As generative AI and AI search technologies rapidly transform the digital ecosystem, the structure of marketing is undergoing a fundamental shift. Traditional advertising-driven strategies are increasingly facing limitations, while information discovery and content-based archives are emerging as central mechanisms through which consumers interact with brands.
Within this evolving environment, a new conceptual framework known as the Synapsco Architant Cycle Theory has been proposed as an integrated model that explains the cyclical relationship between human cognition, consumer behavior, and AI-driven information environments.
The theory originates from Cheongdam Circulation Theory, which interprets human life and decision-making as a continuous journey between uncertainty and choice. Building upon this philosophical foundation, the framework expands into Cheongdam Circulation Structural Theory, a structural model designed to explain how cognition, information processing, and behavior interact within cyclical systems.
At the core of this structure lies the MSAI-ICOM Cognitive Framework.
MSAI represents a nonlinear interaction environment consisting of Message, Story, Asset, and Interaction, where brands and consumers encounter information through diverse communication channels and content experiences.
These interactions are then organized through the ICOM structure, which consists of Input, Control, Output, and Memory.
Within this system, the Control stage functions as a decision and interpretation layer, comparable to a controller or CPU within an information system. It processes incoming information, determines its meaning, and guides how it is transformed into outputs.
The processed results are stored in Memory, and accumulated knowledge flows back into future inputs. This feedback loop creates a continuous cognitive cycle where information and experience reinforce future awareness and decisions.
This cognitive process is reflected in consumer behavior through the AISPUS model,
which describes six stages:
Attention - Interest - Search - Purchase - Use - Synergy
Unlike traditional linear marketing funnels, the AISPUS model explains consumer behavior as a cyclical structure in which experience, feedback, and interaction generate new awareness and repeated engagement.
In AI search environments, the Search stage increasingly evolves into a question-based exploration process. This dynamic is conceptualized as AQA (AI Question Answer).
When AQA is integrated with the AISPUS structure, the model expands beyond a traditional consumer behavior framework and becomes a Consumer Behavior Response Model, where user questions, AI responses, and experiential feedback continuously influence subsequent behavior.
From a marketing perspective, this evolving structure is described as AI Archive Marketing,
which consists of four key components:
AQA – AI Question Answer
BICF – Brand In Content Flow
ACE – AI Choice Essence
CSI – Cycle Synergy Index
Within this framework, marketing shifts away from simple advertising exposure and toward the accumulation of searchable information archives.
Consumers discover information through AI-mediated questions, encounter brands within content flows, make decisions based on contextual knowledge, and contribute new information through sharing and feedback.
Industry observers suggest that this structure may help address the growing phenomenon of advertising avoidance, which has become increasingly prominent in traditional digital marketing environments.
Because consumers voluntarily search for answers rather than passively encountering advertisements, the interaction becomes more organic, trust-driven, and experience-based.
Furthermore, this cyclical information structure indicates the potential emergence of AI-driven service ecosystems, where content, discovery, recommendation systems, and transactions are interconnected.
Such systems could evolve into integrated one-stop marketplaces built upon AI search and information archives.
Synapsco Architant Cycle Theory explains the cyclical relationship between human cognition,
consumer behavior, and AI archive marketing in the AI search era.
Core Summary
• Marketing structures are shifting from advertising-driven models to information archive-based ecosystems.
• The Synapsco Architant Cycle Theory integrates the MSAI-ICOM cognitive framework with the AISPUS consumer behavior model.
• In AI search environments, question-based exploration (AQA) expands the consumer behavior cycle into a Consumer Behavior Response Model.
• The AI Archive Marketing structure consists of AQA, BICF, ACE, and CSI.
• This framework suggests new possibilities for AI-driven marketing ecosystems and integrated digital marketplaces.
Synapsco Architant | maidasha
Synapsco Architant AI Research Group
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