๐Ÿ’ผ Skilly Work ยท Financial services ยท Central Bank of Ireland

The Central Bank expects AI governance you can evidence.

The AI Act covers technical controls; the Central Bank covers governance. Neither proves your people can use AI responsibly. Skilly Work scores how your workforce really uses AI and turns it into an audit-ready record. Prove your people, not just your technology, are AI ready.

Why this matters now

AI is a supervisory priority in Irish financial services

The Central Bank of Ireland is expected to be designated the market surveillance authority for AI in the financial services within its remit, under the forthcoming Regulation of Artificial Intelligence Bill 2026. Its Regulatory & Supervisory Outlook already names AI as a supervisory priority and expects firms to demonstrate AI governance, accountability, human oversight and ongoing monitoring. A completion certificate demonstrates none of that. A record of how your people actually behave does.

The mapping

What the Central Bank expects, and what Skilly Work evidences

Ten expectations, three clusters. Each one-liner is the evidence Skilly Work gives you; open a row for the detail and the honest boundary of what stays your control.

Oversight & accountability

Who is watching, and who answers

Board and senior-management oversight of AI useDirectors run the same cycle; the board dashboard proves it.

Directors and senior managers reflect like staff, and the board dashboard shows participation and competency by level โ€” oversight evidenced at the top of the house, not just asserted in a policy.

Human oversight of material AI-enabled decisionsThe habit Hold the decision is scored: who keeps what human.

The evidence pack shows where the judgement about what to keep human โ€” above all decisions about customers โ€” is strong or thin, by role and risk.

It evidences that people understand where oversight is needed; the oversight control itself stays yours.

Clear accountability for AI decisionsEvery reflection is timestamped to a named person.

Each person carries a standing on each habit and a full scored record, so accountability for how AI is used traces to people, not an aggregate.

Risk, data & transparency

Day-to-day control of AI use

Risk management and risk awarenessScenario reflections build awareness; live risks raise alerts.

Reflections cover AI bias, unverified output, privacy, cyber exposure and over-reliance. A live risk raises an alert with a severity and an action to close, which joins the audit trail.

This is workforce risk awareness and people-side risk surfacing, not your model-risk-management framework.

Data governance in day-to-day useThe habit Ring-fence scores control of what goes into AI tools.

The risk screen also catches data exposure and shadow AI โ€” evidencing that people understand and apply your data-handling rules.

It is not itself a data-governance framework; it evidences the behaviour your framework requires.

Transparency about AI decision-makingThe habit Acknowledge scores openness about AI use.

Scored against your own disclosure norms, in line with Article 50 of the EU AI Act, live from August 2026.

Controls over third-party AI providersCovers external tools and shadow AI, against your own policy.

Skilly reads your AI policy, so feedback references your approved tools and vendors, not generic ones.

It evidences responsible staff use of third-party tools; it does not perform vendor due diligence.

Ongoing evidence

Tracked over time, export-ready

Monitoring and validation across the AI lifecycleQuarterly cycles track capability over time, not once.

Trends by team and role show whether capability is actually improving, cycle over cycle โ€” tracked, not certified once.

A responsible-AI culture, and continuous improvementA recurring practice keeps responsible use visible; honesty stays safe.

Owning a near miss you caught yourself is scored as awareness, not marked down โ€” so people reflect candidly, cycle after cycle.

Evidence for internal audit and supervisory reviewEverything exports as an audit-ready pack, after human review.

Standing on each habit, the scored reflection record with any manager overrides, and the risk log with actions taken โ€” per person and per cohort.

Where Skilly Work fits

The evidence layer for people, not a substitute for your controls

Skilly Work evidences the people dimension of AI governance. It does not provide your model-risk controls, technical documentation, cybersecurity controls or the governance framework itself. Those remain your firmโ€™s own controls, and the Central Bank supervises them directly. What Skilly Work closes is the gap those controls cannot: proving that your people understand and apply them. Governance and technology make AI safe to deploy. Skilly Work evidences that your workforce uses it well.

For internal audit and supervisory review

What you can put on the table

When a supervisor or internal auditor asks how your people use AI, Skilly Work lets you answer with a record rather than an assertion.

Participation across the workforce, and separately for board and senior management.

Competency standing on each SHARP habit, broken down by business unit and role.

Where applied judgement is thin, framed as a development plan, not just a score.

The AI-risk log: alerts raised, their severity, and the action taken to close each one.

Trends across cycles, showing whether capability is improving over time.

Per-person evidence packs, produced after human review, for named-individual accountability.

Evidence that staff reflected against your own AI policy, not a generic course.

A worked example

A fund administrator rolls out Microsoft Copilot

A CBI-regulated fund administrator gives its operations team a generative-AI assistant. In a supervisory review, the questions come quickly.

  • How are staff trained to use it, and did the training change behaviour?
  • How do they recognise an unreliable or hallucinated output?
  • Who decides what the tool is trusted with, and what stays human?
  • How is human oversight of material decisions evidenced?
  • Can you show competence across your team, not just a course completion?

Skilly Work does not answer these on its own; your technical controls and governance framework do. What it adds is the workforce evidence: a scored, timestamped record that your operations team can spot unreliable output, know what to keep human, ring-fence what goes into the tool and disclose AI use, refreshed each quarter and exportable for the review.

Start with one team, one quarter

A structured pilot in one team hands you a real evidence pack you can show your board, risk function or the Central Bank. Try the interactive demo now with no sign-up, or request early access to stand up a first cycle.

Skilly Work is a workforce-evidence product, not legal or regulatory advice. A firm evaluating it will form its own view of how it fits its obligations under the EU AI Act and Central Bank of Ireland supervisory expectations. Skilly Work is in early-access preview.