centres around the world already possess substantial computing resources, even if they are far smaller than those of major corporations. Through distributed computing networks and coordination protocols, these fragmented resources could be pooled together to support large-scale AI development.
“Decentralisation does not mean isolation; it means collaboration without centralised control,” he notes.
Assoc Prof Zhu envisions that Web3 could be used to mitigate the centralisation of computational resources required to train AI models
How fairness in collaborative AI can be ensured
At the same time, such collaborative systems raise complex questions about incentives and fairness. If multiple organisations contribute data and computing power to train an AI model, how should the resulting economic value be shared?
According to Assoc Prof Zhu, one possible solution is data auditing, which evaluates how different datasets contribute to the performance of an AI system. Rather than rewarding organisations for the quantity of data they provide, auditing techniques measure how much each dataset improves the model.
These data contributions can be coordinated using a digital token, which is also a Web3 mechanism.
In Assoc Prof Zhu’s framework, tokens function as representations of value, tracking data contributions, computational resources, and other forms of participation within a shared ecosystem.
Without these mechanisms, collaborative AI ecosystems risk breaking down. Contributors may withdraw if they believe their data is undervalued, while others may provide low-quality information and expect receiving equal rewards.
Expanding participation in the digital economy
The potential impact of Web3 extends beyond technology companies. Assoc Prof Zhu suggests that data-based economic participation could open new forms of financial inclusion.
For instance, individuals who lack conventional financial assets could still contribute valuable health information from wearable devices to medical research or insurance modelling. With AI analysing their data, participants would be compensated based on the value it generates.
Together, the convergence of AI and Web3 points to a broader transformation: a digital economy built not only on intelligent algorithms, but also on transparent governance, distributed infrastructure, and fair participation.
Programmes like the SMU Master of IT in Business (MITB) are designed with this shift in mind, equipping students with the skills to navigate both the technical and economic dimensions of this evolving landscape.
“The sustainable AI-Web3 economy will not be built by technologists or economists alone,” Assoc Prof Zhu says. “It will be built by people who understand both the technology and the economic systems that govern how value flows.”
Preparing for a career in the digital economy
To contribute meaningfully to this evolving space, Assoc Prof Zhu outlines four essential competencies that professionals should develop:
- Economic design thinking: Recognise that every technology operates within an economic system, and design these systems with a human-centred approach.
- Regulatory literacy: Understand national and international regulatory frameworks to innovate within regulatory boundaries.
- Cross-domain synthesis: The most impactful challenges at the AI-Web3 intersection are inherently interdisciplinary, making it important to connect ideas across domains, rather than specialise within a field.
- Ethical reasoning: Consider fairness, inclusion, and long-term sustainability. Designing a tokenised economy shapes who can participate, how value is distributed, and what behaviours are encouraged.
More broadly, he advises building up on capabilities for composability, not completeness. “Technologies will evolve, but what will endure are trustworthy systems with clear property rights and fair incentive structures.”
As AI and Web3 reshape how value from data is created and shared, the SMU MITB programme prepares professionals to design the systems and infrastructure to build a more equitable digital economy. Discover more about the MITB programme here.
For industry leaders looking to pursue industry-focused research at the intersection of technology, business, and governance, the SMU-Fudan DBA (Tech) offers a cross-disciplinary doctoral programme that advocates integration of advanced business research with emerging technology domains such as artificial intelligence, Web3, cybersecurity, digital governance, and FinTech. Find out more about the SMU-Fudan DBA (Tech) programme here.
