Aipedia: Energy assessors and retrofit coordinators
Advisers can use AI to plan how rented homes reach EPC C by 1 October 2030, but they remain responsible for the measures, costs and exemptions they recommend. Landlords face fines of up to £30,000 per property, so poor advice quickly becomes expensive.
Part of: AI in energy assessors and retrofit coordinators
In short
The January 2026 government response sets EPC C for all private tenancies using new EPCs, with compliance by 1 October 2030, a cost cap of up to £10,000 per property, EPCs before and after works and fines up to £30,000 per property. AI tools trained on older material may plan for the old rating, misapply the cap or miss exemption changes, such as removal of the heritage exemption. Landlords carry the compliance duty, but may claim against advisers. PI usually responds to negligent advice, subject to the terms and aggregation.
Landlords want three answers: what rating the property will get under the new EPC, what works will get it to C, and what it will cost. Assessors and energy consultants are using AI tools to model options, draft measure packages and answer landlord questions at scale, often for portfolios.
The rules are still being finalised, and the tools may not know that. A model trained on older material may apply the old rating, the old standard or rules that have since changed.
The government response on privately rented homes (January 2026) sets the framework landlords are planning around. Its main points are:
The EPC reform response also makes HMO and short-term let changes and removes the heritage exemption. Exemptions and detailed rules will be set by the regulations, so advice should rely on the final text when it is made, not on a chatbot's summary. For assessors, reg 24(1) of the EPB Regulations 2012 still requires reasonable care and skill.
Landlord advice carries a direct link between the adviser's words and the landlord's money. The main risks are:
Illustrative: a consultant uses an AI tool to produce improvement plans for a landlord's portfolio. The plans are built around the old rating and do not address fabric performance. The landlord spends close to the cap on several properties, then finds the post-works EPCs fall short. The landlord faces more works, rent disruption and possible penalties, and claims against the consultant for the wasted spend.
The legal duty to comply sits with the landlord, and fines are imposed on the landlord. Whether the landlord can recover losses from an adviser depends on what the adviser was asked to do and what they said. PI usually responds to negligent advice claims, subject to the policy terms. Fines are generally not something an adviser's PI pays directly, but a landlord may claim related losses, and whether those are recoverable depends on the facts and the wording. Portfolio work raises aggregation questions, and limits should reflect the number and value of properties advised on; see any one claim versus aggregate limits. Landlord clients may also ask about HMO licensing and insurance.
Landlord work needs tighter scoping than a single EPC. Practical steps include:
Related guides cover AI and the move to new EPC metrics, AI-written EPC improvement advice and AI grant eligibility checks.
Apex arranges PI for energy assessors and consultants advising landlords. A broker reviews your limit and aggregation terms for portfolio work and how your policy treats AI-assisted advice. Back to the AI in energy assessment hub.
The January 2026 government response sets EPC C for all tenancies by 2030 using new EPCs, with compliance by 1 October 2030. Legislation is due in force in 2027, so check the final regulations before advising.
The government response sets a cost cap of up to £10,000 per property. How the cap applies in detail will depend on the final regulations, so advice should reflect the legislation once made.
Fines are imposed on the landlord, and PI does not generally pay an adviser's client's fines directly. A landlord may still claim related losses if advice was negligent, and recovery depends on the facts and the policy terms.
AI can help organise portfolio data, but each property needs individual checking. One flawed template repeated across many homes can create many claims, so check your limit and aggregation terms.
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