What are the risks of AI washing in intangible asset valuations?
Short Answer
AI washing — overstating AI capabilities or AI-driven value — can inflate intangible asset valuations, mislead investors, and create impairment risk when the claimed AI functionality fails to deliver projected economic benefits.
Full Explanation
AI washing occurs when companies exaggerate the role, sophistication, or impact of AI in their products or operations. In the context of intangible asset valuations, AI washing creates several risks. First, inflated revenue projections based on overstated AI capabilities lead to overstated asset values in income-based valuations (MPEEM, RFR, With-and-Without). If the AI does not deliver the projected revenue or cost savings, the asset becomes impaired. Second, in M&A transactions, AI washing can inflate the purchase price, resulting in excessive goodwill that will need to be impaired when synergies do not materialise. Third, misclassifying rule-based automation as AI may lead to incorrect useful life assumptions — true AI models may warrant different treatment than traditional software. Regulators are increasingly scrutinising AI claims: the FCA, SEC, and EU AI Act all address misleading AI representations. For valuers and auditors, due diligence on AI assets should include technical validation (does the system actually use machine learning?), performance benchmarking (does it outperform non-AI alternatives?), and dependency analysis (what happens if key data sources or talent are lost?). Opagio's questionnaire includes validation checks to distinguish genuine AI capability from AI washing.
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Further Reading
AI Cost Reduction: How to Measure Real Operational Savings
AI vendors promise dramatic cost reductions, but actual savings depend on total cost of ownership, implementation quality, and measurement rigour. This article provides a practical methodology for measuring real AI-driven operational savings — net of all hidden costs.
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