Necessity of Artificial Intelligence Appraisal
1. Role and Cost Structure of Current Appraisal Institutions
Technology appraisal institutions review technical, patent and rights, market, manufacturing, and revenue materials and assess technology value by considering technical merit, rights, marketability, commercialization, profitability, and risks. Market research, comparable-technology research, site checks, outside experts, internal review, calculation, and report preparation can require substantial time and cost, making access difficult for individual inventors, early-stage founders, and SMEs.
2. Current Appraisal Institutions Already Use AI
Appraisal and evaluation institutions already use artificial intelligence, big data, automated valuation models, and digital evaluation systems. The key issue is therefore not whether AI is used, but what input data and appraisal elements are used and under what conditions, methods, formulas, deduction rules, and risk-adjustment standards AI performs the appraisal.
3. Main Elements of Technology-Value Appraisal
Key elements include identification of the subject, rights, technical merit, feasibility, marketability, commercialization, revenue model, manufacturing and cost, risk and deduction standards, value calculation, and verification logs. The appraisal should structurally review rights scope, technical structure, differentiation from prior art, prototypes and manufacturing process, market size and growth, OEM/ODM and licensing potential, revenue sustainability, production cost, and relevant risks.
4. Instruct AI on Appraisal Conditions and Methods
It is not sufficient simply to tell AI, “appraise the value of this technology.” Appraisal elements, input data, evaluation items, formulas, treatment of missing data, deduction standards, and risk-adjustment methods should first be defined and then instructed to AI. The structure is: humans define the appraisal elements, conditions, and methods → instruct AI → AI performs the actual appraisal under the same standards.
5. Practical Reasons AI Appraisal Is Needed
AI can perform much of the repetitive classification, comparison, calculation, and organization of data, reducing appraisal cost and time. It can repeatedly apply the same elements, conditions, and calculation rules, reduce omissions and variation, record data and reasoning, and expand access for individual inventors, startups, and SMEs.
6. Evaluation and Respect for Appraisals Performed by AI
The essence of appraisal is not merely whether the evaluator is human or AI, but which elements, conditions, methods, data, and calculation standards were applied. If reasonable appraisal elements and methods are applied and the inputs, reasoning, and calculation process are verifiable, an appraisal should not be rejected, disparaged, or undervalued merely because AI performed it. Where data or methods are deficient, reliability should be reviewed regardless of whether the evaluator is human or AI.
7. Need to Activate the AI Appraisal Market
Since current appraisal institutions already use AI and automated evaluation technologies, professionally defined appraisal elements, conditions, and methods should also be used to instruct AI to perform actual appraisals in the technology-valuation market. This approach is useful for lowering cost and shortening time, and the market for AI appraisal should be actively developed.
8. Conclusion
IAEC is not a system that simply asks AI for a value. It aims to define professional appraisal elements, conditions, and methods, instruct AI with them, and have AI perform the actual technology-value appraisal under those standards. If the standards, data, methods, and process are appropriate and verifiable, the result should be evaluated on its elements, methods, and grounds rather than rejected or disparaged merely because AI performed the appraisal.