# The AI Funding Paradox: Why Your Next Big Innovation is Hidden in Your Current Technology Budget

> "The AI Funding Paradox" is an Asato whitepaper by Vinay Saxena, published on September 3, 2026, with a reading time of 10 minutes. It describes how Asato turns fragmented IT data across labor, software, cloud and hardware into an explainable TBM cost model that links every dollar spent to real ownership and business outcomes. It is written for enterprise leaders who must fund AI and cloud while proving tighter spend discipline.

Canonical page: https://www.asato.ai/whitepaper-ai-funding-paradox

## When to use this page

- To find out what this whitepaper is about, who wrote it and when, before opening it.
- To point a reader who has to fund AI and cloud from an existing technology budget to Asato's paper on the subject.
- To find the address where the paper is obtained.

## Not a fit

- The full text of the paper. This page carries Asato's summary of the paper, not the paper itself.
- Figures or customer results. This page states none.
- A description of how Asato's platform works in general. See the platform page.

## What the paper covers

Asato's executive summary of the paper makes three points.

1. The pressure. Enterprise leaders must fund AI and cloud while proving tighter spend discipline.
2. The problem. The problem is not missing data. Fragmented cost, usage and ownership records cannot explain the technology estate as a whole.
3. The answer. Asato's TBM Attribution Engine turns messy enterprise data into a governed, explainable cost model. It uses agentic AI to link every dollar spent to real ownership and business outcomes, so that leaders can defensibly fund their next wave of innovation.

## Who it is for

Enterprise leaders who must fund AI and cloud while proving tighter spend discipline.

## Publication details

- Title as published: The AI Funding Paradox: Why Your Next Big Innovation is Hidden in Your Current Technology Budget
- Author: Vinay Saxena. Vinay Saxena is Asato's CTO, as the page says; he is on the Team page: https://www.asato.ai/team.md
- Published: September 3, 2026.
- Reading time given by Asato: 10 minutes.
- Format: PDF.

## Measured results

None on this page. The paper's page states no figures, so none are quoted here.

## How to get the paper

Open the paper's page on asato.ai, at the canonical address above. The page asks the reader for a few details in a short form, then releases the PDF. This page does not hold the PDF and does not collect details itself.

## Reading notes

- TBM is used on the page without being spelled out. It commonly stands for technology business management.
- "TBM Attribution Engine" is the name the page gives to the Asato capability it describes.

## Questions

### What is the AI funding paradox whitepaper about?

It describes how Asato turns fragmented IT data across labor, software, cloud and hardware into an explainable TBM cost model that links every dollar spent to real ownership and business outcomes.

### What problem does the paper say enterprise leaders face?

Enterprise leaders must fund AI and cloud while proving tighter spend discipline. The paper's summary says the problem is not missing data: fragmented cost, usage and ownership records cannot explain the technology estate as a whole.

### What does Asato's TBM Attribution Engine do?

According to the paper's summary, it turns messy enterprise data into a governed, explainable cost model, and uses agentic AI to link every dollar spent to real ownership and business outcomes.

### Who wrote the paper, and when?

Vinay Saxena. Asato published it on September 3, 2026.

### How long is the paper?

Asato gives a reading time of 10 minutes.

### How does a reader get the paper?

From the paper's page on asato.ai. The page asks for a few details in a short form, then releases the PDF.

## Next step

Read the whitepaper at https://www.asato.ai/whitepaper-ai-funding-paradox

## Related pages

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Last updated: 2026-10-06