DAO-ISEM-IORA Seminar Series: Maxim Afanasyev

Traditional economics often models firms as strategic actors and consumers as relatively passive responders. Agentic AI may reverse this asymmetry. Unlike many earlier enterprise technologies, agentic AI has been adopted rapidly by consumers, while firms remain constrained by organizational inertia, legacy systems, compliance requirements, and slow process redesign. This creates a setting in which consumers may become strategically more sophisticated than the enterprises serving them.

We develop a model of this consumer first mover advantage and study how agentic AI increases consumers’ ability to self serve, search, negotiate, substitute, and strategically bypass firm controlled processes. The model shows how this shift can reduce demand for some services and alter consumer behavior in ways that differ sharply from the pre agentic AI environment. These effects are particularly relevant in industries such as legal services, wealth advisory, education technology, e commerce, banking, and insurance.

The framework also helps explain several counterintuitive industry observations: AI may shift demand from services toward physical goods, create new financial stability risks, and reduce rather than increase consumers’ available leisure time. The results suggest that firms should move beyond viewing AI primarily as a productivity tool and instead treat agentic AI as a source of market structure change, demand disruption, and strategic consumer empowerment.

Senior Executive in AI, Solutions and Product Management, with 20+ years of experience and track record in academic research, management consulting, technology and financial services. Advisor to C-levels of major companies and prominent entrepreneurs on Applied AI, Industry trends and emerging technologies.

Joined DAO Team as Adj Assoc Prof in June, in addition to current role at Google Cloud, where provide partners, sales and engineering teams with insights on industry needs to ensure Google Cloud brings novel AI capabilities which are relevant to its clients, and monitor adoption and benefits from these capabilities in Asia Pacific and Japan. Before Google, have been leading large global AI engineering and transformation teams (200+ people and budgets of US$100M+) to build and deploy innovative AI solutions, deliver AI adoption strategies and unlock business value with new technologies across industries, both as an employee and as a consultant. Managed multibillion public and private equity technology investments portfolios before joining McKinsey to establish its AI Transformation capabilities. Stanford University PhD in Operations, Information and Technology. Started career as AI Researcher and worked at leadership roles for major companies in Asia, Europe and North America.

At NUS, Maxim’s research focuses on AI economics, Human-AI and AI Transformations. Maxim is teaching Applied AI use case factory (BSM5213) for Master and MBA students and various Executive Education courses on Applied AI Transformation. Maxim is co-author of “Designing the AI Ready Organization” book which is contracted to be published in 1H 2027. Maxim in his NUS capacity is one of two key contributors named at SAFR, Agentic Governance framework, released by Monetary Authority of Singapore in July 2026.