The working method of practitioners who use AI on real sustainability disclosures every day — and who build AI tools and automations for that work. This free course runs across the whole ESG reporting lifecycle: standards analysis, double materiality, data quality, drafting, greenwashing review and assurance readiness. Not just a prompt list, and not AI writing your report — a disciplined way of working that keeps human judgment in charge of every disclosure.
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Evidence-first — human judgment in charge
The frame for this course is the AI-assisted ESG reporting lifecycle — not "100 prompts" and not automatic report-writing. It's the system LRA's own practitioners use on real disclosures — built around professional judgment, an evidence base, governance and assurance readiness, with AI integrated and the repetitive parts automated where it earns its place. Across 14 modules in three parts, you learn where AI genuinely helps, where it's dangerous, and how to keep a human in charge of every disclosure.
Every practical task is captured as a task card — a single, repeatable format covering the prompt, what to prepare, the expected output, the AI's limits, the red flags, the human-review checklist and the evidence requirements. The course becomes a working reference you keep using long after you finish.
A fictional industrial-components manufacturer: ~1,200 employees, three EU sites, a group with subsidiaries and leased assets, moving from GRI to ESRS. A rich environmental block (Scope 1–3, energy, waste, water) and a strong social block (health & safety, LTIFR, contractors). Mercurius runs through the entire lifecycle and the capstone, so you practise on one realistic dataset from end to end.
Every other London Reporting Academy course is built around real human support — that's our line, AI-powered, always human-in-the-loop. This free course is different by design. Consider it an open door — the same high-quality curriculum built by senior practitioners, the same specialist Study Studio and the practitioner method our paying students use, opened to you free. The trade is honest: Free Access is AI-only self-study, with no support team, no mentor and no graded review. Experience how LRA actually works with AI on real disclosures — then add real human support when you're ready.
When you want a real practitioner in the loop — question support, mentor review of your own drafts, live cohorts and a capstone reviewed by an expert — that lives in our paid courses, such as the Certified ESRS course and the ESG Reporting Full Stack. Browse them all on the courses page. Bringing this to a team? The Corporate Programme below adds full personalisation and human delivery.
ESG reporting isn't learned by memorising definitions, and it can't be handed to a model. It takes judgment — knowing which requirements matter, where data is weak, which claims need evidence and where a confident-sounding answer is simply wrong. AI gives you speed and continuity; the human calibrates direction, owns the decisions and signs off the disclosure.
So the course teaches the boundary as carefully as the capability. AI can be an analyst, a document assistant, an editor, an internal reviewer and an assurance helper. AI cannot own professional judgment, be accountable for disclosures, or be a source of unverified facts. That line runs through every module.
"This is not just a course about prompts. It's a practical system for preparing, checking and governing ESG reporting with AI — with human judgment, an evidence base, governance and assurance readiness."
Built by reporting practitioners who use AI on live disclosures — and build the AI tooling for it — so you learn how the work is really done, not how a model imagines it.
The course is organised around the real reporting workflow — standards, boundary, double materiality, data collection, data quality, benchmarking, drafting, external requests, internal review, assurance and governance — not a loose collection of prompts to copy.
Each task uses one 12-field format: task, type, lifecycle stage, when AI fits, what to prepare, prompt evolution, expected output, AI limits, red flags, human-review checklist, evidence requirements, and a worked Mercurius example. The Playbook and Prompt Library build from these.
Every card shows a prompt growing Basic → Enhanced → Complete, so you learn the reasoning a practitioner adds — framework text, company context, data, constraints — instead of memorising a finished prompt that ages out.
Red flags, human review and evidence requirements sit inside each card. You always paste the current text of the standard — never trust the model's memory — and every claim has to trace to a source.
Many courses teach you to write with AI. Module 12 teaches you to check with AI — completeness, consistency, KPI-vs-narrative, unsupported claims and greenwashing risk — and how to stop the model from "approving" a claim that has no evidence behind it. It's the module that turns AI from a drafting toy into a quality control tool.
Same 14-module method. Free Access is AI-only self-study. The Corporate Programme adds full personalisation and human delivery.
All 14 modules, the ESG AI Playbook, the Prompt Library and the running Mercurius case — inside the AI-powered Study Studio. Self-study at your own pace, with the AI Tutor and AI Avatar on every lesson. No support team, no mentor, no graded capstone — that's the trade for free.
The full programme tailored to your organisation — your sector, data and reporting context — delivered by a senior trainer. Adds the graded capstone, the ESG AI Governance Pack, an AI usage policy, an AI maturity assessment and a live workshop. Online, on-site at Canary Wharf, London, or hybrid.
Guided Flex, Live Cohort and 1:1 Expert Mentorship — across ESRS, IFRS S1/S2, GRI, Assurance and the Full Stack programme — all add human guidance, mentor review and a graded path. This free course is the AI taster; those are the supported journey.
From first lesson to certificate — what the journey looks like on each route.
Best for: individual practitioners who want the full method, free, and are happy to learn solo.
Best for: ESG, reporting and finance teams adopting AI across their reporting cycle together.
The free course lives in the same specialist Study Studio LRA builds — a new generation of sustainability reporting education, not generic online learning. You get the AI Tutor on every lesson, Dr. Kurinko's AI Avatar, the proprietary ESG knowledge base and the Mistake Coach.
On the Free Access route the AI tooling is included, but the human expert support desk is not — that's reserved for the paid courses and the Corporate Programme. It's the one honest trade for a free, AI-only route.
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Step inside the real thing — the Studio our learners enjoy every day, free.
Practical tasks follow one 12-field card — so the course doubles as a working reference you keep using on real reporting work.
Each card grows a prompt Basic → Enhanced → Complete, teaching the practitioner reasoning rather than a finished line to copy.
You always paste the current standard text and tie every claim to a source. Calculations stay in spreadsheets and systems — AI is for interpretation and review, not arithmetic.
A frontier-model AI Tutor is pinned to every Studio page — explain, simplify, translate, ask a follow-up. When text isn't enough, Dr. Kurinko's AI Avatar walks you through it.
Roughly 24–32 hours of core programme, about 40% method and 60% practice, ending in a capstone on the Mercurius case. Each practical module produces a real working artefact.
What generative AI is in plain terms, why it sounds confident even when wrong (hallucination), where it helps in ESG and where it's dangerous, and why it never replaces the expert in regulated disclosure.
What you must never upload, data classification across public / enterprise / local environments, anonymisation, audit trail and reproducibility — plus a checklist for choosing tools without locking onto a model that ages out.
Clarity, specificity, context and format; the Role–Task–Format frame with framework, company and data layers; and the six types of ESG task — descriptive, analytical, comparative, drafting, prescriptive and reviewer.
A navigator for the whole lifecycle: for each stage, what the specialist does, what AI can do, what can't be delegated, the stage's red flag and the expected output.
Extract requirements from GRI, ESRS, ISSB and SASB, map between standards, and set the organisational and value-chain boundary. Red flag: never trust the model's memory — always paste the current requirement text.
Output: disclosure checklist + boundary memoBuild a long list, structure stakeholder input, analyse impacts, risks and opportunities, and assemble an IRO register — with the final judgment on materiality kept firmly human.
Output: long list + IRO registerData-request templates, ESG and supplier questionnaires, Scope 3 requests and follow-ups — using AI to spot gaps and inconsistencies, never to confirm that data is accurate.
Output: data request packFind missing data and anomalies, compare year on year, and turn a KPI table into a narrative. Red flag: LLMs are unreliable for calculations — keep arithmetic in spreadsheets and systems.
Output: data quality memo + KPI narrativeCompare competitor disclosures, build a benchmark matrix, find and prioritise gaps, and produce a readiness roadmap — with every figure checked to its source page, never blended across companies.
Output: benchmark matrix + gap roadmapDraft governance, climate, workforce and business-conduct disclosures, and rewrite technical text into a neutral reporting style — with a hard rule: only provided facts, no added claims, missing data flagged explicitly.
Output: draft disclosureDraft responses to CDP, EcoVadis and rating questionnaires, adapt disclosures for investors, and build board summaries and monthly performance reviews — without ever claiming more than the report supports.
Output: questionnaire response + board summaryMany courses teach writing with AI; this one teaches checking with AI. Completeness, consistency, KPI-vs-narrative, unsupported claims and greenwashing detection — and stopping the model from “approving” a claim with no evidence behind it.
Output: ESG Review LogBuild an evidence register, link disclosures to data sources, prepare for auditor questions and find weak evidence — using the source hierarchy, where the strength of evidence must match the risk of the claim.
Output: evidence registerAn operating model (AI draft → specialist review → data-owner validation → legal → approval → assurance → publication), an ESG AI policy, responsible-AI principles and an AI maturity model — turned into a 90-day adoption roadmap.
Output: AI usage policy + 90-day roadmapRun the full pipeline on one case — extract requirements, find gaps, build DMA elements, request and check data, draft a disclosure, run an AI review, catch unsupported claims, prepare an evidence register and a management summary. Graded against a nine-point rubric on the Corporate Programme.
40–60 tested task cards with prompts, limits and review checklists — a working manual for your ESG team.
Vetted templates by lifecycle stage — quality over quantity, not a raw dump of prompts.
Completeness, consistency, unsupported claims, KPI-to-narrative, cross-reference and terminology checks.
Long list, stakeholder input, IRO register, scoring review and documentation prompts.
Missing-data and anomaly detection, supplier review, period comparison; plus an evidence register and auditor Q&A pack.
AI usage policy, data classification, prompt governance, human-review checklist and maturity assessment. Personalised on the Corporate Programme.
Built for people who do the reporting, not for engineers. If you can read a standard, you can take this course.
Lead the reporting cycle with AI as a force multiplier — faster analysis, safer drafting, stronger internal review — while staying in control of every disclosure.
Add a repeatable AI method to your advisory toolkit — task cards, prompt evolution and review checklists you can apply across clients and standards.
Give the whole team one shared, safe way to use AI across data collection, drafting and quality control — with governance baked in.
Move your team up the AI maturity model — from ad-hoc use to an AI-enabled operating model — with a policy, human-review workflow and a 90-day adoption roadmap.
Finish the course and you earn a verifiable LRA certificate in AI-assisted ESG reporting — confirming you can put AI to work across the reporting lifecycle while keeping human judgment, evidence and governance in charge.
Free in price, not in depth. The free route runs the full method end to end — real standards, a realistic reporting case and the same rigour behind every paid LRA programme. This is serious, practical, hard-won knowledge — and a credential you can be proud to put your name to.
It carries a unique credential ID and a permanent verification link that employers, clients and procurement teams can confirm on request — anywhere in the world, on demand. It's issued on the same verification infrastructure behind every LRA credential: one standard, globally verifiable.
Globally verified
Distinguished expert with 15+ years in sustainability, integrated communications and corporate reporting. GRI Certified Global Trainer, PhD, University of Cambridge, 15+ years on FTSE 100 and Fortune Global 500 disclosures.
The method behind this course is distilled from 200+ live disclosure projects across sectors — the same practitioner experience behind every LRA course, and behind the AI tools LRA builds for sustainability reporting. It captures how an experienced reporter actually uses AI — and automates the repetitive parts — for speed and review, never as a substitute for judgment.
The Free Access route is genuinely free and AI-only. The Corporate Programme adds personalisation, governance and human delivery.
Want human support? The free route is AI-only by design. For question support, mentor review of your own drafts, live cohorts and a graded capstone, see the paid LRA courses on the courses page — every one is built around real practitioner support.
What this free course is, what's included, and where the human support lives.
Yes — genuinely free. No card, and no trial that quietly converts. And it's not a watered-down taster: it's the full 14-module practitioner method, built to the same professional standard as every other LRA course — just opened up at no cost. The honest trade is that it's AI-only self-study: you get the AI-powered Study Studio, but no support team, no mentor and no graded capstone. Think of it as an open door to how LRA works with AI on ESG reporting — and, we hope, a reason to come back for a supported, paid course later.
No, and no. It's the working method LRA's own practitioners use across the whole ESG reporting lifecycle — not just a list of prompts and not automatic report-writing. You learn where AI helps and where it's dangerous, and how to keep a human in charge of every disclosure. AI drafts and reviews; you decide, evidence and sign off.
No. It's built for ESG practitioners without a technical background. If you can read a reporting standard, you can take this course. We deliberately don't tie the method to any specific model or vendor — the tool names age out in months, the judgement doesn't.
Because it's free. Every other LRA course is always human-in-the-loop — question support, mentor review, live cohorts. To offer this one at no cost we made it AI-only and self-study. When you want a real practitioner in the loop, that lives in the paid courses and the Corporate Programme.
Free Access is the full 14-module method, AI-only, for individuals. The Corporate Programme takes the same method and personalises it to your team — your sector, data and reporting context — delivered by a senior trainer, with the graded capstone, the ESG AI Governance Pack, an AI usage policy, a maturity assessment and a live workshop. It's enquiry-led; pricing is agreed during planning.
Module 2 is dedicated to exactly this — AI hygiene and data classification. You learn what must never be uploaded, how to work across public, enterprise and local environments, and how to keep an audit trail. The course teaches the discipline; your own tooling and policy decide what you put where.
Yes — finish the course and you earn a verifiable LRA certificate with a credential ID and a permanent verification link. On the Corporate Programme the certificate follows a graded capstone reviewed against a nine-point rubric.
The method is standard-aware — it works across GRI, ESRS, ISSB (IFRS S1/S2) and SASB, and teaches you to map between them. It's not a deep course on any single standard. For deep, human-supported standard mastery, see the Certified ESRS course or the ESG Reporting Full Stack.
Question about the wider LRA learning model? See How We Deliver Our Courses. Anything specific to this course? Email lra@reporting.academy.
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