Question 1

What is AI Compliance and why is it becoming business-critical?

Accepted Answer

AI Compliance is the discipline of ensuring your organisation's use of artificial intelligence meets its legal, regulatory, and ethical obligations. As AI becomes embedded in business decisions, regulators globally are introducing binding requirements making compliance not a choice, but a business imperative.

Question 2

How is AI Risk different from traditional technology risk?

Accepted Answer

Traditional technology risk is largely predictable and static. AI risk is dynamic models drift, data changes, and outputs can become biased or inaccurate over time without any visible system failure. AI Risk management requires continuous monitoring, not just point-in-time assessments.

Question 3

Which regulations apply to our use of AI?

Accepted Answer

That depends on your sector, geography, and how AI is being used within your organisation. Key frameworks include the EU AI Act, the UK's pro-innovation AI regulatory approach, DORA for financial services, and sector-specific guidance from the FCA, ICO, and other regulators. Bushey maps your specific obligations and builds a compliance programme tailored to your context.

Question 4

What is the EU AI Act and does it apply to us?

Accepted Answer

The EU AI Act is the world's first comprehensive legal framework for AI, classifying systems by risk level and imposing proportionate obligations on developers and deployers. It applies to any organisation operating in the EU or deploying AI that affects EU citizens regardless of where the organisation is headquartered.

Question 5

How do you assess our current AI compliance position?

Accepted Answer

We begin with a structured AI Compliance Assessment mapping every AI system in use across your organisation, classifying its risk level, identifying applicable regulatory obligations, and producing a clear gap analysis. You receive a prioritised remediation roadmap with defined ownership and timescales.

Question 6

What are the consequences of non-compliance with AI regulations?

Accepted Answer

Consequences range from significant financial penalties up to €35 million or 7% of global turnover under the EU AI Act — to reputational damage, regulatory intervention, and operational restrictions. Beyond fines, non-compliance erodes customer and stakeholder trust in ways that are difficult to recover from.

Question 7

How does Bushey help us manage ongoing AI Risk?

Accepted Answer

We establish the monitoring frameworks, review cadences, and escalation protocols needed to manage AI risk on a continuous basis not just at deployment. This includes model performance monitoring, data quality controls, incident response procedures, and regular risk reporting to your board and senior leadership.

Question 8

We use third-party AI tools and platforms. Are we still responsible for compliance?

Accepted Answer

Yes. Regulatory accountability sits with the organisation deploying AI not solely the vendor that built it. If an AI tool is used within your business to inform decisions or interact with customers, you carry compliance obligations for how it is used, regardless of who developed it.

Question 9

Can Bushey support us through a regulatory investigation or audit?

Accepted Answer

Yes. We provide specialist support for organisations facing regulatory scrutiny of their AI systems helping you evidence compliance, prepare documentation, engage with regulators, and implement any remediation required. Early engagement with our team significantly improves outcomes in these situations.

Question 10

How do we build a culture of AI compliance across our organisation?

Accepted Answer

Compliance cannot live solely in a legal or risk team. We work with your leadership to embed AI compliance awareness across the business through training programmes, clear policies, defined accountability structures, and a governance culture where responsible AI use is everyone's responsibility, not an afterthought.

Question 11

What makes this different from standard programme management?

Accepted Answer

Programme management focuses on tasks, timelines, and budgets. This is about something different, taking accountability for how AI delivery is governed and ensuring outcomes are owned, not just tracked. We define success by what holds after go-live, not what was reported during delivery. A programme manager coordinates. We own.

Question 12

We already have a PMO. Why would we need this?

Accepted Answer

A PMO provides structure and reporting. It does not typically take accountability for outcomes or govern how AI decisions are made and evidenced. If your PMO is already doing that and can demonstrate it you may not need us. If there is ambiguity about who truly owns the AI outcome and whether decisions can be defended, that is the gap we fill.

Question 13

How does this work when multiple vendors are involved?

Accepted Answer

This is the environment the model is designed for. We take accountability for how delivery is governed across all parties, vendors, internal teams, system integrators, and partners. Every contributor operates under one governed model, held to the same standard. The complexity of a multi-vendor environment is managed as one connected system, not distributed across it.

Question 14

At what stage should Bushey be engaged early or once delivery is already underway?

Accepted Answer

Earlier is always better. Governance and control are significantly easier to establish at the outset than to retrofit once delivery is in motion. That said, we regularly engage mid-programme when organisations recognise that control has started to drift or that the current model cannot scale with the AI initiative. In either case, we establish what is needed and hold it throughout.

Question 15

How do you handle AI systems that continue to evolve after go-live?

Accepted Answer

This is one of the core reasons AI delivery requires a different governance model. AI systems learn, adapt, and change in ways that static delivery frameworks were not designed to manage. Our model maintains active governance through to operational stability, and beyond where needed, ensuring that controls evolve alongside the system and that accountability does not end at go-live.

Question 16

What does "accountability for outcomes" actually mean in practice?

Accepted Answer

It means we define what success looks like at the outset, not in vague terms, but specifically and measurably. We track progress honestly against that definition, surface issues before they escalate, and remain accountable until outcomes are confirmed stable in live operation. It means that if something is not working, we say so, and we own the resolution, not just the report.

Question 17

How do you ensure AI decisions can be explained and defended?

Accepted Answer

Every significant AI-influenced decision is documented, evidenced, and traceable. We establish governance structures that require decisions to be owned at the appropriate level, supported by evidence rather than assumption, and recorded in a way that can withstand scrutiny from boards, regulators, or auditors. Explainability is built into how delivery is run, not added after the fact.

Question 18

What happens when scope changes or something unexpected emerges?

Accepted Answer

Change is governed, not absorbed. Nothing enters scope without a decision, and every decision is owned, evidenced, and communicated. When something unexpected emerges, we surface it early, assess its impact against defined outcomes, and escalate or resolve with full visibility. You are never presented with a problem that we already knew about.

Question 19

How does this integrate with our existing internal governance and risk frameworks?

Accepted Answer

We work within your existing governance structure, not alongside it. Our model is designed to integrate with how you already manage risk, compliance, and oversight adding the specific controls that AI delivery requires without duplicating or replacing what already works. Where gaps exist between your existing framework and what AI governance requires, we identify them early and address them as part of the engagement.

Question 20

How do we know it is working?

Accepted Answer

You receive a single, consolidated view of progress, risk, and decisions not separate reports from separate workstreams. Reporting reflects reality, not confidence. At every stage gate, you have the information needed to proceed, pause, or challenge. The measure we hold ourselves to is straightforward: you should never be surprised by something we already knew. If you are, that is on us.

Question 21

What is AI Governance and why does our organisation need it?

Accepted Answer

AI Governance is the framework of policies, controls, accountabilities, and processes that ensure your organisation's use of AI is responsible, transparent, and aligned to both business objectives and regulatory requirements. Without it, AI adoption creates risk that is difficult to detect until something goes wrong.

Question 22

What is AI Assurance and how does it differ from AI Governance?

Accepted Answer

AI Governance defines the rules and structures. AI Assurance independently verifies that those structures are working as intended that AI systems are performing as expected, decisions are explainable, and risks are being managed effectively. Together they form the foundation of responsible AI adoption.

Question 23

Is AI Governance only relevant to large enterprises?

Accepted Answer

No. Any organisation using AI to inform decisions, automate processes, or interact with customers carries governance obligations regardless of size. The regulatory landscape is evolving rapidly, and establishing governance early is significantly less costly than retrofitting it after a compliance failure.

Question 24

What regulations and standards does Bushey align its AI Governance work to?

Accepted Answer

We align to emerging and established frameworks including the EU AI Act, ISO/IEC 42001, NIST AI Risk Management Framework, and sector-specific regulatory guidance across financial services, healthcare, and the public sector. Our frameworks are designed to evolve as the regulatory landscape matures.

Question 25

We have AI tools already deployed. Is it too late to establish governance?

Accepted Answer

It is never too late but the sooner governance is established, the lower the risk exposure. We regularly work with organisations that have deployed AI without adequate controls in place. We assess what is live, identify the gaps, and implement governance retrospectively without disrupting current operations.

Question 26

How does AssureChange® apply to AI Governance?

Accepted Answer

AssureChange® provides the structural backbone for our AI Governance engagements defining accountability, establishing audit trails, embedding review cadences, and ensuring that governance is not just documented but actively practiced. It transforms governance from a paper exercise into a lived operational discipline.

Question 27

What does an AI Assurance review actually involve?

Accepted Answer

An AI Assurance review examines your AI systems across four dimensions: model performance and accuracy, data integrity and lineage, decision explainability and bias assessment, and operational controls. We produce a clear findings report with a prioritised remediation plan and defined ownership for every action.

Question 28

How do you handle AI bias and ethical risk?

Accepted Answer

Bias and ethical risk are assessed as a core component of every AI Governance and Assurance engagement. We examine training data, model outputs, and decision pathways to identify where bias may exist and work with your teams to implement controls that reduce and monitor it on an ongoing basis.

Question 29

Can Bushey provide independent AI Assurance on a system built by another supplier?

Accepted Answer

Yes. Independent assurance is one of the most valuable services we provide. Where AI systems have been built or deployed by a third party, an independent Bushey assurance review gives your leadership and board the confidence that the system is performing responsibly and within acceptable risk parameters.

Question 30

How do we start building AI Governance into our organisation?

Accepted Answer

Book a Discovery Call with one of our co-founders. We will assess your current AI footprint, your existing governance maturity, and your regulatory obligations and give you a clear, prioritised view of where to start and what good looks like for your organisation.

Govern It, Deliver It, Prove It, One Control Layer for AI.

AI initiatives aren’t a side project sitting outside your transformation governance.

AI isn’t separate from transformation

The Bushey AI Governance Spine

Early design

Development

Deployment

Operation

Ongoing use

Delivery Control and Risk & Compliance

Delivery Control

Risk & Compliance

Where this gets tested

Can You Demonstrate  Full Control  Over How Your AI Decisions Are Made and Governed?

Can You Stand Behind Every AI-Influenced Outcome You’re Responsible For?

Your Transformation Is Not Failing on

The AI Pilot Trap

Frequently Asked Questions

AssureChange® – Frequently Asked Questions