Operational compliance & regulatory risk
Here's what AI can do for this role — and what still needs a human. Built straight from ENSEK's own job advert, running live on real data. Not a slide about AI. The job, getting done.
Every line on the left is lifted from ENSEK's actual job ad. If a card lacks a harvested JD line, it is omitted. On the right is the AI doing it — with eligible cards running live against the warehouse and offline inspection clearly labelled in the workspace.
“Support the Head of GRC in developing, implementing and maintaining the organisation’s governance framework to support effective oversight, accountability and decision-making.”
What is the PSR vulnerability coverage by region — accounts registered, regional penetration, and PSR accounts in arrears (the highest-risk compliance exposure)?
table“Help develop and maintain the enterprise and operational risk registers, identifying emerging risks, and ensuring appropriate mitigations are in place.”
How does the arrears rate vary by customer affluence band — the Consumer Duty affordability monitoring view?
table“Identify, assess, prioritise and monitor risks that may impact the organisation’s operations, assets, obligations or strategic objectives.”
What is the smart meter rollout compliance gap — traditional vs smart accounts by region, and where is the mandate gap largest?
table“Work with stakeholders to design, implement and monitor effective controls to reduce risk exposure and strengthen organisational resilience.”
Which regions have the highest concentration of F/G-band accounts in the supplied book — the MEES obligation view from the operational estate?
table“Produce high-quality management information and dashboards that give leadership clear visibility of assurance performance, audit status, and risk exposure.”
What does the operational risk concentration look like — churn-risk band segmented by arrears, PSR overlap, and gross debt?
deviationThe honest other half. AI does the analysis; a person owns the decision — especially where regulation, fairness and accountability bite.
A plain-English question — the same one the job ad describes — is translated to SQL by the agentic backend.
Curated cards run server-side against MotherDuck when eligible. The workspace separately labels any local inspection path.
Runs through the workspace live path when a curated server query is available; otherwise the local inspection path is labelled.. No synthetic numbers.
Each figure carries a falsifier — recomputed from the result set, not a stored number, so it can't quietly drift.
It's the role getting done: curated questions run live server-side against the warehouse; local inspection is labelled inside the workspace.
Open the live workspace →Provenance. 5,000-row local verification dataset of the national energy estate — same accounts dataset as the credit-risk workspace. Distributions match ENSEK's real account book. No real customer data.
It's Sorted — I took ENSEK's job ads and didn't write a report on what AI could do. I built it. Get the rest sorted →
I'm trained on this proof and the real ENSEK: the Ignition meter-to-cash platform (seven modules), the move under Centrica in 2024, 7M+ energy accounts migrated for suppliers like British Gas and Utility Warehouse, and the Ofgem framing. Ask me how the Data Analyst function changes shape, or which open roles map to which Ignition module.