---
sourceDocument: Australia Operational Sustainability Management (formerly Environmental, Social, and Governance)
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/environmental-social-governance

 Release :

    - australia

ft:locale :

    - en-US

ft:publication_title :

    - Australia Operational Sustainability Management (formerly Environmental, Social, and Governance)

ft:clusterId :

    - esgv

bundleId :

    - esgv

workflow :

    - Technology


---

# Document intelligence for utility invoices

# Document intelligence for utility invoices {#ariaid-title1}

* Release version: Australia
* 
* Updated March 12, 2026
* 
* ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read

Summarize  
![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI  
This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete.  

## Summary of Document intelligence for utility invoices

Document Intelligence for Utility Invoices is an AI-driven feature within the Operational Sustainability Workspace that automates the extraction and processing of utility bill data.
It collects key information such as consumption, billing dates, amounts, and units of measurement, replacing manual data entry and improving accuracy, efficiency, and auditability.
This automation supports consistent operational sustainability reporting by handling diverse bill formats and languages.
Show full answer Show less  

## Key Features

* **AI-Extracted Data Verification:** Extracted fields are clearly marked for user verification, with options to override and justify changes, ensuring data integrity.
* **Audit Trail:** The original utility bill is attached to the metric data task for traceability and compliance evidence.
* **Configurable Data Mapping:** Extracted data is mapped to metric definitions and entities via configurable tables to align with operational metrics.
* **Unit Matching:** Units of measurement from invoices are matched against the Metric Unit table; unmatched units trigger warnings and incomplete unit references.
* **Error Handling:** Users can correct extraction errors and reprocess invoices as needed.
* **Role-Based Access:** Access to this feature requires the `snesggenai.docinteluser` role assigned to ESG users.
* **Date Restrictions for Manual Metrics:** Manual metric definitions process only standard monthly periods; automated metrics support irregular date ranges for flexibility.
* **Scalability and Integration:** Supports manual uploads and can be extended to integrate with email or other document intake methods.

## Benefits

* Significantly reduces manual workload and errors in utility data collection for sustainability reporting.
* Enhances consistency and accuracy in operational sustainability metrics.
* Improves auditability and compliance through evidence attachment and traceability.
* Supports diverse utility document types and multiple languages.

## Using the Feature

After data extraction and mapping, users can review key details such as consumption, billing dates, amounts, and units on the metric data task page. The extraction status is visible, and AI-marked data fields can be reviewed and overridden with justification. The original utility bill is attached for audit purposes. If extraction fails, users can correct errors and reprocess.

## Practical Considerations

* Ensure users have the required `snesggenai.docinteluser` role for access.
* Verify AI-extracted fields before using the data in reporting.
* Use automated metric definitions for invoices with irregular date ranges to comply with reporting standards.  
The AI-driven document intelligence for utility invoices feature automates metric data collection. It automates the metric data collection by extracting utility bill data such as consumption, billing dates, amounts, and units of
measurement within the Operational Sustainability Workspace.

## Document intelligence overview {#ai-driven-document-intelligence-for-utility-invoices__section_owp_fmz_ngc}

Document Intelligence for Utility Invoices automates utility bill data extraction and processing, removing manual entry for metric reporting. It streamlines the data collection process, improving accuracy and efficiency while
reducing the burden on data owners. This capability addresses the challenges of manual data collection, aggregation, and entry from diverse utility bill formats and languages. It promotes consistent and reliable operational
sustainability reporting.

The AI-extracted fields are clearly marked for verification. You can override and justify changes to confirm
data integrity. The original bill is attached to the metric data task for traceability and audit. After the extraction is completed, the extracted data is mapped to the correct metric definitions and entities using configurable
mapping tables. The system extracts units of measurement from invoices and attempts to match them to existing units in the Metric Unit (sn_grc_metric_unit) table. If a matching unit is found, the unit reference is populated in the
Metric Data record. If no matching unit is found, the Metric Data record is created without a unit reference, the extraction status shows Completed with Errors, and a warning message appears on the Invoice
Detail record. Data owners can review, validate, or override extracted data as needed. If the extraction process fails, you can correct the errors and rerun the extraction by selecting reprocess option.  
Note:  
The sn_esg_gen_ai.docintel_user role is required to view the option to document intelligence for utility bills. This role must be manually assigned to an ESG user.

To understand how you can extract details from the utility bills, refer to [Extract data from utility invoices](https://servicenow-prod.fluidtopics.net/u~MNdZNUvGq0RUvGXN2OYA "The AI-driven Document Intelligence for utility invoices feature automates the extraction of utility bill data, including consumption, billing dates, and amounts. Then the extracted data is mapped to the correct metric definitions and entities using configurable mapping tables within the Operational Sustainability Workspace. This streamlines data processing and enhances accuracy.").  
Note:  
The fields extracted by AI on the Metric Data task page must be verified for accuracy before use.

## Metric definition date restriction {#ai-driven-document-intelligence-for-utility-invoices__section_r4k_tvp_mhc}

When using Document Intelligence with manual metric definitions, the system only processes documents that cover standard monthly periods---where the start date is the first day of the month and the end date is the last day of the same
month.

If your source documents cover irregular date ranges, use automated metric definitions instead. Automated definitions can map and process data for any date range without the first/last day restriction, providing flexibility for
irregular billing cycles or custom periods. This limitation ensures consistency with operational sustainability reporting standards that require standard monthly periods for manual metric entries.

## Benefits of document intelligence for utility invoices {#ai-driven-document-intelligence-for-utility-invoices__section_cyx_jmz_ngc}

* Reduces manual workload and errors in operational sustainability data collection.
* Promotes consistency and accuracy in operational sustainability metric reporting.
* Enhances auditability and compliance with evidence management.
* Scales to handle diverse document types and languages.
* Supports manual uploads and can be extended to integrate with email or other intake flows.
{#ai-driven-document-intelligence-for-utility-invoices__ul_it5_lmz_ngc}

## Viewing extracted data summary {#ai-driven-document-intelligence-for-utility-invoices__section_sxt_2h1_4gc}

After the extraction and data mapping you can view the following:

* The extracted key details from the utility bill, such as consumption, billing dates, bill amount, and units of measurement, mapped to the relevant operational sustainability metric data task.
* The state of the extraction process (for example, complete or failed).
* AI-extracted fields clearly marked for user review.
* The option to review extracted data in the document intelligence review screen.
* The ability to override extracted data and provide justification if needed.
* The original utility bill attached as evidence for audit and compliance.
{#ai-driven-document-intelligence-for-utility-invoices__ul_ow5_vp1_4gc}
**Related concepts**   

* [Using ServiceNow Otto for Operational Sustainability skills](https://servicenow-prod.fluidtopics.net/8yDeHCIwsZCunWQ5xjGHfw "If you have the sn_esg_gen_ai.docintel_user role, you can use the ServiceNow Otto for Operational Sustainability skill to automate the extraction of metrics data from utility invoices. Then map the extracted data to the correct metric definitions and entities.")  
**Related tasks**   

* [Activate the document intelligence for utility invoices skill](https://servicenow-prod.fluidtopics.net/zCYo6FyS1yMrd1z_PtxK0w "Activate and then configure document intelligence for utility invoices skill from Now Assist to automate the extraction of metrics data from utility invoices. Once activated, map the extracted data to the correct metric definitions and entities.")