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Sustainable AI by Design

Your AI Usage Is a
Scope 3 Emission.
Make It Measurable.

Under the GHG Protocol, every AI query your organisation sends to a third-party model is a Scope 3 Category 1 emission. Songlines Control® makes it visible, reportable, and reducible — with AASB S2 mandatory disclosure beginning in FY2026.

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4.32g
CO₂e per GPT-4 query (GHG Protocol)
30–60%
Emissions reduction via intelligent routing
FY2026
AASB S2 mandatory disclosure begins
14 days
To full Scope 3 AI emissions baseline
The Hidden Emissions Problem

AI Inference Is Already in Your Scope 3. You Just Cannot See It Yet.

Most organisations have a well-developed approach to Scope 1 and Scope 2 emissions. Scope 3 is harder — and within Scope 3, AI inference is the fastest-growing and least-measured category.

Under the GHG Protocol Scope 3 Standard, Category 1 covers purchased goods and services. Every AI query your employees send to ChatGPT, Microsoft Copilot, Google Gemini, or any other third-party model is a Category 1 emission — purchased compute, consumed on your behalf, generating carbon you are responsible for reporting.

"The financial cost of an AI query and its environmental impact are the same variable. Governing one governs both."

With AASB S2 mandatory climate disclosure beginning in FY2026, the ability to measure and report AI-related emissions is no longer optional. The organisations that build this capability now will be ahead of their auditors — not behind them.

Illustrative Annual AI Emissions Estimate
Organisation size
10,000 employees
AI queries per employee per day
10 queries
CO₂e per GPT-4 query
4.32g CO₂e
Annual queries
36.5 million
Estimated annual AI emissions
~157 tCO₂e
After Songlines Control® routing
47–110 tCO₂e
Source: GHG Protocol Scope 3 Standard, Category 1. CO₂e estimates based on published inference energy data (Luccioni et al., 2023; IEA, 2024). Actual figures vary by model, region, and usage pattern.
Regulatory Obligations

The Reporting Obligations Are Already Set.

Australian organisations face a converging set of mandatory disclosure requirements that make AI emissions measurement a compliance obligation — not a voluntary initiative.

AASB S2 / IFRS S2
Climate-Related Financial Disclosures
Mandatory climate disclosure for large Australian entities. Requires reporting of Scope 1, 2, and material Scope 3 emissions — including AI inference under Category 1 (purchased goods and services). Auditor verification required from FY2027.
Mandatory from FY2026
GHG Protocol
Scope 3 Category 1 — Purchased Goods & Services
The GHG Protocol Scope 3 Standard classifies third-party AI inference as Category 1 emissions. Organisations using ChatGPT, Copilot, Gemini, or any API-accessed model are already generating reportable Scope 3 emissions — whether they know it or not.
Already in effect
ISO/IEC 42001:2023
AI Management System Standard
The international standard for AI management systems includes environmental impact as a required consideration. Organisations seeking ISO 42001 certification must demonstrate awareness and management of their AI environmental footprint.
Certification available now
How Songlines Control® Helps

Measure. Reduce. Report.
Three Modes. One Platform.

Songlines Control® addresses AI sustainability through the same three operating modes that govern cost, compliance, and security — because the mechanism is identical.

01
Observe Mode
Full Scope 3 AI Emissions Visibility
Deploy in Observe Mode with zero disruption to existing workflows. Every AI interaction is logged, attributed by team and model, and mapped to a CO₂e estimate using published inference energy data. Within 14 days, you have a complete Scope 3 Category 1 AI emissions baseline — verified, auditable, and ready for AASB S2 disclosure.
Sustainability Outcome
Verifiable Scope 3 Category 1 AI emissions baseline. Auditor-ready data for AASB S2 mandatory disclosure.
02
Enforce Mode
30–60% Emissions Reduction via Intelligent Routing
Enforce Mode activates intelligent model routing — automatically directing each query to the most cost-efficient and lowest-emission model capable of handling it. GPT-4 queries that can be served by a smaller, more efficient model are rerouted transparently. The result is a 30–60% reduction in both token spend and AI-related emissions simultaneously.
Sustainability Outcome
30–60% reduction in AI-related Scope 3 Category 1 emissions. Verifiable reduction trajectory for sustainability reporting.
03
Orchestrate Mode
Up to 100% Elimination on Cached Queries
Orchestrate Mode adds semantic caching — storing the results of previous AI queries and serving them directly for semantically equivalent requests, without sending any query to an external model. Cached queries generate zero inference emissions. For organisations with high query repetition (support, HR, legal, procurement), this can eliminate a significant proportion of AI emissions entirely.
Sustainability Outcome
Zero emissions on cached queries. Measurable reduction in total AI inference volume and associated Scope 3 footprint.
The Dual Mandate

Cost Governance and Emissions Reduction Are the Same Mechanism.

This is the insight that changes the conversation. The financial cost of an AI query and its carbon footprint are both functions of the same variable: compute consumed. Reduce one, and you reduce the other — automatically, without any trade-off.

This means the business case for AI governance does not require a separate sustainability justification. The ROI from cost reduction funds the sustainability outcome. The compliance requirement for AASB S2 disclosure funds the governance infrastructure. Both are served by a single deployment.

"The organisations that govern their AI usage now will not just reduce their spend by 30–60%. They will have a verifiable, auditable Scope 3 reduction trajectory ready for their first mandatory AASB S2 disclosure."
Governance Action Cost Outcome Emissions Outcome
Intelligent model routing 30–60% cost reduction 30–60% emissions reduction
Semantic caching Up to 100% cost elimination on cached queries Zero emissions on cached queries
Usage visibility & attribution Budget control by team Scope 3 Category 1 baseline for AASB S2
Policy enforcement Elimination of wasteful or redundant queries Reduction in total inference volume
Immutable audit trail Verifiable cost attribution Auditor-ready emissions data
The Starting Point

14-Day Baseline Assessment

A non-disruptive deployment of Songlines Control® in Observe Mode. No changes to existing workflows. No disruption to your teams. Within 14 days, you have everything you need for your first AASB S2 AI emissions disclosure.

1
Complete AI Usage Inventory
Every model, every team, every workflow — a full picture of your organisation's AI consumption, attributed by department and use case.
2
Scope 3 Category 1 AI Emissions Estimate
A verified CO₂e estimate calculated to GHG Protocol standards, ready for inclusion in your AASB S2 climate disclosure.
3
Cost Attribution Report
AI spend broken down by team, model, and workflow — identifying the highest-cost and highest-emission use cases for prioritised reduction.
4
Reduction Trajectory
A modelled projection of what 30–60% emissions reduction looks like for your specific usage profile — with the governance actions required to achieve it.
5
Executive Readout
A board and sustainability committee-ready summary, suitable for inclusion in your FY2026 AASB S2 disclosure preparation.

Start Your Baseline Assessment

Deploy in Observe Mode. No disruption to existing workflows. Full Scope 3 AI emissions baseline in 14 days — ready for your FY2026 AASB S2 mandatory disclosure.

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Non-disruptive deployment. No changes to existing workflows. Results in 14 days.
White Paper

The Dual Mandate: Aligning AI Governance with Corporate Sustainability Targets

The full methodology, regulatory obligations, and reduction pathway. June 2026 · 8 pages.

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