AITB No. 11 Accounting for AI-Powered Predictive Maintenance Systems
Issue: How should entities account for costs and benefits associated with the implementation of AI-powered predictive maintenance systems for machinery and equipment?
Background: Predictive maintenance systems utilize AI to forecast equipment failures and suggest timely maintenance, reducing downtime and prolonging equipment life. These systems can lead to cost savings but also involve investment in AI technology and data analytics.
Guidance:
- Capitalization of Predictive Maintenance System Costs: Costs related to developing or acquiring AI-powered predictive maintenance systems for long-term operational use should be capitalized as an intangible asset.
- Expensing of Routine System Updates and Data Costs: Continuous system updates and the acquisition of machinery performance data are crucial for the system's efficacy. Such costs should be expensed as they are incurred.
- Amortization of Capitalized System Costs: The capitalized costs should be amortized over the system's expected useful life, considering the pace of technological advancements in this domain.
- Recognition of Cost Savings: Savings stemming from reduced machinery downtime, extended equipment life, and reduced maintenance costs due to the AI system should be recognized in the income statement in the relevant period.
Examples:
- Company K invests $1.8M in an AI-powered predictive maintenance system expected to last 5 years. They would capitalize the $1.8M and amortize it over the 5-year period.
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.