AITB No. 55 Accounting for AI-Driven Predictive Maintenance in Manufacturing
Issue: How should entities in the manufacturing sector account for costs and benefits associated with the deployment and operation of AI-driven predictive maintenance systems?
Background: To optimize production, reduce downtimes, and extend machinery life, manufacturers are leveraging AI-driven predictive maintenance. These systems predict when equipment will fail, allowing timely intervention, which in turn reduces costs and enhances production efficiency.
Guidance:
- Capitalization of Predictive Maintenance System Costs: Expenses related to the development, acquisition, or implementation of AI-driven predictive maintenance systems for long-term operational efficiency should be capitalized as tangible assets.
- Expensing of Data Collection and Analysis Tools: Costs related to sensors, data collection devices, and tools for analyzing machinery health and predicting maintenance needs based on AI algorithms should be expensed as incurred.
- Depreciation of Capitalized System Costs: The capitalized costs should be depreciated over the system's expected useful life, factoring in technological advancements, machinery life cycles, and industry best practices.
- Benefit Recognition: Financial benefits arising from reduced maintenance costs, optimized production schedules, extended machinery life, and reduced downtimes due to the AI system's predictions should be recognized in the income statement in the respective period.
Examples:
- Manufacturing firm C2 invests $4.5M in an AI-driven predictive maintenance system, anticipating benefits over an 8-year span. They would capitalize the $4.5M and depreciate it over the 8-year duration.
Note: This is a fictional representation and does not represent any real-world standard for AI. The development of such standards would involve extensive consultations with experts, stakeholders, and the public. Fictional representations simplify complex AI concepts, stimulate discussion, envision future scenarios, highlight ethical considerations, encourage creativity, bridge knowledge gaps, and set benchmarks for debate in fields like accounting.