From AI usage to financial outcomes
Token consumption, model calls, pilot counts, and employee usage rates describe adoption activity. They do not, on their own, show how much economic value a firm retains from using AI.
The paper connects effective task outputs to financial outcomes through Token-to-Profit Conversion. It considers net operating profit after tax (NOPAT), return on invested capital (ROIC), economic value added (EVA), and firm value.
Two forms of capital
AI-related invested capital is the money committed to building, integrating, maintaining, and governing AI systems. AI utilization capital is the reusable organizational capability developed through human review, feedback, documentation, and workflow learning.
The proposed framework asks whether productivity gains become profit that the firm can capture, and whether the resulting returns exceed the cost of AI-related capital. It is a financial framework, not a claim that AI adoption necessarily improves firm value.
Paper details and original text
An English-language working paper published on SSRN. The date shown for this Research entry is the first SSRN posting date.
| Item | Details |
|---|---|
| Original title | From Tokens to Firm Value: A Financial Framework for Token-to-Profit Conversion in Generative AI Adoption |
| Author | Seiryu Ando |
| Date written | 2026-07-09 |
| First posted on SSRN | 2026-07-13 |
| DOI | 10.2139/ssrn.7088042 |
Read the working paper
Read the proposed financial framework and its definitions in the original paper.