AI for Sustainability and ESG Reporting

About Course

Use AI to organise sustainability evidence, prepare data requests, check illustrative emissions calculations and draft balanced ESG narratives. Distinguish impact and financial materiality, reporting boundaries, emissions scopes, performance claims and assurance evidence. Includes 15 lessons, private practice with worked feedback and a 30-question final quiz.

LO01: Prepare a reporting brief with a clear purpose, audience and boundary.
LO02: Create traceable data requests and identify material evidence gaps.
LO03: Review illustrative emissions information with transparent methods and limitations.
LO04: Interpret ESG measures using appropriate boundaries, denominators and evidence.
LO05: Produce a reviewable reporting pack without overstating completeness or assurance.

Course Content

Reporting purpose and boundaries
Define AI’s role, distinguish reporting frameworks and document scope.

01. Define a responsible AI reporting role
02. Distinguish reporting frameworks and materiality lenses
03. Define the reporting boundary and period

Materiality and data quality
Organise materiality evidence and design reliable data collection and checks.

Emissions foundations
Classify emissions and test calculations and Scope 2 claims.

Value chain and performance
Screen Scope 3, compare targets and metrics and handle workforce measures.

Narrative, assurance and pilot review
Draft supportable claims, assemble evidence and evaluate AI use.

Assessment

Add this certificate to your resume to demonstrate your skills & increase your chances of getting noticed.

Student Ratings & Reviews

No Review Yet

AI for Sustainability and ESG Reporting

About Course

What Will You Learn?

Course Content

Reporting purpose and boundaries
Define AI’s role, distinguish reporting frameworks and document scope.

01. Define a responsible AI reporting role

02. Distinguish reporting frameworks and materiality lenses

03. Define the reporting boundary and period

Materiality and data quality
Organise materiality evidence and design reliable data collection and checks.

04. Organise materiality evidence without inventing stakeholder views

05. Design an ESG data request and dictionary

06. Check units, missing data and duplicates

Emissions foundations
Classify emissions and test calculations and Scope 2 claims.

07. Classify emissions within a stated organisational approach

08. Check an illustrative emissions calculation

09. Review Scope 2 methods and electricity claims

Value chain and performance
Screen Scope 3, compare targets and metrics and handle workforce measures.

10. Screen value-chain emissions and data options

11. Compare absolute and intensity performance

12. Prepare social and governance measures carefully

Narrative, assurance and pilot review
Draft supportable claims, assemble evidence and evaluate AI use.

13. Draft claims that match the evidence

14. Assemble an evidence pack for review and assurance

15. Evaluate a reporting pilot with a release checklist

Assessment

AI for Sustainability and ESG Reporting – Final Quiz

Earn a certificate

Share this course

About Course

What Will You Learn?

Course Content

Reporting purpose and boundaries Define AI’s role, distinguish reporting frameworks and document scope.

01. Define a responsible AI reporting role

02. Distinguish reporting frameworks and materiality lenses

03. Define the reporting boundary and period

Materiality and data quality Organise materiality evidence and design reliable data collection and checks.

04. Organise materiality evidence without inventing stakeholder views

05. Design an ESG data request and dictionary

06. Check units, missing data and duplicates

Emissions foundations Classify emissions and test calculations and Scope 2 claims.

07. Classify emissions within a stated organisational approach

08. Check an illustrative emissions calculation

09. Review Scope 2 methods and electricity claims

Value chain and performance Screen Scope 3, compare targets and metrics and handle workforce measures.

10. Screen value-chain emissions and data options

11. Compare absolute and intensity performance

12. Prepare social and governance measures carefully

Narrative, assurance and pilot review Draft supportable claims, assemble evidence and evaluate AI use.

13. Draft claims that match the evidence

14. Assemble an evidence pack for review and assurance

15. Evaluate a reporting pilot with a release checklist

Assessment

AI for Sustainability and ESG Reporting – Final Quiz

Earn a certificate

Student Ratings & Reviews

Reporting purpose and boundaries
Define AI’s role, distinguish reporting frameworks and document scope.

Materiality and data quality
Organise materiality evidence and design reliable data collection and checks.

Emissions foundations
Classify emissions and test calculations and Scope 2 claims.

Value chain and performance
Screen Scope 3, compare targets and metrics and handle workforce measures.

Narrative, assurance and pilot review
Draft supportable claims, assemble evidence and evaluate AI use.