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Aipedia: Ecologists and environmental consultants
AI tools can populate the statutory biodiversity metric and draft biodiversity gain plans, but a wrong baseline unit or condition score can make the plan undeliverable. Because the gain plan must be approved before development starts, errors can stall a scheme and lead to claims.
Part of: AI in Ecologists and environmental consultants
In short
Mandatory biodiversity net gain in England requires at least a 10% increase in biodiversity value, measured with the statutory biodiversity metric from habitat type, size, distinctiveness, condition and location. AI tools can read survey data into the metric and draft gain plans. The risks are wrong habitat types or condition scores, off-site gains that cannot be secured, and narrative that does not match the calculation. A biodiversity gain plan must be approved before development begins, so an error discovered late can delay commencement. Claims usually seek the cost of extra units, redesign and delay.
Net gain work involves repetitive data handling: transferring habitat survey results into the metric, assigning condition, calculating units and writing the gain plan and management plan. Consultants use AI tools to map survey codes to metric habitat types, check condition criteria, draft narrative and test options for on-site and off-site delivery. CIEEM’s 2025 Summer Conference included AI biodiversity reporting tools among its sessions.
The speed is attractive on schemes with large or complex habitat inventories. The danger is that the metric gives a confident number whatever goes into it.
According to GOV.UK guidance, biodiversity net gain sits in Schedule 7A of the Town and Country Planning Act 1990, inserted by the Environment Act 2021, and applies to permissions granted on applications made on or after 12 February 2024, subject to exemptions. The objective is at least a 10% increase in biodiversity value against the pre-development value of on-site habitat. The completed metric must be submitted with the biodiversity gain plan, which must be approved before development begins. Significant on-site enhancements must be maintained for at least 30 years.
The CIEEM Code requires accuracy and regard to published technical guidance (clause 4), competence (clause 3) and supervision of staff (clause 6). Departures from published guidance need recorded evidence, and limitations of information relied on should be stated.
Typical AI-related errors in metric work include the following:
Illustrative scenario. A consultant uses an AI tool to populate the metric from a habitat survey spreadsheet. Several hedgerow and grassland entries are assigned higher condition than recorded, so the baseline is understated and the on-site proposals appear to deliver the required gain. After permission, the planning authority’s review of the gain plan finds the error. The developer cannot discharge the pre-commencement condition without buying off-site units and revising the landscape scheme. It claims the extra cost and delay from the consultant.
Upstream errors matter too. A baseline built on AI habitat mapping that was not ground truthed carries its mistakes straight into the metric.
Claims over metric errors are usually framed as professional negligence and PI commonly responds, subject to the policy terms. The difficult issue is often loss: the client may have needed some additional units anyway, so experts will argue about the difference between what was spent and what an accurate assessment would have required. Long-term management obligations can also raise questions about advice given years before a claim. Apex has written about how BNG metric claims work and PI for biodiversity net gain generally.
For any metric populated with AI help, a second competent person should check the inputs before the numbers leave the office. Useful controls are:
Apex arranges PI for ecologists who deliver net gain assessments and gain plans. A broker reviews your cover and how your policy treats AI-assisted metric work and long-term management advice. See the AI in ecology consultancy overview and AI in EIA ecology chapters.
Nothing in the CIEEM Code prohibits it. You remain responsible for accuracy, so every input should be reconciled with survey data and checked by a competent ecologist before the metric is submitted with the gain plan.
The biodiversity gain plan must be submitted and approved before development begins. If the metric is wrong, the plan may not be approved until the baseline is corrected and additional gains are secured, which can push back the start on site.
If the client claims the cost was caused by your negligent assessment, PI commonly responds to that claim, subject to the terms, limit and excess. Recoverable loss is usually the difference your error made, not the full cost of units the scheme would have needed anyway.
Tell us about your firm and the work you do. A broker will review how your current PI treats AI-assisted work, or arrange new cover. No fee for a quote. Or call 0117 325 0027.
Start a PI quote Request a callbackApex Insurance Brokers Limited is authorised and regulated by the Financial Conduct Authority. Registered in England and Wales, company number 07014570. This page is general information about how AI is used in the profession and how insurance may respond. It is not legal, regulatory or insurance advice on your circumstances, and it does not guarantee that cover will be available or on what terms.
