AITB No. 25 Accounting for AI-Powered Healthcare Diagnostic Systems
Issue: How should healthcare entities account for costs and benefits associated with the deployment of AI-powered diagnostic systems?
Background: AI is revolutionizing healthcare by assisting in the diagnosis of diseases through the analysis of medical images, genomic sequences, and other complex data. These systems can increase diagnostic accuracy, speed up patient care, and reduce costs.
Guidance:
- Capitalization of Diagnostic System Costs: Expenses related to the development or acquisition of AI-powered healthcare diagnostic systems for long-term clinical use should be capitalized as an intangible asset.
- Expensing of Data Collection and Model Training: Costs associated with collecting patient data or training the AI model to refine diagnostic accuracy should be expensed as incurred.
- Amortization of Capitalized System Costs: The capitalized costs should be amortized over the system's expected useful life, considering technological advancements, evolving medical practices, and regulatory changes.
- Benefit Recognition: Financial benefits arising from improved patient outcomes, reduced misdiagnoses, and optimized clinical operations due to the AI system's capabilities should be recognized in the income statement in the corresponding period.
Examples:
- Hospital Y invests $5M in an AI-powered diagnostic system expected to be effective for 10 years. They would capitalize the $5M and amortize it over the 10-year timeframe.
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.