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Integrating Artificial Intelligence into Product Life Cycle Value and Activity Value Management: A Case Study
of P Channel Agent

Integrating Artificial Intelligence into Product Life Cycle Value
and Activity Value Management: A Case Study of P Channel
Agent

Shao-Syuang Li, PwC Taiwan
Cheng-Jen Huang, Department of Accounting, National Chengchi University

1. Purpose / Objective

The primary objective of this research is to develop a comprehensive framework

that integrates Product Life Cycle Value (PLCV) with Activity Value Management (AVM)
through the incorporation of Artificial Intelligence (AI) technologies. It aims to bridge the
gap between accounting-based value management and data-driven marketing analytics
by creating an intelligent system capable of predicting product performance, optimizing

resource allocation, and supporting sustainable strategic decision-making.
While traditional Activity-based Costing (ABC) systems focus primarily on cost
accuracy and efficiency improvement, they often fail to capture product value dynamics
across the life cycle or to provide predictive insights. Derived from marketing and

customer lifetime value (CLV) perspectives, PLCV similarly has limited linkage to
managerial accounting systems. This paper thus presents an AI-augmented PLCV-AVM
model that integrates accounting, marketing, and data science perspectives.
Recent advances in artificial intelligence and analytics have fundamentally altered

how firms generate, interpret, and act upon value-related information, thereby reshaping
customer value creation processes and strategic decision-making logics (Grewal,
Satornino, Davenport, and Guha, 2025). However, most management accounting systems
remain primarily backward-looking, emphasizing historical cost allocation rather than

anticipating future value creation. This limitation is particularly salient in channel
distribution contexts, where product portfolios evolve rapidly and managerial decisions
must balance short-term profitability with long-term strategic sustainability. By explicitly
addressing this gap, the present study positions PLCV not merely as an extension of CLV,

but as a managerial construct that translates market dynamics into actionable accounting
intelligence.

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