For many organizations, AI is no longer an experiment. It is now embedded in processes that directly impact revenue, costs, risks, and valuation. Pricing algorithms, forecasting models, and decision-making systems influence daily choices that ultimately affect financial reporting.
This fundamentally changes the conversation around AI.
The question is no longer simply: is AI properly designed and controlled?
More importantly: can we rely on the outcomes of AI in our financial figures?
At Coney Minds, we therefore do not approach AI as a standalone technology issue, but as an integral part of processes that ultimately flow into the financial statements.
From that perspective, we have built our approach as a logical three-step framework. An approach that starts with insight into design and governance, but deliberately progresses toward the core question:
How does AI actually operate within your organization — and what does that mean for the auditability of your financial reporting?
The first step focuses on whether your organization is ready to apply AI responsibly. We assess how AI is embedded within your processes. How are models structured? What data is being used? Which governance mechanisms are in place? And how are AI-related risks identified and controlled?
This step provides insight into:
For many organizations, this forms a necessary foundation. It helps create oversight and ensures that AI is not only effective, but also responsibly implemented.
At the same time, this is only the beginning.
Because a well-designed framework still says nothing about what is actually happening in practice.
AI Readiness ScanThe second step aligns the design of AI with relevant standards and expectations.
We assess whether the setup of AI systems complies with applicable frameworks, regulations, and best practices. This can result in assurance reports that provide insight into the level of compliance and control.
For organizations, this is important toward stakeholders such as:
It provides comfort that AI systems are designed in accordance with agreed standards.
But again: compliance by design is not the same as assurance over operational behavior.
AI Assurance- Design & ImplementationThe third step is where the real audit perspective begins for us. Here, the focus shifts from design to operation. Not how AI is intended to function, but what AI is actually doing in practice.
Which decisions are being made?
How do those decisions influence processes?
And what effect do they have on transactions, revenue, costs, and valuation?
At this stage, we analyze:
We do this through data analytics, process intelligence, and in-depth understanding of your processes. The objective is clear: determine whether the operation of AI is reliable and whether it can be relied upon within the financial statement audit.
AI Assurance – Optionele EfficiencyConey Minds originated as a data-driven audit organization. We believe real assurance is not created through documentation alone, but through insight into data and processes.
That is why our focus is not primarily on frameworks or design, but on actual operational behavior.
Through our three-step approach, we help organizations:
AI changes processes.
Processes determine outcomes.
Outcomes determine your figures.
The question is not whether AI impacts your organization.
The question is whether you understand and can substantiate that impact.
That is where we help.