This brief reflection on the impact of Artificial Intelligence (AI) on business valuations will focus on the valuation of unquoted entities. I believe that the use of the tools offered by AI will bring very significant changes to the business valuation profession. These developments will occur in a relatively short time and will be articulated in two phases. First phase – generation of valuation metrics based on the implementation of machine learning algorithms and initial automated or semi-automated valuation processes. The first attempts in this direction are already underway and stem from the possibility of “predicting” the current capitalization of a listed company with good accuracy, starting from a set of publicly available standardized data (Koklev, 2022), to then infer usable parameters, possibly after appropriate adjustments, for valuing unlisted companies (Jagrič, Fister, Grbenic, Herman, 2024). The quality of the predictions may be improved by training the algorithms on datasets selected by industry, geographic area, and reference sample size. Second phase – development of integrated valuation models, combining metrics and predictions generated by machine learning with the collection, analysis, and synthesis of unstructured information performed by large language models.
The availability of reliable business valuations, carried out in a very short time and at very low cost, will radically change the circulation of securities and rights representing the capital of unlisted companies and businesses, as well as the rights representing business units and intangible assets.
There are two possible contrasting scenarios that could have consequences for business valuers: The first, pessimistic, foresees the exit from the market of a significant part of the professionals currently involved in business valuations, consequently not so much of the automation of valuation processes, but of the sharp reduction in prices to the final customer. The activity of the professionals who will remain on the scene will consist of monitoring and continuously improving the valuation processes, as well as intervening in pathological cases, where personal expertise will always remain an essential element (for example, in the case of judicial disputes, fraud, etc.). The second, optimistic, is related to the many professional opportunities arising from the capital market benefits of AI-based valuation applications. It is reasonable to assume that as valuations multiply, there will be a greater demand for professional skills to critically understand the results and derive insights to improve corporate performance and business strategies. For valuation professionals, the current outlook suggests that the resulting challenges and opportunities should be addressed now.
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