The convergence of artificial intelligence (AI) and Web3 is poised to reshape the business landscape in ways few organizations have fully explored. While each of the technologies has been studied extensively on its own, their combined potential remains relatively underexamined.
Insights suggest that AI and Web3 could complement each other, addressing key limitations while unlocking new opportunities for innovation. From accelerating adoption to transforming traditional business models, the intersection of these technologies promises to redefine how organizations operate and compete in the digital age.
Although AI and Web3 are not new, they have followed different paths in recent years. AI, which has existed in various forms since the 1950s, has surged in attention recently due to the rise of generative AI and large language models. These technologies have showcased surprising capabilities, sparking widespread excitement. EY’s CEO Outlook Pulse survey found that a remarkable 99 percent of companies are making or planning investments in GenAI.
However, most companies remain in early experimentation phases, with few at advanced stages, partly due to trust issues and concerns about risks, said EY in a recent report.
Meanwhile, Web3, built on blockchain technology, gained prominence with Bitcoin in 2009 and saw renewed interest in 2021 through NFTs and the metaverse. Despite generating new products and platforms, adoption remains limited to niche enthusiasts, and mainstream uptake is still minimal.
Combination of AI and Web3 to address key limitations
The combination of AI and Web3 has the potential to address each other’s limitations, accelerating adoption for both.
The report explains that AI faces challenges with trust, as generative AI can produce “hallucinations” and be used to generate misinformation or synthetic media at scale. Web3, with its blockchain-based verification mechanisms, can help mitigate these issues by enabling content validation, digital watermarking and secure multi-party data sharing. These tools can also support collaborative knowledge pooling while respecting privacy and regulatory constraints.
Conversely, AI can help Web3 overcome usability barriers. Web3’s complex interfaces and terminology often deter mainstream users, but AI-powered assistants could simplify navigation, personalize experiences, and make digital-first constructs more accessible. Additionally, AI’s increasing role in processing and exchanging value digitally could drive broader adoption of Web3 technologies like cryptocurrencies and smart contracts.
While neither technology will solve all challenges—issues like scalability and environmental impact remain—strategically combining AI and Web3 could enhance trust, usability, and adoption, unlocking significant new opportunities for businesses and organizations.
Convergence of AI and Web3 to transform business models
The convergence of AI and Web3 has the potential to fundamentally transform business models and reshape the enterprise. Initially, this transformation will focus on rethinking individual business functions, said EY. Companies are already using AI to improve productivity and efficiency, but the next step will be to redesign functions entirely, an effort that will be most effective when AI is combined with Web3.
Supply chains are a prime example. A supply chain could leverage blockchain for security, integrity and inventory control, employ smart contracts for supplier interactions and use AI to predict and respond to disruptions dynamically.
Over time, disruption will extend from specific functions to entire business models. As AI and Web3 automate key skills such as supply chain management, R&D, or marketing, these capabilities may become commoditized, shrinking the competitive advantage of companies that rely on them. Businesses will need to find new ways to create, deliver and capture value to stay relevant.
Web3’s decentralized, open-source architecture also holds the potential to upend traditional business models. By enabling peer-to-peer interactions, it could reduce the dominance of centralized platforms and reshape industries built on network effects.
Finally, AI and Web3 could transform organizational structures. Web3 has introduced DAOs—decentralized organizations without central leadership—and AI could enhance these models, making them adaptive, intelligent and edging closer to the concept of a superfluid enterprise.
Read: How asset tokenization is transforming the future of finance
AI-plus strategy to navigate accelerated disruption
The breakthrough capabilities of AI, exemplified by tools like ChatGPT, illustrate how disruptive technologies can rapidly accelerate once they reach critical inflection points. Business leaders should remain vigilant, actively monitoring evolving technologies to identify opportunities and risks before they reach tipping points.
Many companies begin with experiments and proofs of concept, but to truly leverage AI, leaders must adopt a forward-looking, strategic approach. EY explains that an “AI-plus” strategy considers not only AI itself but also its intersection with other emerging technologies, preparing businesses to navigate accelerated disruption and rethink traditional business models.
