Your team is using AI to produce sustainability work. Someone should check what it is actually saying.
AI generates sustainability strategies, ESG disclosures, circularity recommendations, and board materials with apparent authority and considerable speed.
It does not always generate them on sound assumptions.
The AI Sustainability Assumption Audit is a diagnostic review of AI-generated sustainability outputs — strategies, reports, claims, board memos, framework comparisons — to identify what assumptions they are carrying before those assumptions are acted on, published, or submitted.
$1,500. One audit memo. One review call. Four to five business days.
The risk no one is talking about
AI is not wrong about sustainability. It is fluent in the wrong frame.
AI systems are trained on the existing sustainability corpus — the frameworks, standards, reports, guidance documents, and institutional language the field has produced over decades.
That corpus is extensive. It is also the reason sustainability has produced more activity than transformation for forty years.
The assumptions that have kept sustainability work structurally optional, dependent on market conditions that never fully arrived, organised around reporting rather than redesign, and separated from the business decisions that actually govern outcomes — those assumptions are baked into the corpus. They are what the field has written down.
When AI returns a confident, well-structured sustainability answer, it may be reproducing those assumptions in new language — at higher speed, with greater apparent authority, and with less friction to challenge than a human consultant would face.
The danger is not that AI is always wrong.
The danger is that it can be perfectly fluent in the wrong frame — and that fluency is exactly what makes it hard to catch.
A board deck produced by AI looks like expertise. An ESG disclosure drafted by AI reads like diligence. A circularity strategy generated by AI carries the vocabulary of the field.
None of that means the assumptions underneath have been examined.
This audit is for principals and leaders who have commissioned AI-generated sustainability work and want to know what they actually have.
The AI Sustainability Assumption Audit is most useful when:
- AI has been used to draft a sustainability strategy that will govern investment or public positioning
- An ESG or sustainability report has been produced with AI assistance and will be submitted to investors, regulators, or a rating agency
- A board memo or leadership brief on sustainability has been generated using AI and will inform a significant decision
- A circularity or net-zero plan contains AI-generated recommendations that have not been independently reviewed
- A consultant has delivered work produced with AI assistance and you want to understand what it is built on
- Your team is using AI routinely in sustainability workflows and no one has examined whether the outputs are carrying the field’s inherited assumptions forward
The question is not whether AI is useful in this work. It is.
The question is whether the specific outputs your organisation is acting on have been properly diagnosed.
What The Audit Examines
You submit a defined packet of AI-generated sustainability materials — up to 10 pages of output, or equivalent prompt-response logs.
These may include any of the following:
- AI-generated sustainability strategy drafts
- ESG or annual report sections
- circularity or net-zero recommendations
- product or packaging claims
- board memos or leadership briefs
- prompt-response logs from internal AI workflows
- framework comparisons or regulatory summaries
- consultant deliverables produced with AI assistance
Ken reviews the materials for:
- Inherited assumptions treated as neutral expertise — where the AI has reproduced the field’s operating consensus without flagging it as a position
- Strategy-layer answers to assumption-layer problems — where the output addresses the visible challenge while leaving the real constraint untouched
- Reporting language mistaken for transformation — where the output describes what is being measured rather than what is changing
- Circularity framed as technical loop closure — where the output treats material flows as the constraint rather than the business model
- Business-case logic that keeps sustainability structurally optional — where the financial framing preserves the conditions under which sustainability can always be deferred
- Responsibility boundaries left untested — where the output assumes partners, markets, or infrastructure will solve what the organisation has not committed to
- Confident answers that reproduce the consensus the work needs to examine — where fluency substitutes for diagnosis
How it works
Step 1 — Submit Materials
You provide a defined packet of AI-generated sustainability materials: up to 10 pages of output or equivalent prompt-response logs, with a brief note on how the materials were produced and what decisions they are intended to inform.
Step 2 — Diagnostic Review
Ken reviews the materials through the same diagnostic framework used in the Sustainability Ceiling Diagnostic™ — applied specifically to AI-generated output.
The review identifies where the outputs are sound, where they are carrying forward assumptions that have not been examined, and where the gap between AI-generated confidence and actual diagnostic rigour is consequential.
Step 3 — Audit Memo and Review Call
You receive a written AI Sustainability Assumption Audit memo, typically within four to five business days.
The memo is followed by a 45-minute review call with Ken to discuss findings, answer questions, and identify what further work — if any — is warranted.
What you receive
The written audit memo identifies:
- Where the AI outputs are sound and reliable — what can be used with confidence
- Where they are reproducing untested assumptions — what has been carried forward from the field’s existing consensus without examination
- What frames are being repeated — the recurring positions, framings, or logical structures the AI is defaulting to
- What questions are absent — what a rigorous diagnostician would have asked that the AI output did not surface
- Where responsibility boundaries remain invisible — what the outputs are assuming others will solve
- Where human diagnostic review is needed before the output is used — the specific passages or recommendations that should not be acted on without further examination
- Recommendations for better prompts, review criteria, and decision safeguards — practical guidance for improving how AI-generated sustainability work is produced and reviewed going forward
$1,500
Scope: up to 10 pages of AI-generated output with one audit memo and one review call. Additional materials or expanded scope: quoted separately before work begins.[Book the AI Sustainability Assumption Audit →
What this audit is and is not
The AI Sustainability Assumption Audit is not an AI implementation service.
It is not prompt engineering, model evaluation, or a technical assessment of the AI system used.
It is not a legal review, regulatory compliance check, or claims-compliance audit.
It is not a substitute for the full Sustainability Ceiling Diagnostic™, which examines the broader belief architecture governing an organisation’s sustainability work — not only its AI-generated outputs.
It is a diagnostic review of whether AI-supported sustainability outputs are carrying assumptions that have not been examined — and what that means for the decisions they are intended to inform.
Confidentiality
The materials you submit, Ken’s review, and the written audit memo are confidential.
Nothing is published, cited, referenced, or used in any form without explicit written permission.
The audit memo belongs to you.
Before AI-generated sustainability language enters a strategy, a board deck, a regulatory submission, or a public claim — examine what it is carrying.
The speed at which AI can produce sustainability content is not, by itself, a risk.
The risk is that the content looks like expertise, reads like diligence, and carries the vocabulary of the field — while reproducing the same assumptions that have kept sustainability work from changing the decisions that matter.
By the time those assumptions surface, they may be embedded in a strategy that has been approved, a commitment that has been made public, or a disclosure that has been submitted.
The AI Sustainability Assumption Audit is designed to catch that before it happens — quickly, confidentially, and at a scope that does not require a full diagnostic engagement to begin.
$1,500. Four to five business days. One memo that tells you what you actually have.
Book the AI Sustainability Assumption Audit →
If you want to examine the assumptions beneath your broader sustainability strategy, not only the AI-generated outputs: Explore the Sustainability Ceiling Diagnostic™ →
If you want a first look at what your sustainability restructure may have left exposed: Explore the Ceiling Snapshot →